WO2025232185A1 - 一种面向执行器失效的转向-差动路径跟踪控制方法 - Google Patents

一种面向执行器失效的转向-差动路径跟踪控制方法

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Publication number
WO2025232185A1
WO2025232185A1 PCT/CN2024/138244 CN2024138244W WO2025232185A1 WO 2025232185 A1 WO2025232185 A1 WO 2025232185A1 CN 2024138244 W CN2024138244 W CN 2024138244W WO 2025232185 A1 WO2025232185 A1 WO 2025232185A1
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Prior art keywords
differential
path tracking
steering
actuator
function
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English (en)
French (fr)
Inventor
张俊智
张峻峰
何承坤
马瑞海
刘伟龙
陈鸣辉
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Tsinghua University
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Tsinghua University
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Classifications

    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • B60W30/045—Improving turning performance
    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18145—Cornering
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/064—Degree of grip
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • 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

Definitions

  • This disclosure relates to the field of intelligent vehicle control technology, and in particular to a steering-differential path tracking control method, device, electronic device and storage medium for actuator failure.
  • designing a path tracking control method that can simultaneously ensure the path tracking accuracy and lateral stability of the vehicle under failure conditions is a problem that urgently needs to be solved.
  • This disclosure aims to at least partially address one of the technical problems in the related art.
  • the first objective of this disclosure is to propose a steering-differential path tracking control method for actuator failure, in order to solve the problems of the limitations of existing technologies, such as the inability to calculate steering-differential coordination and insufficient consideration of tire nonlinearity.
  • the second objective of this disclosure is to provide a device.
  • the third objective of this disclosure is to propose an electronic device.
  • the fourth objective of this disclosure is to provide a computer-readable storage medium.
  • a first aspect of this disclosure proposes a steering-differential path tracking control method for actuator failure, comprising:
  • the remaining execution capacity of the actuator under fault conditions is calculated based on the vehicle speed information and the road adhesion coefficient.
  • the differential steering function is triggered.
  • the path tracking control function, yaw stability function, and total driving torque are calculated. Based on the zero-reset control obstacle function, actuator commands are allocated to obtain vehicle control instructions.
  • the remaining actuator capability under fault conditions calculated based on the vehicle speed information and the road adhesion coefficient further includes:
  • ⁇ is the fault information matrix
  • diag() is a function that generates a matrix based on the diagonal elements.
  • calculating the maximum permissible yaw rate based on the remaining actuator capability under the fault condition includes:
  • the maximum yaw rate under steering execution and the maximum permissible yaw rate under steering-differential conditions are obtained based on the vehicle's dynamics and tire models.
  • the maximum yaw rate is obtained using nonlinear tires and nonlinear solution methods, and its calculation formula is as follows:
  • ⁇ min and ⁇ max are the minimum and maximum values of the front wheel steering angle that can be executed under fault-free conditions, respectively;
  • Tijmin and Tijmax are the maximum braking and maximum driving values that can be executed by the four wheels under fault-free conditions, respectively;
  • Tij is the optimized driving and braking torque of the four wheels;
  • Fz,ij is the vertical load of the four wheels;
  • Rij is the rolling radius of the four wheels;
  • [] T is the transpose of the matrix.
  • the actuator command allocation based on the zero-return control barrier function includes:
  • the step of determining whether the differential participates in path tracking based on the maximum permissible yaw rate, and triggering the differential steering function if the differential participates in path tracking includes:
  • the maximum required yaw rate is calculated. It is then determined whether the differential will participate in path tracking. If the maximum required yaw rate is between the maximum and minimum values of the yaw rate under steering conditions, then path tracking can be completed by steering alone, and the differential will not be triggered.
  • path tracking is completed using steering-differential coordination, triggering differential.
  • ⁇ is the design variable and h(x) is the intermediate calculation function
  • the total driving torque is calculated based on the error between the target vehicle speed and the current longitudinal vehicle speed.
  • the step of obtaining the vehicle control command includes:
  • a steering-differential path tracking control device for actuator failure comprising:
  • the vehicle information acquisition module acquires vehicle dynamics and environmental information, and calculates the current vehicle speed and the current road adhesion coefficient.
  • the execution capability calculation module calculates the remaining execution capability of the actuator under fault conditions based on the vehicle speed information and the road adhesion coefficient.
  • the maximum yaw rate calculation module calculates the maximum permissible yaw rate based on the remaining execution capacity of the actuator under the fault condition
  • the differential judgment module determines whether the differential participates in path tracking based on the maximum permissible yaw rate. If the differential participates in path tracking, the differential steering function is triggered.
  • the control command acquisition module calculates the path tracking control function, yaw stability function, and total driving torque, and allocates actuator commands based on the zero-reset control obstacle function to obtain vehicle control commands.
  • a third aspect of this disclosure provides an electronic device, including: a processor, and a memory communicatively connected to the processor;
  • the memory stores computer-executed instructions
  • the processor executes computer execution instructions stored in the memory to implement the method described in any of the preceding descriptions.
  • a fourth aspect of this disclosure provides a computer-readable storage medium, comprising computer-executable instructions stored therein, which, when executed by a processor, are used to implement the method described in any of the above embodiments.
  • This disclosure provides a steering-differential path tracking control method for actuator failure.
  • it For high-level autonomous vehicles, it combines fault information, environmental information, and vehicle state to determine the maximum execution capability of the vehicle's path tracking process—the maximum yaw rate—and uses this as a safety limit target for path tracking during failure. Simultaneously, it utilizes this safety limit target as a safety and stability criterion for the entire vehicle's path tracking process.
  • a quadratic optimization path tracking control method based on a zero-return control barrier function is employed to ensure that the vehicle's operating state does not exceed the execution capability boundary after failure, while also improving the vehicle's path tracking accuracy, while ensuring the vehicle's safety and stability before and after failure.
  • Figure 1 is a flowchart of a first specific embodiment of a steering-differential path tracking control method for actuator failure provided in this disclosure
  • Figure 2 is a schematic diagram of a steering-differential path tracking control system for actuator failure.
  • Figure 3 is a schematic diagram of the solution results of the maximum yaw rate calculation module based on the degree of fault.
  • Figure 4 is a structural block diagram of a steering-differential path tracking control device for actuator failure provided in an embodiment of this disclosure.
  • the core of this disclosure is to provide a steering-differential path tracking control method, device, electronic device, and storage medium for actuator failure.
  • Figure 1 is a flowchart of a first specific embodiment of a steering-differential path tracking control method for actuator failure provided in this disclosure; the specific operation steps are as follows:
  • Step S101 Obtain vehicle dynamics state and environmental information, and calculate the current vehicle speed and current road adhesion coefficient
  • Step S102 Calculate the remaining actuator capability under fault conditions based on the vehicle speed information and the road adhesion coefficient
  • ⁇ is the fault information matrix
  • diag() is a function that generates a matrix based on the diagonal elements.
  • Step S103 Calculate the maximum permissible yaw rate based on the remaining actuator capability under the fault condition
  • ⁇ Mz is the actual yaw moment generated by the four-wheel differential
  • fl, fr, rl, rr are the left front, right front, left rear and right rear wheels respectively
  • Fx is the longitudinal force of the front and rear axles.
  • the tire model uses the Magic Tire Formula, and its calculation formula is as follows:
  • B, C, D, and E are the fitting parameters of the Magic Tire Formula for tire characteristics, and ⁇ i is the tire sidewall angle.
  • the maximum yaw rate under steering execution and the maximum permissible yaw rate under steering-differential conditions are obtained based on the vehicle's dynamics and tire models.
  • the maximum yaw rate is obtained using nonlinear tires and nonlinear solution methods, and its calculation formula is as follows:
  • ⁇ min and ⁇ max are the minimum and maximum values of the front wheel steering angle that can be executed under fault-free conditions, respectively;
  • Tijmin and Tijmax are the maximum braking and maximum driving values that can be executed by the four wheels under fault-free conditions, respectively;
  • Tij is the optimized driving and braking torque of the four wheels;
  • Fz,ij is the vertical load of the four wheels;
  • Rij is the rolling radius of the four wheels;
  • [] T is the transpose of the matrix.
  • Step S104 Based on the maximum permissible yaw rate, determine whether the differential is involved in path tracking. If the differential is involved in path tracking, trigger the differential steering function.
  • the maximum required yaw rate is calculated. It is then determined whether the differential will participate in path tracking. If the maximum required yaw rate is between the maximum and minimum values of the yaw rate under steering conditions, then path tracking can be completed by steering alone, and the differential will not be triggered.
  • path tracking is completed using steering-differential coordination, triggering differential.
  • ⁇ is the design variable and h(x) is the intermediate calculation function
  • the total driving torque is calculated based on the error between the target vehicle speed and the current longitudinal vehicle speed.
  • Step S105 Calculate the path tracking control function, yaw stability function, and total driving torque; allocate actuator commands based on the zero-reset control obstacle function to obtain vehicle control instructions.
  • the actuator command allocation based on the zero-return control barrier function includes:
  • This embodiment provides a steering-differential path tracking control method for actuator failure.
  • First based on various sensor information provided by autonomous driving, it solves for the stable maximum yaw rate under differential intervention and steering-only conditions after failure, thus addressing the problem of quantifying and determining the remaining path tracking capability after failure. Furthermore, it selects whether to intervene with differential intervention based on the optimization results.
  • through the design of a zero-reset control barrier function and the construction of a secondary optimization solution it unifies the longitudinal and lateral control for coordinated control, satisfying various performance and safety requirements of the failed path tracking process. Therefore, this method ensures safe path tracking for autonomous vehicles after failure, avoiding lateral instability problems that can easily result from failure or differential intervention.
  • this embodiment describes a steering-differential path tracking control system for actuator failure, as shown in Figure 2, as follows:
  • a safe path tracking system for high-level autonomous vehicles in the event of execution failure includes a sensor array supporting autonomous driving, an autonomous driving controller, a maximum yaw rate calculation module based on the degree of failure, a path tracking control module, and an actuator subsystem.
  • the maximum yaw rate calculation module based on the degree of fault receives feedback signals from the actuator subsystem and various sensing information provided by the combination of autonomous driving sensors, including vehicle motion state, vehicle posture, road perception information, etc. It processes the information to obtain actuator fault information, vehicle speed, road adhesion coefficient, and constructs a nonlinear dynamic model of the whole vehicle and a nonlinear tire model. Using a nonlinear optimization method, it generates the maximum permissible yaw rate of steering-differential coordination and the maximum permissible yaw rate of steering in the case of steering only under the current vehicle fault state and road adhesion conditions, and transmits them to the path tracking control module to provide a reference for the safe and stable operation of the vehicle.
  • the maximum yaw rate calculation module based on fault severity includes: a maximum permissible yaw rate nonlinear optimization calculation unit, which calculates the remaining execution capacity of the actuator based on the current fault information and solves for the maximum permissible yaw rate under the current vehicle speed and road adhesion conditions; a fault identification unit, which receives actuator feedback information and various sensor information provided by the combination of autonomous driving sensors to generate vehicle execution fault information; a dynamic state identification unit, which receives wheel speed signals and GPS signals and fuses them to generate the current vehicle speed signal; and an environmental state identification unit, which receives sensor data from the combination of autonomous driving sensors and actuator feedback signals to generate the current road adhesion information.
  • the maximum permissible yaw rate nonlinear optimization calculation unit receives fault information from the fault identification unit, vehicle speed information from the dynamic state identification unit, and road adhesion information from the environmental state identification unit. Based on the vehicle's nonlinear dynamics model and nonlinear tire model, it constructs a nonlinear optimization problem to solve the maximum yaw rate under the remaining actuator execution capability.
  • the solution yields the maximum yaw rate under the steering-only condition and the maximum permissible yaw rate under the steering-differential coordination condition.
  • a fault information-vehicle speed-maximum permissible yaw rate table can be generated offline, and the results can be retrieved by looking up the table to improve the response speed.
  • the path tracking control module receives path planning signals from the autonomous driving controller, sensing signals from the combination of autonomous driving sensors, and maximum yaw rate signals from the maximum yaw rate calculation module. It compares the required yaw rate of the target path at the target vehicle speed with the maximum permissible yaw rate under steering conditions only, selects whether to differentially intervene in path tracking control, and uses a quadratic optimization method based on the zero-return control obstacle function to generate execution commands for the driving mechanism subsystem based on path tracking performance requirements, maximum yaw rate requirements, and drive/braking torque requirements. These commands include front wheel steering angle commands for the steering system, four-wheel braking torque commands for the braking system, and four-wheel drive torque commands for the drive system.
  • the path tracking control module includes: a secondary optimization unit for execution allocation based on a zero-return control obstacle function, which selects whether differential intervention is required for path tracking control and generates execution commands for the actuator subsystem under the premise of meeting path tracking requirements, maximum yaw rate limit requirements, and drive torque command requirements; a path tracking unit, which calculates the path tracking error and the corresponding path tracking control function based on path information and current vehicle position information; a yaw rate limiting unit, which calculates the vehicle stability function based on the allowable maximum yaw rate and the current vehicle path tracking error; and a drive/brake control unit, which calculates the vehicle drive/brake torque command based on the target vehicle speed and the current vehicle speed.
  • a secondary optimization unit for execution allocation based on a zero-return control obstacle function, which selects whether differential intervention is required for path tracking control and generates execution commands for the actuator subsystem under the premise of meeting path tracking requirements, maximum yaw rate limit requirements, and drive torque command requirements
  • the execution allocation secondary optimization unit based on the zero-return control obstacle function selects differential intervention when the required yaw rate is greater than the maximum allowable yaw rate of steering in the case of steering only; otherwise, it completes path tracking by steering only.
  • the execution allocation secondary optimization unit based on the zero-return control obstacle function receives the path tracking control function from the path tracking unit, the yaw stability function from the yaw limiting unit, and the vehicle drive/brake torque command from the drive/brake control unit. Under the premise of satisfying the above constraints, it constructs the execution command of the secondary optimization problem solving execution mechanism subsystem.
  • the actuator subsystem includes: a four-wheel independent braking brake system, a four-wheel independent drive steer system, a steer-by-wire system, and sensor combinations for the corresponding subsystems; and the actuator subsystem execution command generated by the actuator subsystem execution path tracking module.
  • the sensor combination of the corresponding subsystem includes a drive motor current sensor, a brake pressure sensor, a wheel speed sensor, and a front wheel steering angle sensor.
  • the supporting autonomous driving sensor combination includes a camera combination, GPS, IMU, etc., and transmits the measured signals to the maximum yaw rate calculation module and the path tracking control module;
  • the autonomous driving controller generates vehicle speed commands and path planning commands based on perception information.
  • This disclosure provides a steering-differential path tracking control system for actuator failure.
  • it For high-level autonomous vehicles, it combines fault information, environmental information, and vehicle state to determine the maximum execution capability of the vehicle's path tracking process—the maximum yaw rate—and uses this as a safety limit target for path tracking during failure. Simultaneously, the obtained safety limit target is used as a safety and stability criterion for the entire vehicle's path tracking process.
  • a quadratic optimization path tracking control method based on a zero-return control barrier function is employed to ensure that the vehicle's operating state does not exceed the execution capability boundary after failure, while ensuring vehicle safety and stability before and after failure, and improving the vehicle's path tracking accuracy.
  • this embodiment elaborates on the steering-differential path tracking control method for actuator failure, as follows:
  • the system acquires vehicle dynamics and environmental information, processes the feedback sensor information, and calculates the current vehicle speed vx and the current road adhesion coefficient ⁇ .
  • Identify fault information The remaining actuator capability under fault conditions is calculated based on current vehicle operating data and fault information fed back from the actuator subsystem. The following model is then performed based on the fault information:
  • ⁇ is the fault information matrix
  • diag() is a function that generates a matrix based on the diagonal elements.
  • v ⁇ sub> x ⁇ /sub> is the longitudinal velocity of the vehicle.
  • ⁇ is the vehicle's longitudinal acceleration;
  • ⁇ is the vehicle's yaw rate.
  • ⁇ is the yaw acceleration of the vehicle;
  • ⁇ is the sideslip angle of the vehicle.
  • the tires use the Magic Tire Formula:
  • B, C, D, and E are the fitting parameters of the Magic Tire Formula for tire characteristics; ⁇ f and ⁇ r are the tire slip angles of the front and rear axles, respectively.
  • ⁇ min and ⁇ max are the minimum and maximum executable front wheel steering angles under fault-free conditions, respectively;
  • Tijmin and Tijmax are the maximum executable braking and driving torques of the four wheels under fault-free conditions, respectively;
  • Tij is the optimized driving and braking torque of the four wheels;
  • Fz,ij is the vertical load of the four wheels;
  • Rij is...
  • the maximum and minimum yaw rates ⁇ max and ⁇ min under the steering-differential condition can be obtained.
  • Setting ⁇ Mz to zero, the maximum and minimum yaw rates ⁇ ,max and ⁇ ,min under the steering-only condition can be solved.
  • It can generate a table of fault information, vehicle speed, and maximum permissible yaw rate for different combinations of vehicle speed and fault type, and obtain the maximum permissible yaw rate by looking up the table.
  • the maximum required yaw rate ⁇ d is calculated based on the target vehicle speed vd and the maximum curvature ⁇ max of the target path. As shown in Figure 3, when ⁇ d is within the range of the maximum and minimum yaw rates ⁇ ,max and ⁇ ,min under steering-only conditions, path tracking can be completed by steering alone, and the differential function is not triggered; otherwise, steering-differential coordination is required to compensate for the lack of steering capability and complete the path tracking task, thus triggering the differential function.
  • the path tracking model based on two-degree-of-freedom vehicle dynamics adopts:
  • the target yaw acceleration is calculated from the path information.
  • V(x) x T Px
  • P is the definition matrix of the path tracking function, which defines the path tracking error target and needs to be set by the user.
  • B(x) -e ⁇ (- h(x)) + ⁇ + e ⁇ ( ⁇ )
  • h(x) is the intermediate calculation function
  • ⁇ is the design variable
  • the total driving/braking torque is calculated based on the error between the planned target vehicle speed vd and the current longitudinal vehicle speed vx , to obtain the required total driving/braking torque Tacc .
  • the control input of the vehicle execution subsystem that meets the requirements of path tracking accuracy, yaw stability, remaining execution capability, and vehicle speed tracking can be obtained.
  • Corresponding relaxation variables are designed to prioritize the yaw stability and safety of the vehicle.
  • the actuator executes the corresponding control command.
  • T ⁇ sub> ij ⁇ /sub> positive values are executed by the corresponding wheel drive system, while negative values are coordinated and controlled by the corresponding wheel braking and drive system.
  • the front wheel steering angle command ⁇ sub> f ⁇ /sub> is executed by the steering system.
  • this method solves for the stable maximum yaw rate under differential intervention and steering-only conditions after a failure, thus addressing the problem of quantifying and determining the remaining path tracking capability after a failure. Furthermore, it selects whether to intervene with differential intervention based on the optimization results. In addition, by designing a zero-reset control obstacle function and constructing a secondary optimization solution, it unifies longitudinal and lateral control for coordinated control, satisfying various performance and safety requirements of the failed path tracking process. Therefore, this method ensures safe path tracking for autonomous vehicles after a failure, avoiding lateral instability problems that can easily result from failure or differential intervention.
  • Figure 4 is a structural block diagram of a steering-differential path tracking control device for actuator failure provided in an embodiment of this disclosure; the specific device may include:
  • the vehicle information acquisition module 100 acquires vehicle dynamics state and environmental information, and calculates the current vehicle speed and current road adhesion coefficient.
  • the execution capability calculation module 200 calculates the remaining execution capability of the actuator under fault conditions based on the vehicle speed information and the road adhesion coefficient.
  • the maximum yaw rate calculation module 300 calculates the maximum permissible yaw rate based on the remaining execution capacity of the actuator under the fault condition.
  • the differential judgment module 400 determines whether the differential participates in path tracking based on the maximum permissible yaw rate. If the differential participates in path tracking, the differential steering function is triggered.
  • the control command acquisition module 500 calculates the path tracking control function, yaw stability function, and total driving torque, and allocates actuator commands based on the zero-reset control obstacle function to obtain vehicle control commands.
  • This embodiment of a steering-differential path tracking control device for actuator failure is used to implement the aforementioned steering-differential path tracking control method for actuator failure. Therefore, the specific implementation of the steering-differential path tracking control device for actuator failure can be found in the embodiment section of the steering-differential path tracking control method for actuator failure described above.
  • the vehicle information acquisition module 100, the execution capability calculation module 200, the angular velocity calculation module 300, the differential judgment module 400, and the control command acquisition module 500 are respectively used to implement steps S101, S102, S103, S104, and S105 in the aforementioned steering-differential path tracking control method for actuator failure. Therefore, its specific implementation can be referred to the description of the corresponding embodiments, which will not be repeated here.
  • this disclosure also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.
  • this disclosure also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.
  • this disclosure also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.
  • personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection/sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement/user notice and sign an agreement/authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.
  • This disclosure is intended to provide implementation schemes for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and/or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.
  • the terms “one embodiment,” “some embodiments,” “example,” “specific example,” or “some examples,” etc. refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this disclosure.
  • the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.
  • the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
  • those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
  • first and second are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated.
  • a feature defined as “first” or “second” may explicitly or implicitly include at least one of that feature.
  • a plurality of means at least two, such as two, three, etc., unless otherwise explicitly specified.
  • computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM).
  • the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
  • the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module.
  • the integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
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Abstract

涉及智能汽车控制技术领域，尤其涉及一种面向执行器失效的转向-差动路径跟踪控制方法、装置、电子设备及存储介质，其中，方法包括：获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；基于车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；基于故障情况下的执行器剩余执行能力计算最大容许横摆角速度，基于最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。

Description

一种面向执行器失效的转向-差动路径跟踪控制方法
相关申请的交叉引用
本公开基于申请号为202410554168.0、申请日为2024年05月07日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本公开作为参考。
技术领域
本公开涉及智能汽车控制技术领域，尤其涉及一种面向执行器失效的转向-差动路径跟踪控制方法、装置、电子设备及存储介质。
背景技术
随着汽车智能技术的发展，高级别自动驾驶系统对于车辆安全的要求越来越严苛。对于高级别自动驾驶，车辆的驾驶主动权逐步由驾驶员过渡到自动驾驶系统，后者必须拥有能够自主处理故障的能力。因此，面对执行器故障，自动驾驶车辆需要具备在执行器完全或部分失效时，依然能通过剩余执行能力安全、可靠地跟踪预定路径的能力。而转向系统、制动系统、驱动系统作为车辆运动的主要执行系统，其对于整车的安全性和稳定性至关重要，尤其转向失效或者转向能力不足工况下，差动可以作为转向冗余备份补充一定转向能力。但是差动转向容易导致车辆失稳，其介入必须保证车辆的横向稳定性。
现有技术中，对于执行功能丧失的主要应对措施集中在冗余的执行器设计或者故障执行器的隔离。但在执行失效后如何有效的选择目标执行器，如何利用有限的执行能力保证车辆路径跟踪的横向稳定性尚未得到充分解决。
综合所述可知，如何设计一种可以在失效工况下同时保证整车的路径跟踪精度与横向稳定性的路径跟踪控制方法是目前亟需解决的问题。
发明内容
本公开旨在至少在一定程度上解决相关技术中的技术问题之一。
为此，本公开的第一个目的在于提出一种面向执行器失效的转向-差动路径跟踪控制方法，以解决现有技术手段局限性较大，无法针对转向-差动协调情况进行计算，对轮胎非线性区部分考虑不充分等问题。
本公开的第二个目的在于提出一种装置。
本公开的第三个目的在于提出一种电子设备。
本公开的第四个目的在于提出一种计算机可读存储介质。
为达上述目的，本公开第一方面实施例提出了一种面向执行器失效的转向-差动路径跟踪控制方法，包括：
获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；
基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；
基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度；
基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；
计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。
优选地，所述基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力还包括：
基于故障信息进行建模，其计算公式为：
其中，Λ为故障信息矩阵，分别为转向系统和四个车轮驱动系统剩余执行器能力系数，diag()为根据对角元素生成矩阵的函数。
优选地，所述基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度包括：
基于车辆的动力学模型和轮胎模型获取转向执行情况下的最大横摆角速度和转向-差动情况下的最大容许横摆角速度，利用非线性轮胎和非线性求解方式获得最大横摆角速度，其计算公式为：
其中，δmin、δmax分别为无故障情况下前轮转向角可执行的最小值和最大值；Tijmin、Tijmax分别为无故障情况下四个车轮可执行的制动最大值和驱动最大值；Tij为优化的四个车轮的驱制动力矩；Fz,ij为四个车轮的垂向载荷；Rij为四个车轮的滚动半径；[]T为矩阵的转置标志。
优选地，所述基于归零控制障碍函数进行执行器命令分配包括：
对求解满足路径跟踪精度和最大横摆角速度要求的执行器命令进行求解处理，其处理公式为：
其中，π＝(u,δ1,δ2)为优化变量，π*为优化变量的最优值，δ1为第一松弛变量，δ2为第二松弛变量；H为优化目标函数的二次项设计值，为一正定矩阵，F为优化目标函数的一次项设计值，均为优化目标设计参数；c1、c2均为控制器设计参数；C为驱动系数矩阵，C＝[0 1 1 1 1 0 0]；umin、umax分别为控制输入的最大值向量和最小值向量；Lf()、Lg()分别为目标函数对于状态空间方程自治部分与控制输入增益部分的导数。
优选地，所述基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能，包括：
基于目标车速与目标路径的最大曲率，计算得到最大需求横摆角速度，判断差动是否参与路径跟踪，若所述最大需求横摆角速度符合转向工况下横摆角速度的最大值与最小值之间，则仅转向即可完成路径跟踪，差动不触发；
否则，利用转向-差动协同完成路径跟踪，触发差动。
优选地，所述路径跟踪控制函数计算公式为：
V(x)＝xTPx
其中，P为路径跟踪函数的定义矩阵；
所述横摆稳定函数计算公式为：
B(x)＝-e-h(x)+θ+eθ
其中，θ为设计变量，h(x)为中间计算函数；
基于目标车速和当前车辆纵向车速误差，计算得到驱动总力矩。
优选地，所述得到车辆控制指令后包括：
基于所述车辆控制指令，四轮制动力矩中正值由对应车轮驱动系统执行，负值由对应车轮制动和驱动系统协调控制，前轮转向角命令由转向系统执行。
为达上述目的，本公开第二方面实施例提出了一种面向执行器失效的转向-差动路径跟踪控制装置，包括：
车辆信息获取模块，获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；
执行能力计算模块，基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；
最大横摆角速度计算模块，基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度；
差动判断模块，基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；
控制指令获取模块，计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。
为达上述目的，本公开第三方面实施例提出了一种电子设备，包括：处理器，以及与所述处理器通信连接的存储器；
所述存储器存储计算机执行指令；
所述处理器执行所述存储器存储的计算机执行指令，以实现上述任一项所述的方法。
为达上述目的，本公开第四方面实施例提出了一种计算机可读存储介质，包括所述计算机可读存储介质中存储有计算机执行指令，所述计算机执行指令被处理器执行时用于实现上述任一项所述的方法。
本公开提供的一种面向执行器失效的转向-差动路径跟踪控制方法，针对高级别自动驾驶车辆，结合故障信息、环境信息、车辆状态确定车辆路径跟踪过程的最大执行能力——最大横摆角速度，将其作为失效过程中路径跟踪的安全限制目标。同时，利用得到的安全限制目标作为整车路径跟踪过程的安全稳定判据，利用基于归零控制障碍函数的二次优化路径跟踪控制方法，在确保失效前后车辆安全稳定性的前提下确保整车运行状态不超出失效后的执行能力边界，并提升车辆的路径跟踪精度。
本公开附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本公开的实践了解到。
附图说明
本公开上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解，其中：
图1为本公开所提供的一种面向执行器失效的转向-差动路径跟踪控制方法的第一种具体实施例的流程图；
图2为一种面向执行器失效的转向-差动路径跟踪控制系统示意图；
图3为基于故障程度的最大横摆角速度计算模块求解结果示意图；
图4为本公开实施例提供的一种面向执行器失效的转向-差动路径跟踪控制装置的结构框图。
具体实施方式
本公开的核心是提供一种面向执行器失效的转向-差动路径跟踪控制方法、装置、电子设备及存储介质，通过对高级别自动驾驶车辆在执行器失效情况下的最大横摆角速度进行精确计算和控制，在满足自动驾驶车辆的路径跟踪精度前提下提升了车辆安全稳定性，从而推进了车辆冗余安全技术的提升。
为了使本技术领域的人员更好地理解本公开方案，下面结合附图和具体实施方式对本公开作进一步的详细说明。显然，所描述的实施例仅仅是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
请参考图1，图1为本公开所提供的一种面向执行器失效的转向-差动路径跟踪控制方法的第一种具体实施例的流程图；具体操作步骤如下：
步骤S101：获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；
步骤S102：基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；
基于故障信息进行建模，其计算公式为：
其中，Λ为故障信息矩阵，分别为转向系统和四个车轮驱动系统剩余执行器能力系数，diag()为根据对角元素生成矩阵的函数。
步骤S103：基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度；
基于车辆的动力学模型和轮胎模型获取转向执行情况下的最大横摆角速度和转向-差动情况下的最大容许横摆角速度，针对差动车辆动力学进行建模，其计算公式为：
其中，ΔMz为通过四轮差动产生的实际横摆力矩，fl,fr,rl,rr分别为左前、右前、左后和右后车轮，Fx为前后轴的纵向力。
所述轮胎模型采用魔术轮胎公式，其计算公式为：
其中，B,C,D,E均为魔术轮胎公式对于轮胎特性的拟合参数，αi为轮胎偏侧角。
基于车辆的动力学模型和轮胎模型获取转向执行情况下的最大横摆角速度和转向-差动情况下的最大容许横摆角速度，利用非线性轮胎和非线性求解方式获得最大横摆角速度，其计算公式为：
其中，δmin、δmax分别为无故障情况下前轮转向角可执行的最小值和最大值；Tijmin、Tijmax分别为无故障情况下四个车轮可执行的制动最大值和驱动最大值；Tij为优化的四个车轮的驱制动力矩；Fz,ij为四个车轮的垂向载荷；Rij为四个车轮的滚动半径；[]T为矩阵的转置标志。
步骤S104：基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；
基于目标车速与目标路径的最大曲率，计算得到最大需求横摆角速度，判断差动是否参与路径跟踪，若所述最大需求横摆角速度符合转向工况下横摆角速度的最大值与最小值之间，则仅转向即可完成路径跟踪，差动不触发；
否则，利用转向-差动协同完成路径跟踪，触发差动。
所述路径跟踪控制函数计算公式为：
V(x)＝xTPx
其中，P为路径跟踪函数的定义矩阵；
所述横摆稳定函数计算公式为：
B(x)＝-e-h(x)+θ+eθ
其中，θ为设计变量，h(x)为中间计算函数；
基于目标车速和当前车辆纵向车速误差，计算得到驱动总力矩。
步骤S105：计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。
所述基于归零控制障碍函数进行执行器命令分配包括：
对求解满足路径跟踪精度和最大横摆角速度要求的执行器命令进行求解处理，其处理公式为：
其中，π＝(u,δ1,δ2)为优化变量，π*为优化变量的最优值，δ1为第一松弛变量，δ2为第二松弛变量；H为优化目标函数的二次项设计值，为一正定矩阵，F为优化目标函数的一次项设计值，均为优化目标设计参数；c1、c2均为控制器设计参数；C为驱动系数矩阵，C＝[0 1 1 1 1 0 0]；umin、umax分别为控制输入的最大值向量和最小值向量；Lf()、Lg()分别为目标函数对于状态空间方程自治部分与控制输入增益部分的导数。
所述得到车辆控制指令后包括：
基于所述车辆控制指令，四轮制动力矩中正值由对应车轮驱动系统执行，负值由对应车轮制动和驱动系统协调控制，前轮转向角命令由转向系统执行。
本实施例提供一种面向执行器失效的转向-差动路径跟踪控制方法，首先基于自动驾驶赋予的多种传感信息，求解失效后差动介入与仅转向工况下横摆角速度稳定最大值，解决了失效后剩余路径跟踪能力如何确定量化的问题，并且根据优化结果选择差动是否介入；此外，通过归零控制障碍函数的设计和二次优化求解问题的构建，统一的将纵横向控制进行协同控制，满足了失效路径跟踪过程的多种性能指标与安全指标要求。从而，该方法保证了自动驾驶车辆执行失效后安全路径跟踪，避免了失效或者差动介入容易导致的横向失稳问题。
基于上述实施例，本实施例对所述一种面向执行器失效的转向-差动路径跟踪控制系统进行描述，如图2所示，具体如下：
一种针对高级别自动驾驶车辆执行失效的安全路径跟踪系统，包括支撑自动驾驶的传感器组合、自动驾驶控制器、基于故障程度的最大横摆角速度计算模块、路径跟踪控制模块和执行机构子系统；
所述基于故障程度的最大横摆角速度计算模块，接受执行机构子系统的反馈信号和自动驾驶传感器组合提供的多种传感信息，包括车辆运动状态、车身姿态、路面感知信息等，处理得到执行器故障信息、车速、道路附着系数，构建整车非线性动力学模型与非线性轮胎模型，采用非线性优化方法，生成当前车辆故障状态和道路附着情况下，车辆能够稳定运行的转向-差动协调最大容许横摆角速度和仅转向情况下的转向最大容许横摆角速度，并传递给路径跟踪控制模块，为车辆的安全稳定运行提供参考；
所述基于故障程度的最大横摆角速度计算模块，包括：最大容许横摆角速度非线性优化计算单元，通过针对当前的故障信息计算执行器剩余执行能力，求解当前车速与道路附着情况下的最大容许横摆角速度；故障识别单元，接受执行器反馈信息与自动驾驶传感器组合提供的多种传感信息，生成车辆执行故障信息；动力学状态识别单元，接受轮速信号与GPS信号，融合生成当前车速信号；环境状态识别单元，接受自动驾驶传感器组合的传感数据与执行机构反馈信号，生成当前道路的附着信息；
所述最大容许横摆角速度非线性优化计算单元，通过接受故障识别单元的故障信息、动力学状态识别单元的车速信息、环境状态识别单元的道路附着信息，基于车辆的非线性动力学模型、非线性轮胎模型构建求解剩余执行器执行能力下最大横摆角速度的非线性优化问题，求解得到仅转向情况下的最大横摆角速度和转向-差动协调情况下的最大容许横摆角速度，可选的，可以离线生成故障信息-车速-最大容许横摆角速度表格，通过查表查询结果，以提升响应速度；
所述路径跟踪控制模块，接受自动驾驶控制器的路径规划信号、支撑自动驾驶传感器组合的传感信号和最大横摆角速度计算模块的最大横摆角速度信号，对比目标路径在目标车速下的需求横摆角速度与仅转向情况下的转向最大容许横摆角速度，选择是否差动介入路径跟踪控制，并采用基于归零控制障碍函数的二次优化方法，基于路径跟踪性能要求、最大横摆角速度要求、驱动/制动转矩需求生成行机构子系统的执行命令，包括转向系统的前轮转角命令、制动系统的四轮制动转矩命令和驱动系统的四轮驱动转矩命令；
所述路径跟踪控制模块，包括：基于归零控制障碍函数的执行分配二次优化单元，选择差动是否介入路径跟踪控制，并在满足路径跟踪需求、最大横摆角速度限制需求和驱动转矩命令需求前提下，生成执行机构子系统的执行命令；路径跟踪单元，根据路径信息和当前车辆位置信息计算路径跟踪误差并计算对应路径跟踪控制函数；横摆限制单元，根据容许最大横摆角速度和当前车辆路径跟踪误差计算整车稳定函数；驱动/制动控制单元，根据目标车速与当前车速计算整车驱动/制动转矩命令；
所述基于归零控制障碍函数的执行分配二次优化单元，当需求横摆角速度大于仅转向情况下的转向最大容许横摆角速度，选择差动介入，否则，仅转向完成路径跟踪；
所述基于归零控制障碍函数的执行分配二次优化单元，在接受路径跟踪单元的路径跟踪控制函数、横摆限制单元的横摆稳定函数、驱动/制动控制单元的整车驱动/制动转矩命令，在满足上述约束前提下，构建二次优化问题求解执行机构子系统的执行命令；
所述执行机构子系统，包括：四轮独立制动的线控制动系统、四轮独立驱动的线控驱动系统、线控转向系统及对应子系统的传感器组合，执行机构子系统执行路径跟踪模块生成的执行机构子系统执行命令；
所述对应子系统的传感器组合包括驱动电机电流传感器、制动压力传感器、轮速传感器、前轮转向角传感器；
所述支撑自动驾驶传感器组合，包括摄像头组合、GPS、IMU等，并将测得信号传递给最大横摆角速度计算模块和路径跟踪控制模块；
所述自动驾驶控制器根据感知信息生成车速命令与路径规划命令。
本公开实施例提供的一种面向执行器失效的转向-差动路径跟踪控制系统，针对高级别自动驾驶车辆，结合故障信息、环境信息、车辆状态确定车辆路径跟踪过程的最大执行能力——最大横摆角速度，将其作为失效过程中路径跟踪的安全限制目标。同时，利用得到的安全限制目标作为整车路径跟踪过程的安全稳定判据，利用基于归零控制障碍函数的二次优化路径跟踪控制方法，在确保失效前后车辆安全稳定性的前提下确保整车运行状态不超出失效后的执行能力边界，并提升车辆的路径跟踪精度。
基于上述实施例，本实施例对面向执行器失效的转向-差动路径跟踪控制方法进行详细阐述，具体如下：
获取车辆动力学状态与环境信息，通过针对反馈的传感信息进行处理，计算得到当前车辆车速vx与当前道路附着系数μ。
识别故障信息。通过当前车辆运行数据与执行器子系统反馈的故障信息计算得到故障情况下的执行器剩余执行能力，针对故障信息，进行如下建模：
其中，Λ为故障信息矩阵，分别为转向系统和四个车轮驱动系统剩余执行器能力系数，代表剩余执行能力与无故障情况下的执行能力比值，diag()为根据对角元素生成矩阵的函数。
计算最大容许横摆角速度。基于车辆的动力学模型、轮胎模型构建求解剩余执行器执行能力下最大横摆角速度的非线性优化问题，求解得到转向执行情况下的最大横摆角速度和转向-差动情况下的最大容许横摆角速度；
针对考虑差动的车辆动力学进行建模：
其中，vx为车辆纵向速度，为车辆纵向加速度；γ为车辆的横摆角速度，为车辆的横摆角加速度；β为车辆侧偏角，为车辆侧偏角加速度；Iz为车辆的z轴转动惯量，m为整车质量；δf为前轮转向角，Fy,i(i＝f,r，分别代表前后轴)为前后轴的侧向力，Fx,i为前后轴的纵向力，Fx,ij为四轮驱动/制动力命令(ij＝fl,fr,rl,rr，分别代表左前，右前，左后，右后车轮)；a和b分别为车辆前轴到质心距离和后轴到质心距离；w为车辆轮距；ΔMz为通过四轮差动产生的实际横摆力矩。
轮胎采用魔术轮胎公式：
式中，B,C,D,E均为魔术轮胎公式对于轮胎特性的拟合参数；αf、αr分别为前后轴的轮胎侧偏角。
构建如下优化问题：
其中，δmin、δmax分别为无故障情况下前轮转向角可执行的最小值和最大值；Tijmin、Tijmax分别为无故障情况下四个车轮可执行的制动最大值和驱动最大值；Tij为优化的四个车轮的驱制动力矩；Fz,ij为四个车轮的垂向载荷；Rij为
四个车轮的滚动半径；[]T为矩阵的转置标志。
通过求解上述的优化问题，可以得到转向-差动工况下横摆角速度的最大值γmax和最小值γmin。将ΔMz置为零，可求解得到仅转向工况下横摆角速度的最大值γδ,max和最小值γδ,min。
可以针对不同车速与不同故障类型组合生成故障信息-车速-最大容许横摆角速度表格，通过查表操作获得最大容许横摆角速度。
判断差动是否参与路径跟踪。根据目标车速vd与目标路径的最大曲率ρmax计算得到最大的需求横摆角速度γd。如图3所示，当γd处于仅转向工况下横摆角速度的最大值γδ,max和最小值γδ,min范围内，仅转向即可完成路径跟踪任务，差动功能不触发；否则，需要转向-差动协同才可弥补转向能力缺失，完成路径跟踪任务，因此触发差动功能。
计算路径跟踪控制函数、横摆稳定函数和驱动/制动总力矩。
基于二自由度车辆动力学的路径跟踪模型采用：

式中，为路径跟踪过程状态变量向量，eY、为车辆路径跟踪误差与车辆路径跟踪误差变化率，eφ、为车辆导航角跟踪误差与车辆导航角跟踪误差变化率；u＝[δf Tfl Tfr Trl Trr]T为路径跟踪过程中的控制输入向量；A为路径跟踪模型状态转移矩阵，w为路径跟踪模型扰动矩阵；B为路径跟踪模型输入矩阵，当差动介入时，B＝B1，当仅转向时，B＝B2；Cf和Cr分别为车辆前轴与后轴的轮胎侧偏刚度；为由路径信息计算得到的目标横摆角加速度。
路径跟踪控制函数V(x)计算为：
V(x)＝xTPx
式中，P为路径跟踪函数的定义矩阵，定义路径跟踪误差目标，需要自行设定。
横摆稳定的归零控制障碍函数B(x)计算为：

B(x)＝-e-h(x)+θ+eθ
式中，h(x)为中间计算函数，θ为设计变量。
通过上述设计，只需设计控制输入，使得V(x)→0即可保证路径跟踪精度，使得B(x)≥0即可满足车辆横摆角速度γ满足稳定性要求。
驱动/制动总力矩根据规划的目标车速vd与当前车辆纵向车速vx误差，计算得到需求的总驱动/制动力矩Tacc。
基于归零控制障碍函数进行执行器命令优化分配。为了求解满足路径跟踪精度和最大横摆角速度要求的执行器命令，可以通过求解以下二次优化问题：
式中，π＝(u,δ1,δ2)为优化变量，π*为优化变量的最优值，δ1为第一松弛变量，δ2为第二松弛变量；H为优化目标函数的二次项设计值，为正定矩阵，F为优化目标函数的一次项设计值，均为优化目标设计参数；c1、c2均为控制器设计参数；C为驱动系数矩阵，C＝[0 1 1 1 1 0 0]；umin、umax分别为控制输入的最大值向量和最小值向量；Lf()、Lg()分别为目标函数对于状态空间方程自治部分与控制输入增益部分的导数。
通过求解上述优化问题，即可得到满足路径跟踪精度、横摆稳定要求、剩余执行能力、车速跟踪的整车执行子系统的控制输入，且设计了对应松弛变量，优先保证整车横摆稳定安全性。
执行器执行对应控制命令，四轮驱动/制动力矩Tij中正值由对应车轮驱动系统执行，负值由对应车轮制动和驱动系统协调控制，前轮转向角命令δf由转向系统执行。
首先基于自动驾驶赋予的多种传感信息，求解失效后差动介入与仅转向工况下横摆角速度稳定最大值，解决了失效后剩余路径跟踪能力如何确定量化的问题，并且根据优化结果选择差动是否介入；此外，通过归零控制障碍函数的设计和二次优化求解问题的构建，统一的将纵横向控制进行协同控制，满足了失效路径跟踪过程的多种性能指标与安全指标要求。从而，该方法保证了自动驾驶车辆执行失效后安全路径跟踪，避免了失效或者差动介入容易导致的横向失稳问题。
请参考图4，图4为本公开实施例提供的一种面向执行器失效的转向-差动路径跟踪控制装置的结构框图；具体装置可以包括：
车辆信息获取模块100，获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；
执行能力计算模块200，基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；
最大横摆角速度计算模块300，基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度；
差动判断模块400，基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；
控制指令获取模块500，计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。
本实施例的一种面向执行器失效的转向-差动路径跟踪控制装置用于实现前述的一种面向执行器失效的转向-差动路径跟踪控制方法，因此一种面向执行器失效的转向-差动路径跟踪控制装置中的具体实施方式可见前文中的一种面向执行器失效的转向-差动路径跟踪控制方法的实施例部分，例如，车辆信息获取模块100，执行能力计算模块200，角速度计算模块300，差动判断模块400，控制指令获取模块500，分别用于实现上述一种面向执行器失效的转向-差动路径跟踪控制方法中步骤S101，S102，S103，S104，S105，所以，其具体实施方式可以参照相应的各个部分实施例的描述，在此不再赘述。
为了实现上述实施例，本公开还提出一种电子设备，包括：处理器，以及与所述处理器通信连接的存储器；所述存储器存储计算机执行指令；所述处理器执行所述存储器存储的计算机执行指令，以实现执行前述实施例所提供的方法。
为了实现上述实施例，本公开还提出一种计算机可读存储介质，计算机可读存储介质中存储有计算机执行指令，所述计算机执行指令被处理器执行时用于实现前述实施例所提供的方法。
为了实现上述实施例，本公开还提出一种计算机程序产品，包括计算机程序，该计算机程序被处理器执行时实现前述实施例所提供的方法。
本公开中所涉及的用户个人信息的收集、存储、使用、加工、传输、提供和公开等处理，均符合相关法律法规的规定，且不违背公序良俗。
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本公开预期可提供用户选择性阻止使用或访问个人信息数据的实施方案。即本公开预期可提供硬件和/或软件，以防止或阻止对此类个人信息数据的访问。一旦不再需要个人信息数据，通过限制数据收集和删除数据可最小化风险。此外，在适用时，对此类个人信息去除个人标识，以保护用户的隐私。
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此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本公开的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现定制逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本公开的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本公开的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本公开的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。如，如果用硬件来实现和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本公开各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (10)

  1. 一种面向执行器失效的转向-差动路径跟踪控制方法，包括：
    获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；
    基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；
    基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度；
    基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；
    计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。
  2. 根据权利要求1所述的面向执行器失效的转向-差动路径跟踪控制方法，其中，所述基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力还包括：
    基于故障信息进行建模，其计算公式为：
    其中，Λ为故障信息矩阵，分别为转向系统和四个车轮驱动系统剩余执行器能力系数，diag()为根据对角元素生成矩阵的函数。
  3. 根据权利要求1所述的面向执行器失效的转向-差动路径跟踪控制方法，其中，所述基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度包括：
    基于车辆的动力学模型和轮胎模型获取转向执行情况下的最大横摆角速度和转向-差动情况下的最大容许横摆角速度，利用非线性轮胎和非线性求解方式获得最大横摆角速度，其计算公式为：
    Λ[δmin,Tijmin]T≤[δf,Tij]T≤Λ[δmax,Tijmax]T,
    其中，δmin、δmax分别为无故障情况下前轮转向角可执行的最小值和最大值；Tijmin、Tijmax分别为无故障情况下四个车轮可执行的制动最大值和驱动最大值；Tij为优化的四个车轮的驱制动力矩；Fz,ij为四个车轮的垂向载荷；Rij为四个车轮的滚动半径；[]T为矩阵的转置标志。
  4. 根据权利要求3所述的面向执行器失效的转向-差动路径跟踪控制方法，其中，所述基于归零控制障碍函数进行执行器命令分配包括：
    对求解满足路径跟踪精度和最大横摆角速度要求的执行器命令进行求解处理，其处理公式为：

    s.t.LfV(x)+LgV(x)u+c1V(x)-δ1≤0,
    LfB(x)+LgB(x)u+c2h(x)≥0,
    Cπ-δ2＝Tacc,
    Λumin≤u≤Λumax.
    其中，π＝(u,δ1,δ2)为优化变量，π*为优化变量的最优值，δ1为第一松弛变量，δ2为第二松弛变量；H为优化目标函数的二次项设计值，为一正定矩阵，F为优化目标函数的一次项设计值，均为优化目标设计参数；c1、c2均为控制器设计参数；C为驱动系数矩阵，C＝[0 1 1 1 1 0 0]；umin、umax分别为控制输入的最大值向量和最小值向量；Lf()、Lg()分别为目标函数对于状态空间方程自治部分与控制输入增益部分的导数。
  5. 根据权利要求1-4中任一项所述的面向执行器失效的转向-差动路径跟踪控制方法，其中，所述基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能，包括：
    基于目标车速与目标路径的最大曲率，计算得到最大需求横摆角速度，判断差动是否参与路径跟踪，若所述最大需求横摆角速度符合转向工况下横摆角速度的最大值与最小值之间，则仅转向即可完成路径跟踪，差动不触发；
    否则，利用转向-差动协同完成路径跟踪，触发差动。
  6. 根据权利要求1-5中任一项所述的面向执行器失效的转向-差动路径跟踪控制方法，其中，所述路径跟踪控制函数计算公式为：
    V(x)＝xTPx
    其中，P为路径跟踪函数的定义矩阵；
    所述横摆稳定函数计算公式为：
    其中，为设计变量，h(x)为中间计算函数；
    基于目标车速和当前车辆纵向车速误差，计算得到驱动总力矩。
  7. 根据权利要求1-6中任一项所述的面向执行器失效的转向-差动路径跟踪控制方法，其特征在于，所述得到车辆控制指令后包括：
    基于所述车辆控制指令，四轮制动力矩中正值由对应车轮驱动系统执行，负值由对应车轮制动和驱动系统协调控制，前轮转向角命令由转向系统执行。
  8. 一种面向执行器失效的转向-差动路径跟踪控制装置，包括：
    车辆信息获取模块，获取车辆动力学状态与环境信息，计算得当前车辆车速信息及当前道路附着系数；
    执行能力计算模块，基于所述车速信息及所述道路附着系数计算得故障情况下的执行器剩余执行能力；
    最大横摆角速度计算模块，基于所述故障情况下的执行器剩余执行能力计算最大容许横摆角速度；
    差动判断模块，基于所述最大容许横摆角速度，判断差动是否参与路径跟踪，若差动参与路径跟踪，则触发差动转向功能；
    控制指令获取模块，计算路径跟踪控制函数、横摆稳定函数和驱动总力矩，基于归零控制障碍函数进行执行器命令分配，得到车辆控制指令。
  9. 一种电子设备，包括：处理器，以及与所述处理器通信连接的存储器；
    所述存储器存储计算机执行指令；
    所述处理器执行所述存储器存储的计算机执行指令，以实现如权利要求1-7中任一项所述的方法。
  10. 一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机执行指令，所述计算机执行指令被处理器执行时用于实现如权利要求1-7中任一项所述的方法。
PCT/CN2024/138244 2024-05-07 2024-12-10 一种面向执行器失效的转向-差动路径跟踪控制方法 Pending WO2025232185A1 (zh)

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