WO2025131299A1 - Système et procédé de commande de distribution de traction et de freinage - Google Patents

Système et procédé de commande de distribution de traction et de freinage Download PDF

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Publication number
WO2025131299A1
WO2025131299A1 PCT/EP2023/087537 EP2023087537W WO2025131299A1 WO 2025131299 A1 WO2025131299 A1 WO 2025131299A1 EP 2023087537 W EP2023087537 W EP 2023087537W WO 2025131299 A1 WO2025131299 A1 WO 2025131299A1
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WIPO (PCT)
Prior art keywords
vehicle
processing circuitry
computer system
traction force
transport mission
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Application number
PCT/EP2023/087537
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English (en)
Inventor
Calle SKILLSÄTER
Johan SJÖBERG
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Volvo Autonomous Solutions AB
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Volvo Autonomous Solutions AB
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Priority to PCT/EP2023/087537 priority Critical patent/WO2025131299A1/fr
Publication of WO2025131299A1 publication Critical patent/WO2025131299A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0011—Planning or execution of driving tasks involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
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    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
    • B60W10/184—Conjoint control of vehicle sub-units of different type or different function including control of braking systems with wheel brakes
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/403—Image sensing, e.g. optical camera
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/408—Radar; Laser, e.g. lidar
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/26—Wheel slip
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/26—Wheel slip
    • B60W2520/263—Slip values between front and rear axle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/40—Torque distribution
    • B60W2520/403—Torque distribution between front and rear axle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/15—Road slope, i.e. the inclination of a road segment in the longitudinal direction
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/20—Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W2556/00—Input parameters relating to data
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
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    • B60W2556/55—External transmission of data to or from the vehicle using telemetry
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    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/18—Braking system
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    • B60W2720/10—Longitudinal speed
    • B60W2720/103—Speed profile

Definitions

  • the disclosure relates generally to the field of controlling traction force and brake forces between wheel axles of a vehicle, such as a heavy-duty vehicle.
  • the disclosure relates to a computer system, vehicle and methods for controlling traction force and brake force distribution between a first wheel axle, such as a front axle, and a second wheel axle, such as a rear axle, of an electric vehicle operating in a confined geographical area.
  • the disclosure can be applied to heavy-duty vehicles, such as trucks, buses, and construction equipment, among other vehicle types.
  • the disclosure can be applied to autonomous vehicles, such as unmanned autonomous vehicles operating in a confined geographical area.
  • autonomous vehicles such as autonomous heavy-duty vehicles (e.g., haulers, trucks, and semi-trailer vehicles) are designed to carry heavy loads.
  • the heavily laden vehicles must be able to start from standstill, even in uphill conditions, accelerate on various types of road surfaces, as well as brake in a controlled and reliable manner at all times. It may also be important that the vehicle can be operated within the confined geographical area in an energy-efficient manner without unnecessary component wear.
  • heavy-duty vehicles such as autonomous vehicles operating in a confined geographical area.
  • a computer system for controlling traction force and brake force distribution between a first wheel axle and a second wheel axle of an electric vehicle operating in a confined geographical area.
  • the computer system comprises processing circuitry configured to: obtain transport mission characteristics for an upcoming transport mission for the vehicle; determine at least one vehicle pathway characteristic for the upcoming transport mission based on topology data of an intended route for the transport mission; on the basis on the determined transport mission characteristics and the determined at least one vehicle pathway characteristic, determine a speed profile for the vehicle for performing the transport mission along the intended route; predict a risk for wheel slip based on the determined at least one vehicle pathway characteristic and the determined speed profile; generate a traction force and braking force distribution profile for the vehicle along the intended route based on the predicted risk for wheel slip; obtain a real-time vehicle position; in response to the obtained real-time vehicle position, control the distribution of traction force and braking force between the first wheel axle and the second wheel axle along the intended route based on the generated traction force and braking force distribution
  • the first aspect of the disclosure may seek to improve the control of a vehicle in areas with variable topography so as to balance the traction and braking operations of the vehicle in relation to prevailing road conditions. In this manner, it becomes possible to control the vehicle in a more favorable manner, which may not only have a positive impact on the operations of the vehicle, but also on the wear of roads within the confined geographical area. Moreover, or in particular, the disclosure may seek to avoid, or at least reduce, road wear by providing an improved traction force and braking force distribution profile configured to performing real-time adaptation to changes in the vehicle path, i.e. the route to be followed by the vehicle, in which the change may refer to e.g. changes in elevation, inclination, gradients, and terrain types.
  • a further technical improvement may include providing an improved traction and braking force distribution profile enabling controlling the vehicle on the basis of a predicted risk of wheel slip.
  • the proposed computer system allows for improving the control of an autonomous vehicle in a confined geographical area containing a variable topography.
  • the first wheel axle is a front axle
  • the second wheel axle is a rear axle
  • the first wheel axle and the second wheel axle are two rear axles.
  • the computer system may be configured to control traction force and brake force distribution between more than two axles, such as a plurality of axles, including e.g. a front wheel axle and a set of rear axles.
  • the processing circuitry may further be configured to control a differential lock of the vehicle based on the generated traction force and braking force distribution profile.
  • a technical improvement may include providing a more precise control of the operations of the vehicle. For instance, in demanding driving conditions, such as mud, a differential lock may be used, or even required, to achieve optimal traction and prevent the loss of drive force due to wheel spinning.
  • a drawback of using a differential lock continuously is increased wear on the vehicle and the road. By selectively engaging and disengaging the differential lock based on the terrain (for example, in a depression where water commonly accumulates), it becomes possible to provide improved traction when needed, while simultaneously avoiding unnecessary wear.
  • the processing circuitry may further be configured to determine a steering mode for the vehicle based on the generated traction force and braking force distribution profile. Moreover, the processing circuitry may be configured to control a steering device based on the determined steering mode.
  • the processing circuitry may be configured to control a steering device based on the determined steering mode.
  • the transport mission characteristics for an upcoming transport mission for the vehicle may comprise transport mission data indicative of at least a destination location and a destination time.
  • a technical improvement may include providing even more precise transport mission characteristics, and thus an even more accurate speed profile.
  • the transport mission data may further contain transport mission duration data, distance to be traveled and similar transport mission data.
  • the transport mission data may also contain a speed restriction profile for the transport mission, a minimum speed profile for the transport mission, desired or required speed for different segments of the transport mission (e.g., city driving, highway cruising, acceleration, deceleration).
  • the processing circuitry may further be configured to obtain transport mission data containing environmental conditions data, such as ambient temperature, which affects the efficiency and performance of e.g. the batteries, and humidity and wind conditions, which can influence aerodynamics and energy consumption.
  • environmental conditions data such as ambient temperature, which affects the efficiency and performance of e.g. the batteries, and humidity and wind conditions, which can influence aerodynamics and energy consumption.
  • the processing circuitry may further be configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the environmental conditions data.
  • the processing circuitry may further be configured to obtain transport mission data containing data about available charging infrastructure. Moreover, the processing circuitry may further be configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the available charging infrastructure.
  • the vehicle pathway characteristic may be obtained from data of a topology map over the confined geographical area.
  • the vehicle pathway characteristic may comprise data indicative of road inclination.
  • the processing circuitry may further be configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle in response to a predicted change in road inclination.
  • a technical improvement may include to further improve the generation of the traction force and braking force distribution profile in that the underlying data is further refined. Accordingly, controlling traction force and braking force based on predicted changes in road inclination may further reduce road wear as well as enhance safety, stability, and performance, thereby providing a more efficient and comfortable driving experience.
  • the topology data of the intended route for the transport mission may comprise relevant data for determining the route profile, including elevation changes, inclination and inclination changes, road grade, and terrain type (urban, highway, off-road, etc.).
  • the vehicle pathway characteristic may further, or alternatively, include traffic conditions, such as traffic congestion and stop-and-go driving conditions, which affect energy consumption and power demand.
  • traffic conditions such as traffic congestion and stop-and-go driving conditions, which affect energy consumption and power demand.
  • the risk for wheel slip may be predicted by determining a friction force between a road surface and the wheels of the first wheel axle and the second wheel axle, respectively, based on the vehicle pathway characteristic and speed profile.
  • the risk for wheel slip may be predicted from data indicative of a previous predicted high level of wheel slip.
  • data can e.g. be obtained from a vehicle that has operated along the route at a previous occasion.
  • the risk for wheel slip may be predicted by comparing predicted and/or current vehicle speed with predicted/or current wheel rotational speed.
  • the vehicle speed and the wheel rotational speed may be obtained from the vehicle pathway characteristics.
  • the realtime vehicle position may be obtained from a navigation system.
  • the navigation system may include obtaining data from various technologies such as GNSS, GPS, lidar and the like.
  • the processing circuitry may further be configured to determine a gross combined weight (GCW) of the vehicle, and further configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the GCW.
  • GCW gross combined weight
  • a technical benefit may include to further improve the generation of the traction force and braking force distribution profile in that the underlying data is further extended.
  • the processing circuitry may further be configured to determine a distribution of a payload on the vehicle, and further configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the GCW and distribution of the payload.
  • a technical benefit may include to even further improve the generation of the traction force and braking force distribution profile in that the underlying data is further extended. More specifically, by including GCW and payload distribution into the process of generating the traction force and braking force distribution profile, the operations of the vehicle are balanced in view of the weight distribution between the first wheel axle and the second wheel axle (such as the front and rear axles).
  • the processing circuitry may further be configured to determine a speed profile containing predicted acceleration and/or deceleration of the vehicle along the intended route, and further configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the speed profile containing the predicted acceleration and/or deceleration of the vehicle along the intended route.
  • the processing circuitry may further be configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle along the intended route so as to minimize road wear.
  • a technical improvement may include to further extend the road lifespan. Minimizing road wear helps extend the lifespan of roads and infrastructure. By reducing wear and tear, the need for frequent maintenance and repairs is diminished, contributing to longer-lasting roads. Minimizing road wear may also lead to less frequent and less extensive maintenance, resulting in cost reductions over the long term.
  • the processing circuitry may further be configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle before an occurrence of wheel slip associated with the predicted risk of wheel slip.
  • the processing circuitry may further be configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle before an occurrence of wheel slip associated with the predicted risk of wheel slip.
  • a vehicle comprising the computer system according to the first aspect.
  • the second aspect of the disclosure may seek to solve the same problem as described for the first aspect of the disclosure.
  • effects and features of the second aspect of the disclosure are largely analogous to those described above in connection with the first aspect of the disclosure.
  • a computer- implemented method for controlling traction force and brake force distribution between a first wheel axle and a second wheel axle of an electric vehicle operating in a confined geographical area comprising: obtaining transport mission characteristics for an upcoming transport mission for the vehicle; determining at least one vehicle pathway characteristic for the upcoming transport mission based on topology data of an intended route for the transport mission; on the basis on the determined transport mission characteristics and the determined at least one pathway characteristic, determining a speed profile for the vehicle for performing the transport mission along the intended route; predicting a risk for wheel slip based on the determined at least one pathway characteristic and the determined speed profile; generating a traction force and braking force distribution profile for the vehicle along the intended route based on the predicted risk for wheel slip; obtaining a real-time vehicle position; in response to the obtained real-time vehicle position, controlling the distribution of traction force and braking force between the first wheel axle and the second wheel axle along the intended route based on the generated traction force and braking force
  • the third aspect of the disclosure may seek to solve the same problem(s) as described for the first to second aspects of the disclosure.
  • effects and features of the third aspect of the disclosure are largely analogous to those described above in connection with the first and second aspects of the disclosure.
  • a computer program product comprising program code for performing, when executed by the processing circuitry comprised in the computer system of the first aspect, the method of the third aspect.
  • a non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry of the first aspect, cause the processing circuitry to perform the method of the third aspect.
  • FIGS. 1A - 1C illustrate exemplary views of vehicles and vehicle powertrain systems, comprising a computer system having a processing circuitry configured to control traction force and brake force distribution of the vehicle according to an example.
  • FIG. 2 illustrates an overview of a confined geographical area with a number of autonomous vehicles, according to examples.
  • FIG. 3 illustrates an example of controlling traction force and brake force distribution of a vehicle, such as one of the vehicles of FIGS. 1A - 1C, along a pathway (intended route) in the confined geographical area of FIG. 2, according to the examples.
  • FIG. 4 is a flow chart of an exemplary method to control a vehicle according to an example.
  • FIG. 5 is a schematic diagram of an exemplary computer system for implementing examples disclosed herein, according to an example.
  • the present disclosure is at least partly based on the realization that deploying and controlling electric vehicles, such as autonomous electric vehicles, in a confined geographical area may still be challenging in terms of providing an efficient and reliable operation of the vehicle, while at least maintaining sustainable road surface conditions. More specifically, hilly terrains may demand adaptability from autonomous vehicles to navigate inclines and declines seamlessly. Ensuring optimal performance across diverse terrain types while maintaining operational efficiency may thus present one challenge. Moreover, the continuous traversal of autonomous vehicles in confined areas with hilly terrain may generally also increase the risk of accelerated wear and tear on road surfaces. Uneven terrain and frequent elevation changes can lead to road degradation and compromise overall infrastructure integrity. The challenges may be particularly pertinent in applications such as mining, quarries, or construction sites where operational spaces are constrained, and the terrain is inherently rugged.
  • the present disclosure provides a computer system, a powertrain system, a vehicle including the computer system, and methods for controlling traction force and brake force distribution between wheel axles of an electric vehicle operating in a confined geographical area.
  • the disclosure may seek to improve the control of a vehicle in confined areas with variable topography so as to balance the traction and braking operations of the vehicle in relation to prevailing road conditions. In this manner, it becomes possible to control the vehicle in a more favorable manner, which may not only have a positive impact on the operations of the vehicle, but also on the wear of roads within the confined geographical area. Moreover, or in particular, the disclosure may seek to avoid, or at least reduce, road wear by providing an improved traction force and braking force distribution profile configured to performing real-time adaptation to changes in the vehicle path, i.e. the route to be followed by the vehicle, in which the change may refer to e.g. changes in elevation, inclination, gradients, and terrain types.
  • a further technical improvement may include providing an improved traction and braking force distribution profile enabling controlling the vehicle on the basis of a predicted risk of wheel slip.
  • the proposed computer system allows for improving the control of an autonomous electric vehicle in a confined geographical area containing a variable topography.
  • FIGS. 1 A to 1C Examples of such computer systems and vehicles will now be described in relation to FIGS. 1 A to 1C, in combination with FIGS. 2 to 5.
  • FIG. 1 A there is illustrated one example of a vehicle 10.
  • the vehicle 10 is here a heavy-duty vehicle, such as a truck. While the vehicle 10 in FIG. 1 A is illustrated as a truck, the vehicle 10 may be of any type of vehicle suitable for transporting people and/or goods, such as bulk material from one location to another.
  • the vehicle may be an excavator, loader, articulated hauler, dump truck, truck or any other suitable vehicle known in the art.
  • the vehicle 10 may be driven by an operator.
  • the vehicle 10 may be an autonomous vehicle that is controlled by a vehicle motion management (VMM) unit configured to individually control vehicle units and/or vehicle axles and/or wheels of the vehicle.
  • VMM vehicle motion management
  • the vehicle 10 is also an electric vehicle. Accordingly, the vehicle 10 is an autonomous electric vehicle.
  • the vehicle 10 comprises a powertrain system 14.
  • the powertrain system 14 comprises a propulsion unit 20.
  • the propulsion unit may be provided by one or more electrical machines. In other types of arrangement, the propulsion unit 20 may include a traction-supporting internal combustion engine.
  • the propulsion unit is 20 typically an energy converting unit configured to provide a torque. In this example, the propulsion unit 20 is an electric machine.
  • the electric machine 20 is further powered by a battery system and/or a fuel cell system.
  • the powertrain system 14 here also comprises any one of a battery system 21 and a fuel cell system 22.
  • the powertrain system 14 is an electric powertrain system and the vehicle 10 is a fully electrical vehicle.
  • the vehicle 10 may also include a supporting internal combustion.
  • the powertrain system 14 in FIG. 1 A comprises at least one propulsion unit in the form of one or more electric machines 20, the battery system 21 and the fuel cell system 22.
  • the powertrain system 14 is configured to provide traction power for the vehicle 10.
  • the traction power is delivered to one or more ground engaging members 15, 16, 17, e.g. one or more wheels of the vehicle 10.
  • the traction power is delivered to the wheels, such as the wheels 15 by any one of the battery system 21 and the fuel cell system 22 in cooperation with one or more electric machines 20.
  • Electric machines 20 are responsible for converting electrical energy from the battery system 21 or fuel cell system 22 into mechanical power to drive the vehicle's wheels.
  • the electric machine 20 is thus configured to provide traction power to the vehicle 10.
  • the electric machine 20 is configured to be connected to the battery system 21 and the fuel cell system 22. It should be noted that the powertrain system 14 may be provided with a plurality of electric machines 20.
  • the powertrain system 14 may further comprise additional components as is readily known in the field of electrical propulsions systems, such as a transmission for transmitting a rotational movement from the electric machine(s) to a propulsion shaft, sometimes denoted as the drive shaft (not shown).
  • the propulsion shaft connects the transmission to the wheels.
  • Some vehicles may use a traditional multi-speed transmission, while others employ single-speed transmissions or direct-drive configurations for simplicity and efficiency.
  • the electrical machine is typically coupled to the transmission by a clutch.
  • the electric machine is arranged to receive electric power from any one of the battery system and the fuel cell system.
  • the electric machine is here also arranged specifically as a traction motor for the vehicle.
  • the vehicle 10 comprises a chassis 30 and a load carrying container 31 connected to the chassis 30.
  • the chassis 30 is configured to support the load carrying container 31.
  • the load carrying container 31 is configured to carry materials, such as mining shovel or the like.
  • the vehicle 10 is supported by wheels 15, 16, 17, where each wheel comprises a tire.
  • the vehicle 10 comprises multiple axles, including a front axle 11 and a number of rear axles 12, 13.
  • the front axle 11 is here considered as a first wheel axle.
  • one of the rear axles, such as the rear axle 12, is considered as the second wheel axle.
  • the tractor unit has front wheels 15 which are normally steered, and rear wheels 16, 17 of which at least one pair are driven wheels. Any one of the front axle 11 and the rear axles 12, 13 may be configured to be driven by the powertrain system 14. In some examples, only the front axle is driven by the powertrain system 14. In other examples, only one of the rear axles, such as the rear axle 12, is driven by the powertrain system 14. In yet other examples, all axles 11, 12, 13 are driven by the powertrain system 14.
  • the rear wheels of the vehicle 10 may be mounted on tag or pusher axles.
  • a tag axle is where the rear-most drive axle is non-powered, also referred to as a free- rolling or dead axle.
  • a pusher axle is where the forward-most drive axle is not powered.
  • the vehicle 10 of FIG. 1A comprises the front axle 11.
  • the front axle 11 is provided with the pair of wheels 15.
  • the vehicle 10 of FIG. 1 A comprises two rear axles 12, 13.
  • Each one of the rear axles 12, 13 are provided with corresponding set of pair of wheels, 16, 17, respectively.
  • FIG. IB schematically illustrates another example of an autonomous electric vehicle 10.
  • the vehicle 10 of FIG. 10 is a load carrying vehicle in the form of a hauler.
  • the load carrying vehicle 10 comprises the chassis 30, the load carrying container 31 connected to the chassis 30, and a plurality of wheels 15, 16.
  • the vehicle 10 of FIG. IB further comprises the front axle 11.
  • the front axle 11 is provided with the pair of wheels 15.
  • the vehicle 10 of FIG. IB comprises the rear axle 12.
  • the rear axle 12 is provided with the corresponding set of pair of wheels 16.
  • the vehicle 10 of FIG. IB is also an example of an autonomous electric vehicle comprising front wheel and rear wheel steering.
  • the vehicle 10 here comprises a front wheel steering device 24 and a rear wheel steering device 26.
  • Each one of the front wheel steering device 24 and the rear wheel steering device 26 is configured to control steering of the respective axle and its corresponding wheels.
  • Each one of the front wheel steering device 24 and the rear wheel steering device 26 is connected to the computer system 100.
  • the computer system 100 is configured to control steering of the front axle 11 and the rear axle 12.
  • the steering of the front axle 11 and the rear axle 12 can be performed either individually, or in combination.
  • the computer system 100 is configured to control steering of the front axle 11 and the rear axle 12 by means of the front wheel steering device 24 and the rear wheel steering device 26, respectively.
  • FIG. 1C schematically illustrates more details of an axle of the vehicle 10 in FIG. 1A and/or IB.
  • the axle is the front axle 11.
  • the axle in FIG. 1C may likewise be a rear axle, such as the rear axle 12.
  • the front axle 11 is connected to the wheels 15, 15’, 15”.
  • the front axle 11 comprises a first axle part 11’ connected to the left wheel 15a and a second axle part 11” connected to the right wheel 15”.
  • the vehicle 10 here also comprises a differential lock 18.
  • the powertrain system 14 also comprises the differential lock 18.
  • the differential lock 18 is configured to control distribution of traction from the electric machine 20 to the wheels 15, 15’, 15” by mechanically linking the two drive wheels 15, 15’, 15” to the axle 11, 11’, 11”.
  • each wheel on an axle part can rotate independently, which is beneficial for smooth turns.
  • the vehicle 10, here the axle 11, comprises one or more brakes, which are provided e.g. in the form of one or more service brakes 19, 19’ 19”.
  • the first (left) and second (right) driven wheels 15, 15’, 15” may be arranged to be braked by respective first and second service brakes 19, 19’, 19”.
  • Each one of the service brakes may, e.g., be a pneumatically actuated disc brake or drum brake.
  • the wheel service brakes are controlled by corresponding brake controllers (not illustrated).
  • Each one of the wheel brake controllers is here communicatively coupled to the computer system 100, allowing the computer system 100 to communicate with the brake controllers, and thereby control vehicle braking.
  • the computer system 100 may also be configured to control the transfer of torque from the electric machine 20, i.e. from the powertrain system 14, to the wheels, such as the front wheels 15.
  • the computer system 100 may also be configured to control the transfer of torque from the electric machine 20, i.e. from the powertrain system 14, to plurality of set of wheel, such as the front wheels 15 and the rear wheels 16.
  • the computer system 100 is configured to feed torque transfer command to the electric machine 20 to transfer torque to the wheels via the driven axle(s) of the vehicle 10.
  • the autonomous vehicle 10 of any one of FIGS. 1 A to 1C may be configured to autonomously navigate along a vehicle pathway 220 in the form of a route comprising a set of route segments, as illustrated in e.g. FIGS. 2 and 3.
  • a localization service may be used to locate the autonomous vehicle 10 with respect to the route 220.
  • the autonomous vehicle 10 is here arranged with a set of sensors (not illustrated). Any sensor in the set of sensors may be mounted at any suitable location of the autonomous vehicle 10.
  • the set of sensors may comprise at least one 2D Lidar sensor, at least one 3D Lidar sensor, at least one camera unit, at least one wireless device for network positioning, or any other suitable sensor.
  • the at least one 2D Lidar sensor may be arranged on multiple or all sides of the autonomous vehicle 10, e.g. such that the at least one 2D Lidar sensor is capable of scanning all surroundings of the autonomous vehicle 10.
  • the at least one 3D Lidar sensor may be arranged on the roof of the autonomous vehicle 10 to be able to scan 360 degrees around the autonomous vehicle 10.
  • the at least one wireless device may comprise any suitable wireless device which can communicate with any number of suitable network entities in a wireless network.
  • the network entities may be able to triangulate the position of the wireless device, and thereby also locate the autonomous vehicle 10, and report the location back to the wireless device.
  • Any other suitable methodology for locating the autonomous vehicle 10 with the use of the wireless network may also apply.
  • this may be any suitable telecommunications positioning methodology, e.g. by using ultra-wide band positioning and triangulation.
  • the at least one camera unit may comprise one or more different types of camera units arranged in one or more places of the autonomous vehicle 10.
  • the at least one camera unit may comprise a Red, Green, Blue and Depth (RGBD) sensor camera unit which can record the surroundings and account for depth.
  • RGBD Red, Green, Blue and Depth
  • the at least one camera unit may additionally, or alternatively, comprise any one of one or more infrared cameras, heat cameras, stereo cameras.
  • the set of sensors may comprise any suitable sensor device for communicating with a Global Navigation Satellite System (GNSS) for finding the location of the autonomous vehicle 10 based on communication with satellites.
  • GNSS Global Navigation Satellite System
  • the GNSS may for example be GPS or any other alternatives, e.g. BeiDou, Galileo, GLONASS, or any other suitable satellite positioning system.
  • FIG. 2 there is illustrated a number of vehicles 10 operating within a confined geographical area 200.
  • the confined geographical area 200 corresponds to a quarry area.
  • the confined geographical area 200 can be defined in several different manners, as is commonly known in the art.
  • defining the confined geographical area 200 for autonomous vehicles 10 here involves specifying the boundaries and parameters within which these vehicles are authorized to operate.
  • the definition of the confined geographical area 200 often includes considerations for geographic limits and operational boundaries for the vehicle 10.
  • the confined geographical area for autonomous vehicles is defined by any one of geographic coordinates, which specifies the geographical coordinates (latitude and longitude) that define the boundaries of the area, physical landmarks, which identifies physical landmarks or boundaries that set the edges of the confined area, and digital mapping, which utilizes digital mapping technologies to create a virtual boundary for the confined area.
  • GPS-based mapping systems can e.g. be employed to create a geofence, a virtual perimeter that the autonomous vehicles should not cross.
  • GPS or RFID Radio-Frequency Identification
  • the definition of the confined geographical area 200 may also be based on operational boundaries, which specify operational constraints within the confined area.
  • the operational constraints may include speed limits, specific routes, or areas where certain vehicle behaviors are restricted or encouraged.
  • the definition of the confined geographical area 200 may also be based on environmental conditions (e.g. weather conditions, lighting, or specific road surfaces).
  • the definition of the confined geographical area 200 may also be based on legal and regulatory framework and various safety measures.
  • the confined geographical area 200 may generally include a communication protocols so as to establish communication protocols between the autonomous vehicles and a central control system or infrastructure within the confined area. In this manner the vehicles 10 can be monitored in real-time and further coordinated in relation to each other.
  • the vehicles 10 are controlled in an autonomous manner so as to carry out several different transportation missions within the quarry area.
  • the vehicles 10 are operating along a vehicle pathway 220, as illustrated in FIG. 2.
  • the vehicles 10 may not only transport material from a first starting position (location) 222, such as a loading zone, to a second destination position (location) 224, such as an unloading zone, but also perform one or more quarrying operations, including e.g. removal of material from the earth’s surface.
  • the materials may e.g. be rock, sand, gravel, limestone, or other minerals.
  • the vehicle pathway 220 is here typically defined by the road, including one or more road segments.
  • the vehicle pathway 220 also corresponds to the intended route for the transport (transport mission).
  • the computer system 100 receives transport mission characteristics about the upcoming transport mission, which includes route data about the intended route.
  • the intended route for the vehicle thus refers to the pathway of the vehicle 10 for performing the transport mission.
  • the vehicle pathway sometimes also referred to as the vehicle path, thus refers to the specific trajectory or course that the vehicle 10 is planned to take to perform the transport mission.
  • the vehicle pathway typically encompasses the physical route traveled by a vehicle 10.
  • the route, or intended route typically refers to a predetermined course for the vehicle to operate from one place to another, e.g. from 220 to 224 along the vehicle path 220.
  • the route can include a series of directions or instructions indicating the specific roads or paths to take along the vehicle path to reach a destination.
  • the vehicles 10 may be subject to road conditions resulting in traction loss due to different friction between the wheels 15, 16, 17 of the vehicle 10 and the road. Such road conditions may occur e.g. during rainy periods and/or at colder periods the road surface is covered with snow or ice.
  • hilly terrains within the confined geographical area 200 introduce additional complexities in navigation, requiring the vehicles 10 to adapt to varying inclines and declines while maintaining operational performance.
  • the vehicles 10 may be subjected to unpredictable road conditions and surfaces that can have a detrimental effect on the contact between the tires and the road.
  • Such road conditions and road surface may occasionally result in wheel slip of the vehicle 10, which is even more evident in operating situations in hilly terrain when needed torque is high, such as climbing an uphill road segment.
  • Excessive wheel slip occurs when too much torque is applied to an axle, or a wheel, compared to the road friction. Excessive wheel slip is undesired since it results in an unpredictable vehicle behavior and also in energy inefficient operation.
  • the computer system 100 is configured to control a traction force and brake force distribution between the front axle 11 and the rear axle 12 of the vehicle 10. It should be appreciated that the computer system 100 may likewise be configured to control traction force and brake force distribution between two rear axles, such as rear axles 12, 13, or even between three axles, as such as the front axle 11, and the rear axles 12, 13.
  • the computer system 100 is here an integral part of the vehicle 10. It should be noted that the computer system 100 may be an integral part of the powertrain system 14. In other examples, the computer system 100 and the powertrain system 14 may be separate parts configured to communicate with each other. In addition, or alternatively, the computer system 100 may e.g. be a part of a remote server, such as the central control system, or the like, as illustrated in e.g. FIG. 2 and FIG. 3, while further being configured to be in communication with one or more corresponding sub-computer systems 100’ of the vehicles 10.
  • a remote server such as the central control system, or the like
  • a computer system 100 comprising a central control system and a number of vehicles 10, each one of the vehicles having a sub-computer system, and wherein the central control system is configured to be in communication with the sub-computer systems of the vehicles 10 so as to control traction force and brake force distribution between the front axle 11 and the rear axle 12 of each one of the vehicles 10.
  • the computer system 100 comprises processing circuitry 102.
  • the processing circuitry 102 is configured to control a traction force and brake force distribution between the front axle 11 and the rear axle 12 of the electric vehicle 10.
  • the computer system 100 of FIGS. 1A to 3 may also comprise a memory and a system bus (although not illustrated). These components and further optional technical details of the computer system 100 are described in relation to FIG. 5.
  • the processing circuitry 102 is configured to obtain transport mission characteristics for an upcoming transport mission for the vehicle 10.
  • the transport mission can be varied for different types of vehicle.
  • the transport mission can be to transport materials and/or goods from point 222 (position / location) to point 224 (position / location) along a planned route, here corresponding to the vehicle path 220, see e.g. FIG. 2, i.e. the transport is performed by the vehicle 10 from a geographical starting point (first position) to a geographical destination (second position).
  • the transport may typically be performed along a route, including one or more roads.
  • the vehicle path 220 is here a road.
  • Other examples are also possible, such as transportation of people.
  • the transportation may also include an iterative transportation of materials along a certain route.
  • the processing circuitry 102 is configured to determine transport mission characteristics for an upcoming transport mission for the vehicle 10 based on transport mission data.
  • the transport mission characteristics can be provided in several different manners to the processing circuitry 102.
  • the transport mission characteristics may contain several different types of data.
  • the transport mission characteristics for an upcoming transport mission for the vehicle 10 comprises transport mission data indicative of at least the destination location 224 and a destination time.
  • the destination time refers to a point in time for the vehicle 10 to arrive at the destination point 224.
  • the transport mission data further contains transport mission duration data, distance to be traveled and similar transport mission data.
  • the transport mission data may also contain a speed restriction profile for the transport mission, a minimum speed profile for the transport mission, desired or required speed for different segments of the transport mission (e.g., city driving, highway cruising, acceleration, deceleration).
  • the processing circuitry 102 is configured to determine at least one vehicle pathway characteristic for the upcoming transport mission based on topology data of an intended route (such as the route / vehicle pathway 220) for the transport mission.
  • the vehicle pathway characteristic can be provided in several different manners to the processing circuitry 102.
  • the vehicle pathway characteristic may contain several different types of data.
  • the vehicle pathway characteristic is obtained from data of a topology map over the confined geographical area 200.
  • the topology data / topology map can be obtained from a drone scan 3D map and/or from an ongoing recording by one or more vehicles driving along the vehicle path 220.
  • the processing circuitry 102 is configured to obtain topology data from a number of data sources, such as digital maps, GPS data, or geographic information system (GIS) databases. These sources may generally include relevant information about the road network, including roads, elevation data, inclination data, and potential destinations.
  • the topology data is received by the processing circuitry 102 from a route planner system of the computer system 100 and/or the vehicle 10. In other examples, the topology data is obtained from previous transport missions along the planned route.
  • the vehicle pathway characteristic here comprises data indicative of at least a road inclination.
  • the vehicle pathway characteristic comprises data indicative a road inclination associated with the vehicle pathway 220 and the intended route for the vehicle 10 to complete the transport mission.
  • the topology data of the intended route for the transport mission may comprise relevant data for determining the route profile of the vehicle pathway 220, including elevation changes, inclination and inclination changes, road grade, and terrain type (urban, highway, off-road, etc.).
  • the vehicle pathway characteristic may further include traffic conditions, such as traffic congestion and stop-and-go driving conditions, which affect energy consumption and power demand.
  • traffic conditions such as traffic congestion and stop-and-go driving conditions, which affect energy consumption and power demand.
  • the processing circuitry 102 is configured determine a speed profile for the vehicle 10 for performing the transport mission along the intended route.
  • the intended route is here a planned route based on the transport mission characteristics.
  • the intended route thus corresponds to the vehicle pathway 220.
  • the speed profile for the vehicle 10 for performing the transport mission along the intended route is determined on the basis on the determined transport mission characteristics and the determined at least one vehicle pathway characteristic.
  • the speed profile is a predicted vehicle speed for the vehicle 10 under the transport mission.
  • the predicted vehicle speed is calculated in relation to the time for when the transport mission should be completed.
  • processing circuitry 102 is configured to receive data indicative of a desired vehicle speed for the vehicle 10 under the transport mission.
  • the desired vehicle speed can e.g. be determined on the basis of the desired time for the duration of the transport mission.
  • the desired time is a desired time period for completing the transport mission.
  • the desired time can also be a desired time for when the transport mission should be completed.
  • the desired time period is the period between the start of the transport mission and the completion of the transport mission.
  • the desired vehicle speed is then calculated based on this time period.
  • the processing circuitry 102 is configured to calculate the desired time for when the transport mission should be completed and/or the desired time period for duration of the transport mission. Based on the desired time for when the transport mission should be completed and/or the desired time period for the duration of the transport mission, the processing circuitry 102 subsequently calculates the desired vehicle speed. The desired vehicle speed is then used as the predicted vehicle speed for the transport mission. It should be readily appreciated that the vehicle speed (both predicted and desired) may also be limited by the maximal vehicle speed, which in turn may depend on both the specifications of the vehicle, the topology and the road. Accordingly, determining the desired or required speed for the vehicle 10 to perform the transport mission involves considering various factors that affect the journey, such as time constraints, distance, and road conditions.
  • the processing circuitry 102 is configured to estimate one or more speed profiles for the vehicle 10.
  • the processing circuitry 102 may thus create realistic speed profiles for different segments of the journey, wherein both optimal and suboptimal scenarios are taken into account based on road conditions, traffic, and any speed limits.
  • the predicted vehicle speed (or desired vehicle speed) is received by the processing circuitry 102 directly from the route planner system.
  • the predicted vehicle speed (or desired vehicle speed) is obtained from previous transport missions along the planned route.
  • processing circuitry 102 is configured to predict a risk for wheel slip based on the determined at least one pathway characteristic and the determined speed profile.
  • the risk for wheel slip is predicted by determining a friction force between a road surface and the wheels of the front axle 11 and rear axle 12, respectively.
  • the road surface refers to the road for the vehicle 10 when performing and completing the transport mission along the vehicle pathway 220 (intended route). More specifically, the risk for wheel slip is predicted by determining a friction force between a road surface and the wheels of the front axle 11 and the rear axle 12, respectively, based on the vehicle pathway characteristic and speed profile.
  • the processing circuitry 102 is configured to generate a traction force and braking force distribution profile for the vehicle 10 along the intended route based on the predicted risk for wheel slip.
  • the prediction of risk of wheel slip involves considering various forces acting on the vehicle 10.
  • One force is the tire-road friction, and one example of an equation commonly used for predicting wheel slip is based on the comparison between the maximum longitudinal force and the available friction.
  • the processing circuitry 102 evaluates and predicts the driving conditions so as to determine a traction force value that is below the maximum longitudinal force.
  • the processing circuitry 102 is configured to balance the traction force in relation to available driving conditions, which are determined from the transport mission, the vehicle pathway characteristics and the speed profile.
  • the maximum longitudinal force (Flong max ) that drives the vehicle 10 forward or resists backward motion is related to the tireroad friction by the following equation:
  • Equation 1 where is the maximum longitudinal force [N]; q is the coefficient of friction between the tire and the road; and
  • ⁇ normal is the normal force (the force exerted by the road surface perpendicular to the tire) [N],
  • the wheel may start to slip, and the slip ratio increases.
  • the friction may typically vary along the vehicle pathway and also vary in view of other parameters.
  • the above equation and assumption are simplified representations, and more advanced vehicle dynamics models may generally be used, which involve additional factors such as tire slip angle, tire characteristics, and vehicle dynamics parameters to provide a more accurate prediction of wheel slip.
  • the vehicle weight such as the GCW
  • payload may also be taken into consideration when predicting the risk of wheel slip.
  • a predicted wheel slip may essentially relate to a predicted speed difference between a wheel and the vehicle (zero slip means that the wheel and vehicle are covering ground at the same speed). Accordingly, there are several different ways to predict the risk of wheel slip for the vehicle 10.
  • the risk for wheel slip may be predicted from data indicative of a previous predicted high level of wheel slip. Such data can e.g. be obtained from a vehicle that has operated along the route at a previous occasion.
  • the risk for wheel slip may be predicted by comparing predicted and/or current vehicle speed with predicted/or current wheel rotational speed. The vehicle speed and the wheel rotational speed may be obtained from the vehicle pathway characteristics.
  • the data used by the processing circuity 102 so as to predict the risk for wheel slip is obtained from a map over the vehicle pathway 220 and the confined geographical area 200, which comprises data about potential wheel slip, the vehicle pathway characteristic, such as road conditions and road inclinations for the vehicle path. From this data, a risk of wheel slip can be predicted for the vehicle 10 along the intended route, corresponding to the vehicle pathway 220.
  • This prepared map over the confined geographical area 200 which is indicative of predicted risk of wheel slip along the vehicle pathway 220 (intended route), are then used in combination with the determined speed profile for the vehicle (for performing the transport mission are) for generating the traction force and braking force distribution profile for the vehicle(s) 10.
  • the processing circuitry 102 determines the road inclination of the intended route based on topology date, determines a speed profile for the transmission based on e.g. the distance and the road inclination data, predict the risk of wheel slip based on the speed profile and the road inclination data, and generates the traction force and brake force distribution profile for the vehicle, which contains data indicative of road inclination and changes in road inclination along the intended route.
  • the processing circuitry 102 is configured to obtain a real-time vehicle position.
  • the real-time vehicle position is obtained from a navigation system (not illustrated).
  • the navigation system may be an integral part of the vehicle 10 that is in communication with the processing circuitry 102.
  • the navigation system may be an integral part of the computer system 100 itself, and thus in communication with the processing circuitry 102.
  • the real-time vehicle position may be obtained from a navigation system.
  • the navigation system is here configured to obtain data from various external and internal systems, such as GNSS, GPS, lidar system and the like.
  • the processing circuitry 102 is configured to control the distribution of traction force and braking force between the front axle 11 and rear axle 12 along the intended route 220 based on the generated traction force and braking force distribution profile. More specifically, in response to the obtained real-time vehicle position, the processing circuitry 102 controls the distribution of traction force and braking force between the front axle 11 and the rear axle 12 along the intended route 220 based on the generated traction force and braking force distribution profile.
  • the vehicle can also operate more energy-efficiently. This is particularly relevant in electric vehicles, where optimizing energy usage may generally have a positive impact on the driving range. To this end, predicting risk of wheel slip allows for adjusting braking force and/or traction force distribution in order to maintain the vehicle 10 stable, prevent oversteering or understeering, and reduce road wear.
  • the traction force distribution between the front axle 11 and the rear axle 12 is here controlled by controlling the transfer of traction force to the wheels of the front axle 11 and the rear axle 12.
  • the traction force is provided by the propulsion unit, such as the electric machine 20.
  • the brake force distribution between the front axle 11 and the rear axle 12 is controlled by e.g. operating the service brakes 19, 19’, 19”, as illustrated in e.g. FIG. 1C.
  • each one of the axles, such as the front axle 11 and the rear axle 12 are powered a by a separate electric machine. That is, the vehicle 10 comprises a plurality of electric machines 20.
  • the traction force distribution between the front axle 11 and the rear axle 12 is controlled by controlling the transfer of traction force to the wheels of the front axle 11 and the rear axle 12 by controlling each one of the electric machines.
  • the processing circuitry 102 is further configured to control the distribution of traction force and braking force between front axle 11 and rear axle 12 in response to a determined pathway characteristic in the form of a predicted change in road inclination.
  • the processing circuitry 102 is here configured to generate the traction force and brake force distribution profile based on vehicle pathway characteristics comprising data indicative of predicted change in road inclination associated with the road for the vehicle pathway 220 (intended route).
  • the processing circuitry 102 determines the road inclination of the intended route based on topology date, determines a speed profile for the transmission based on e.g. the distance and the road inclination data, predict the risk of wheel slip based on the speed profile and the road inclination data, generates the traction force and brake force distribution profile for the vehicle, and then controls the distribution of traction force and braking force between the first wheel axle 11 and the second wheel axle 12 based on the generated traction force and brake force distribution profile, in which traction force and brake force is adjusted by the processing circuitry 102 in response to a predicted change in road inclination.
  • the processing circuitry 102 controls the distribution of traction force and braking force between front axle 11 and rear axle 12.
  • the processing circuitry 102 is further configured to control the distribution of traction force and braking force between front axle 11 and rear axle 12 along the pathway (intended route) so as to minimize road wear.
  • the processing circuitry 102 is further configured to control the distribution of traction force and braking force between front axle 11 and rear axle 12 before the occurrence of a wheel slip associated with the predicted risk of wheel slip.
  • the computer system 100 may be configured in a similar vein so as to control a traction force and brake force distribution between another set of axles among the axles of the vehicle 10, e.g. between the rear axles 12, 13.
  • the processing circuitry 102 is further configured to control the differential lock 18 of the vehicle 10 based on the generated traction force and braking force distribution profile.
  • the differential lock 18 is configured to be controlled between an active state, in which the differential lock 18 is turned on, and an inactive state, in which the differential lock 18 is turned off.
  • the processing circuitry 102 may further be configured to determine a steering mode for the vehicle 10 based on the generated traction force and braking force distribution profile.
  • the processing circuitry 102 is configured to determine a steering mode for any one of the front wheel steering device 24 and the rear wheel steering device 26 based on the generated traction force and braking force distribution profile.
  • the processing circuitry 102 is configured to control one or both of steering devices 24, 26 based on the determined steering mode.
  • the processing circuitry 102 is further configured to determine a gross combined weight (GCW) of the vehicle 10. Moreover, the processing circuitry 102 is here configured to generate the traction force and braking force distribution profile for the vehicle 10 along the intended route 220 based on the GCW.
  • GCW gross combined weight
  • the processing circuitry 102 is also configured to determine a distribution of a payload on the vehicle 10. Moreover, the processing circuitry 102 is configured to generate the traction force and braking force distribution profile for the vehicle 10 along the intended route 220 based on the GCW and the distribution of the payload.
  • the GCW of a truck here refers to the total weight of the entire combination of the truck, including possible use and weight of any trailer, including the cargo, passengers, and any other items carried.
  • the GCW is a standard parameter and can be determined in several different ways, e.g. by weighing the truck, trailer and cargo, from a look-up table, from data received from a remote server or the like.
  • the GCW may also be provided by the route planner system of the computer system 100. Hence, the GCW can likewise be determined from an on-board estimation by one or more weighing sensors and data indicative of the different loads on the vehicle 10.
  • the computer system 100 may generally store the GCW in the memory in beforehand or receive data from a user, driver, operator or the like.
  • the processing circuitry 102 may further be configured to obtain transport mission data containing environmental conditions data such as ambient temperature, which affects the efficiency and performance of e.g. the batteries, and humidity and wind conditions, which can influence aerodynamics and energy consumption. Moreover, the processing circuitry 102 may further be configured to generate the traction force and braking force distribution profile for the vehicle 10 along the intended route 220 based on the environmental conditions data.
  • environmental conditions data such as ambient temperature, which affects the efficiency and performance of e.g. the batteries, and humidity and wind conditions, which can influence aerodynamics and energy consumption.
  • the processing circuitry 102 may further be configured to generate the traction force and braking force distribution profile for the vehicle 10 along the intended route 220 based on the environmental conditions data.
  • the processing circuitry 102 may further be configured to obtain transport mission data containing data about available charging infrastructure. Moreover, the processing circuitry 102 may further be configured to generate the traction force and braking force distribution profile for the vehicle 10 along the vehicle pathway (intended route) 220 based on the available charging infrastructure.
  • FIG. 3 illustrates an example of controlling traction force and brake force distribution of a vehicle, such as one of the vehicles of FIGS. 1A - 1C, along a pathway in the confined geographical area of FIG. 2 according to the examples.
  • FIG. 3 schematically illustrates an operating situation of a loaded truck 10 driving uphill and downhill, in which the computer system 100 can be used to control the traction force and brake force distribution between the front axle 11 and the rear axle 12 of the electric vehicle 10.
  • the processing circuitry 102 is configured to generate a traction force and braking force distribution profile for the vehicle 10 along the pathway (intended route) 220 based on the predicted risk for wheel slip, which is determined based on the above-mentioned transport mission characteristics, vehicle pathway characteristic and speed profile of the vehicle 10.
  • the processing circuitry 102 of the computer system 100 obtains a realtime position of the vehicle 10, e.g. at the location 222 (starting position), at a location 226 (uphill road segment), at a location 228 (downhill road segment) and at, or near, the location 224 (destination).
  • the processing circuitry 102 controls the distribution of traction force and braking force between the front axle 11 and the rear axle 12 along the pathway 220 based on the generated traction force and braking force distribution profile.
  • the processing circuitry 102 generates traction force and braking force distribution profile for the vehicle 10 as described in the following brief example of an operation along the vehicle pathway 220.
  • the processing circuitry 102 determines that the distribution between traction force and brake force at location 222 (e.g. starting position) is 50% braking force on the front axle 11 and 50% braking force on the rear axle 12 in combination with 50% traction force on the front axle 11 and 50% traction force on the rear axle 12.
  • the percentage value refers to the distribution of the traction force, provided by the propulsion unit, between the axles and/or the distribution of the brake force from the brake systems, such as the service brakes, between the axles.
  • the processing circuitry 102 determines that the distribution between traction force and brake force at location 226 is 70% braking force on the front axle 11 and 30% braking force on the rear axle 12 in combination with 70% traction force on the front axle 11 and 30% traction force on the rear axle 12.
  • the percentage value refers to the distribution of the traction force, provided by the propulsion unit, between the axles and/or the distribution of the brake force from the brake systems, such as the service brakes, between the axles. In this manner, the vehicle 10 is powered more on the rear axle 12 at the uphill road segment 226.
  • the processing circuitry 102 of the computer system 100 controls the vehicle 10 based on the generated traction force and braking force distribution profile so as to improve the drivetrain system 14 of the vehicle 10, e.g. in order to minimize road wear by distributing the traction force and braking force between the front axle 11 and the rear axle 12.
  • the processing circuitry 102 may optionally also determine to engage the differential locks 18.
  • the processing circuitry 102 may in some situations also determine to include an adjustment of the steering mode, e.g. determine only to steer on the rear axle 12 moving uphill. As mentioned herein, this is obtained by controlling one or more of the front and rear steering devices 24, 26 based on the determined steering mode.
  • the processing circuitry 102 determines that the distribution between traction force and brake force at location 228 is 30% braking force on the front axle 11 and 70% braking force on the rear axle 12 in combination with 30% traction force on the front axle 11 and 70% traction force on the rear axle 12.
  • the percentage value refers to the distribution of the traction force, provided by the propulsion unit, between the axles and/or the distribution of the brake force from the brake systems, such as the service brakes, between the axles. In this manner, the vehicle 10 is powered more on the front axle 11 at the downhill road segment 228.
  • the processing circuitry 102 determines that the distribution between traction force and brake force at location 224 is 100% braking force on the front axle 11 and 0% braking force on the rear axle 12 in combination with 0% traction force on the front axle 11 and 0% traction force on the rear axle 12.
  • the percentage value refers to the distribution of the traction force, provided by the propulsion unit, between the axles and/or the distribution of the brake force from the brake systems, such as the service brakes, between the axles. In this manner, the vehicle 10 is at stand-still at the destination 224.
  • the processing circuitry 102 determines that the distribution between traction force and brake force at the uphill road segment 226 is to be controlled such that the propulsion unit transfers about 5% to 15% more traction force on the rear axle 12 in comparison to the traction force on the front axle 11 when moving uphill.
  • a traction force and braking force distribution profile is also generated based on similar parameters but with the additional feature that also the differential lock 18 of the front axle 11 is controlled by the processing circuitry 102, which here commands the differential lock 18 to automatically engage before entering a difficult hill, such as the uphill road segment 226 of FIG. 3.
  • the exact distribution of traction force and braking force between the front axle 11 and the rear axle 12 may need to be tuned based on type of vehicle etc.
  • the computer system 100 of FIG. 3 is e.g.
  • the remote server is e.g. a centralized controller.
  • the distribution of traction/braking force between the two axles 11, 12 of the vehicle 10 is e.g. based on determined road gradient / road inclination (vehicle pathway characteristics) and predicted risk of wheel slip.
  • the traction force and brake force are distributed between the front axle 11 and the rear axle 12 based on a magnitude of the road inclination.
  • the control of the traction force and brake force distribution based on the magnitude of the road inclination is by way of example derivable from the assumption that the friction for the front axle 11 is essentially equal to the friction for the rear axle 12, such that the maximum traction force can be considered proportional to the longitudinal normal force on the front and rear axles 11, 12, respectively.
  • the processing circuitry 102 may typically also take other factors into account such as acceleration and retardation of the vehicle 10.
  • the distribution of traction/braking force between the two axles 11, 12 of the vehicle 10 is based on determined road gradient / road inclination, predicted risk of wheel slip and payload data.
  • Such example can be implemented by the processing circuitry 102 in combination with onboard sensors, such as an IMU for detecting the road gradient, and a load sensor (not illustrated) configured to detect whether the vehicle 10 is loaded or not.
  • the processing circuitry 102 may be arranged in the central control system (part of the computer system 100) for the vehicles 10 and the confined geographical area 200, wherein the processing circuitry 102 is configured to utilizes site management data, such as gradient information from the predefined vehicle pathway 220 and load data reported from a load weighing system on a loader arranged in the confined geographical area 200.
  • site management data such as gradient information from the predefined vehicle pathway 220 and load data reported from a load weighing system on a loader arranged in the confined geographical area 200.
  • the processing circuitry 102 of the central control system (part of the computer system 100) can also engage the differential lock if deemed necessary due to a determined steepness of the vehicle pathway 220 and/or the predicted risk of the wheel slip along the vehicle pathway 220.
  • the processing circuitry 102 is configured to collect data from the vehicles 10 on the site within the confined geographical area 200 via e.g. a wireless interface.
  • the processing circuitry 102 is also configured to define and generate the transport mission to the vehicles 10, which together with the above determined vehicle pathway characteristics and predicted risk of wheel slip form the basis for the profile for traction force and brake force distribution along the vehicle pathway 220.
  • the parts of the computer system 100 may be comprised in a single vehicle 10, in a plurality of vehicles and/or be comprised in any other suitable location.
  • the processing circuitry 102 of the computer system 100 may be communicatively connected with any one of one or more sensors of the vehicles, sensors within the confined geographical area 200, the GNSS, and the wireless network 40.
  • the processing circuitry 102 may further be able to actuate the navigation of the autonomous vehicles 10, or at least be able to provide commands to the autonomous vehicles 10.
  • the processing circuitry 102 may also be configured to feed additional motion commands to the vehicle 10 for realizing the route associated with the transport mission.
  • FIG. 4 is a flow chart of an exemplary method to control a vehicle 10 according to an example. More specifically, FIG. 4 is an exemplary computer implemented method 300 according to an example. Thus the method 300 is implemented by the computer system 100 and the processing circuitry 102, as described herein. The computer-implemented method 300 is intended for controlling traction force and brake force distribution between a first wheel axle (such as the front axle 11) and a second wheel axle (such as the rear axle 12) of the electric vehicle 10 operating in the confined geographical area 200.
  • a first wheel axle such as the front axle 11
  • a second wheel axle such as the rear axle 12
  • the method comprises a step S10 of obtaining transport mission characteristics for an upcoming transport mission for the vehicle 10.
  • the processing circuitry 102 is configured to implement this step.
  • the method comprises a step S20 of determining at least one vehicle pathway characteristic for the upcoming transport mission based on topology data of the intended route (vehicle pathway 220) for the transport mission.
  • the processing circuitry 102 is configured to implement this step.
  • the method 300 comprises a step S30 of determining a speed profile for the vehicle 10 for performing the transport mission along the intended route (vehicle pathway 220), on the basis on the determined transport mission characteristics and the determined at least one pathway characteristic.
  • the processing circuitry 102 is configured to implement this step. It should be noted that the step may typically include a plurality of different vehicle pathway characteristics, as mentioned herein.
  • the method comprises a step S40 of predicting a risk for wheel slip based on the determined at least one vehicle pathway characteristic and the determined speed profile.
  • the method comprises a step S50 of generating a traction force and braking force distribution profile for the vehicle along the pathway based on the predicted risk for wheel slip.
  • the processing circuitry 102 is configured to implement this step.
  • the method comprises a step S60 of obtaining a real-time vehicle position.
  • the processing circuitry 102 is configured to implement this step.
  • the method 300 further comprises a step S70 of controlling the distribution of traction force and braking force between the front axle (first wheel axle) and the rear axle (second wheel axle) along the pathway 220 based on the generated traction force and braking force distribution profile.
  • the processing circuitry 102 is configured to implement this step.
  • a computer program product comprising program code for performing, when executed by the processing circuitry 102, the method 300 as described above.
  • a non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry 102, cause the processing circuitry 102 to perform the method 300 as described above.
  • FIG. 5 is a schematic diagram of a computer system 1000 for implementing examples disclosed herein.
  • the computer system 1000 is adapted to execute instructions from a computer-readable medium to perform these and/or any of the functions or processing described herein.
  • the computer system 1000 may be connected (e.g., networked) to other machines in a LAN (Local Area Network), LIN (Local Interconnect Network), automotive network communication protocol (e.g., FlexRay), an intranet, an extranet, or the Internet. While only a single device is illustrated, the computer system 1000 may include any collection of devices that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.
  • any reference in the disclosure and/or claims to a computer system, computing system, computer device, computing device, control system, control unit, electronic control unit (ECU), processor device, processing circuitry, etc. includes reference to one or more such devices to individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.
  • control system may include a single control unit or a plurality of control units connected or otherwise communicatively coupled to each other, such that any performed function may be distributed between the control units as desired.
  • such devices may communicate with each other or other devices by various system architectures, such as directly or via a Controller Area Network (CAN) bus, etc.
  • CAN Controller Area Network
  • the computer system 1000 may comprise at least one computing device or electronic device capable of including firmware, hardware, and/or executing software instructions to implement the functionality described herein.
  • the computer system 1000 may include processing circuitry 1002 (e.g., processing circuitry including one or more processor devices or control units), a memory 1004, and a system bus 1006.
  • the computer system 1000 may include at least one computing device having the processing circuitry 1002.
  • the system bus 1006 provides an interface for system components including, but not limited to, the memory 1004 and the processing circuitry 1002.
  • the processing circuitry 1002 may include any number of hardware components for conducting data or signal processing or for executing computer code stored in memory 1004.
  • the processing circuitry 1002 may, for example, include a general-purpose processor, an application specific processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a circuit containing processing components, a group of distributed processing components, a group of distributed computers configured for processing, or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.
  • the processing circuitry 1002 may further include computer executable code that controls operation of the programmable device.
  • the system bus 1006 may be any of several types of bus structures that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and/or a local bus using any of a variety of bus architectures.
  • the memory 1004 may be one or more devices for storing data and/or computer code for completing or facilitating methods described herein.
  • the memory 1004 may include database components, object code components, script components, or other types of information structure for supporting the various activities herein. Any distributed or local memory device may be utilized with the systems and methods of this description.
  • the memory 1004 may be communicably connected to the processing circuitry 1002 (e.g., via a circuit or any other wired, wireless, or network connection) and may include computer code for executing one or more processes described herein.
  • the memory 1004 may include non-volatile memory 1008 (e.g., read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.), and volatile memory 1010 (e.g., random-access memory (RAM)), or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a computer or other machine with processing circuitry 1002.
  • a basic input/output system (BIOS) 1012 may be stored in the non-volatile memory 1008 and can include the basic routines that help to transfer information between elements within the computer system 1000.
  • BIOS basic input/output system
  • the computer system 1000 may further include or be coupled to a non-transitory computer-readable storage medium such as the storage device 1014, which may comprise, for example, an internal or external hard disk drive (HDD) (e.g., enhanced integrated drive electronics (EIDE) or serial advanced technology attachment (SATA)), HDD (e.g., EIDE or SATA) for storage, flash memory, or the like.
  • HDD enhanced integrated drive electronics
  • SATA serial advanced technology attachment
  • the storage device 1014 and other drives associated with computer-readable media and computer-usable media may provide nonvolatile storage of data, data structures, computer-executable instructions, and the like.
  • Computer-code which is hard or soft coded may be provided in the form of one or more modules.
  • the module(s) can be implemented as software and/or hard-coded in circuitry to implement the functionality described herein in whole or in part.
  • the modules may be stored in the storage device 1014 and/or in the volatile memory 1010, which may include an operating system 1016 and/or one or more program modules 1018.
  • All or a portion of the examples disclosed herein may be implemented as a computer program 1020 stored on a transitory or non-transitory computer-usable or computer-readable storage medium (e.g., single medium or multiple media), such as the storage device 1014, which includes complex programming instructions (e.g., complex computer-readable program code) to cause the processing circuitry 1002 to carry out actions described herein.
  • the computer-readable program code of the computer program 1020 can comprise software instructions for implementing the functionality of the examples described herein when executed by the processing circuitry 1002.
  • the storage device 1014 may be a computer program product (e.g., readable storage medium) storing the computer program 1020 thereon, where at least a portion of a computer program 1020 may be loadable (e.g., into a processor) for implementing the functionality of the examples described herein when executed by the processing circuitry 1002.
  • the processing circuitry 1002 may serve as a controller or control system for the computer system 1000 that is to implement the functionality described herein.
  • the computer system 1000 may include an input device interface 1022 configured to receive input and selections to be communicated to the computer system 1000 when executing instructions, such as from a keyboard, mouse, touch-sensitive surface, etc.
  • Such input devices may be connected to the processing circuitry 1002 through the input device interface 1022 coupled to the system bus 1006 but can be connected through other interfaces, such as a parallel port, an Institute of Electrical and Electronic Engineers (IEEE) 1394 serial port, a Universal Serial Bus (USB) port, an IR interface, and the like.
  • the computer system 1000 may include an output device interface 1024 configured to forward output, such as to a display, a video display unit (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)).
  • the computer system 1000 may include a communications interface 1026 suitable for communicating with a network as appropriate or desired.
  • Example 1 A computer system 100 for controlling traction force and brake force distribution between a first wheel axle (such as the front axle 11) and a second wheel axle (such as the rear axle 12) of an electric vehicle 10 operating in a confined geographical area 200, the computer system comprises processing circuitry 102 configured to: obtain transport mission characteristics for an upcoming transport mission for the vehicle; determine at least one vehicle pathway characteristic for the upcoming transport mission based on topology data of an intended route for the transport mission; on the basis on the determined transport mission characteristics and the determined at least one pathway characteristic, determine a speed profile for the vehicle for performing the transport mission along the intended route; predict a risk for wheel slip based on the determined at least one pathway characteristic and the determined speed profile; generate a traction force and braking force distribution profile for the vehicle along the intended route based on the predicted risk for wheel slip; obtain a real-time vehicle position; in response to the obtained real-time vehicle position, control the distribution of traction force and braking force between the first wheel axle and the second wheel axle along the intended route based on the
  • Example 2 The computer system of example 1, wherein the processing circuitry is further configured to control a differential lock of the vehicle based on the generated traction force and braking force distribution profile.
  • Example 3 The computer system of example 1 or example 2, wherein the processing circuitry is further configured to determine a steering mode for the vehicle based on the generated traction force and braking force distribution profile. Moreover, the processing circuitry is configured to control a steering device based on the determined steering mode.
  • Example 4 The computer system of any of the preceding examples, wherein the transport mission characteristics 20 for an upcoming transport mission for the vehicle comprises transport mission data indicative of at least a destination location and a destination time.
  • Example 5 The computer system of any of the preceding examples, wherein the vehicle pathway characteristic is obtained from data of a topology map over the confined geographical area.
  • Example 6 The computer system of any of the preceding examples, wherein the vehicle pathway characteristic comprises data indicative of road inclination.
  • Example 7 The computer system of any of the preceding examples, wherein, based on the pathway characteristic and speed profile, the risk for wheel slip is predicted by determining a friction force between a road surface and the wheels of the first wheel axle and the second wheel axle, respectively.
  • Example 8 The computer system of any of the preceding examples, wherein the real-time vehicle position is obtained from a navigation system.
  • Example 9 The computer system of any of the preceding examples, wherein the processing circuitry is further configured to determine a gross combined weight GCW of the vehicle, and further configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the GCW.
  • Example 10 The computer system of example 9, wherein the processing circuitry is further configured to determine a distribution of a payload on the vehicle, and further configured to generate the traction force and braking force distribution profile for the vehicle along the intended route based on the GCW and distribution of the payload.
  • Example 11 The computer system of any of the preceding examples, wherein the processing circuitry is further configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle along the intended route so as to minimize road wear.
  • Example 12 The computer system of any of the preceding examples, wherein the processing circuitry is further configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle before the occurrence of any wheel slip associated with the predicted risk of wheel slip.
  • Example 13 The computer system of any of the preceding examples, wherein the processing circuitry is further configured to control the distribution of traction force and braking force between the first wheel axle and the second wheel axle in response to a determined pathway characteristic in the form of a predicted change in road inclination.
  • Example 14 A vehicle 1 comprising the computer system of any of examples 1- 13.
  • Example 15 A computer-implemented method 300 for controlling traction force and brake force distribution between a first wheel axle and a second wheel axle of an electric vehicle 10 operating in a confined geographical area 200, the method comprising: obtaining transport mission characteristics for an upcoming transport mission for the vehicle; determining at least one vehicle pathway characteristic for the upcoming transport mission based on topology data of an intended route for the transport mission; on the basis on the determined transport mission characteristics and the determined at least one pathway characteristic, determining a speed profile for the vehicle for performing the transport mission along the intended route; predicting a risk for wheel slip based on the determined at least one pathway characteristic and the determined speed profile; generating a traction force and braking force distribution profile for the vehicle along the intended route based on the predicted risk for wheel slip; obtaining a real-time vehicle position; in response to the obtained real-time vehicle position, controlling the distribution of traction force and braking force between the first wheel axle and the second wheel axle along the intended route based on the generated traction force and braking force distribution profile.
  • Example 16 A computer program product comprising program code for performing, when executed by the processing circuitry of any of examples 1-13, the method of example 15.
  • Example 17 A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry of any of examples 1-13, cause the processing circuitry to perform the method example 15.
  • Relative terms such as “below” or “above” or “upper” or “lower” or “horizontal” or “vertical” may be used herein to describe a relationship of one element to another element as illustrated in the Figures. It will be understood that these terms and those discussed above are intended to encompass different orientations of the device in addition to the orientation depicted in the Figures. It will be understood that when an element is referred to as being “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or intervening elements may be present. In contrast, when an element is referred to as being “directly connected” or “directly coupled” to another element, there are no intervening elements present.

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  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Human Computer Interaction (AREA)
  • Regulating Braking Force (AREA)

Abstract

La présente divulgation concerne un système informatique (100) pour commander une distribution de force de traction et de force de freinage entre un premier essieu de roue (11) et un second essieu de roue (12) d'un véhicule électrique (10) fonctionnant dans une zone géographique confinée (200), le système informatique comprenant un circuit de traitement (102) configuré pour : obtenir des caractéristiques de mission de transport pour une mission de transport à venir pour le véhicule ; déterminer au moins une caractéristique de voie de véhicule pour la mission de transport à venir sur la base de données de topologie d'un itinéraire prévu pour la mission de transport ; sur la base des caractéristiques de mission de transport déterminées et de la ou des caractéristiques de voie déterminées, déterminer un profil de vitesse pour le véhicule pour effectuer la mission de transport le long de l'itinéraire prévu ; prédire un risque de patinage de roue sur la base de la ou des caractéristiques de voie déterminées et du profil de vitesse déterminé ; générer un profil de distribution de force de traction et de force de freinage pour le véhicule le long de l'itinéraire prévu sur la base du risque prédit de patinage de roue ; obtenir une position de véhicule en temps réel ; en réponse à la position de véhicule en temps réel obtenue, commander la distribution de force de traction et de force de freinage entre le premier essieu de roue et le second essieu de roue sur la base du profil de distribution de force de traction et de force de freinage généré.
PCT/EP2023/087537 2023-12-22 2023-12-22 Système et procédé de commande de distribution de traction et de freinage Pending WO2025131299A1 (fr)

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US8676442B2 (en) * 2012-05-18 2014-03-18 International Business Machines Corporation In-vehicle drive pattern optimization for reduced road wear
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WO2022106004A1 (fr) * 2020-11-19 2022-05-27 Volvo Truck Corporation Gestion prédictive d'énergie et de mouvement pour véhicules utilitaires lourds à plusieurs remorques
WO2022106005A1 (fr) * 2020-11-19 2022-05-27 Volvo Truck Corporation Procédés de réduction de dérive à haute vitesse dans des véhicules utilitaires lourds à plusieurs remorques
EP4220328A1 (fr) * 2020-09-25 2023-08-02 Hitachi Construction Machinery Co., Ltd. Machine d'exploitation minière
US20230242121A1 (en) * 2022-01-28 2023-08-03 Volvo Truck Corporation Method for controlling a heavy-duty vehicle

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8676442B2 (en) * 2012-05-18 2014-03-18 International Business Machines Corporation In-vehicle drive pattern optimization for reduced road wear
US20220126801A1 (en) * 2020-01-15 2022-04-28 Volvo Truck Corporation Wheel slip based vehicle motion management for heavy duty vehicles
EP4220328A1 (fr) * 2020-09-25 2023-08-02 Hitachi Construction Machinery Co., Ltd. Machine d'exploitation minière
WO2022106004A1 (fr) * 2020-11-19 2022-05-27 Volvo Truck Corporation Gestion prédictive d'énergie et de mouvement pour véhicules utilitaires lourds à plusieurs remorques
WO2022106005A1 (fr) * 2020-11-19 2022-05-27 Volvo Truck Corporation Procédés de réduction de dérive à haute vitesse dans des véhicules utilitaires lourds à plusieurs remorques
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