Distributed driving chassis control method based on HIL

Abstract

The invention belongs to the technical field of chassis driving control, and discloses a distributed driving chassis control method based on HIL, and the method comprises the steps: obtaining a pedal input signal and a steering wheel angle signal, carrying out the mapping and smoothing processing, inputting a driving force and yaw moment fusion distribution model, and obtaining a driving force and yaw moment fusion distribution model; the target torque of each wheel is obtained and issued to a real vehicle chassis test board, and a vehicle-mounted motor is controlled to output corresponding actual torque and actual vehicle speed; calculating a target angular velocity needing to be tracked by each wheel load motor through a vehicle dynamics and kinematics model; according to the difference value between the actual angular speed of the vehicle-mounted motor and the target angular speed of the load motor, a torque instruction of the vehicle-mounted motor is dynamically adjusted; and external resistance loss and internal torque loss are calculated through the vehicle speed and angular speed synthesis module and the vehicle environment model and are fed back to the vehicle dynamics model. Software and hardware closed-loop coupling and torque and driving control closed-loop verification are achieved, and the simulation precision of an HIL simulation system is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of chassis driving control technology, and in particular to a distributed drive chassis control method based on HIL. Background Technology

[0002] With the rapid development of new energy vehicle technology, higher requirements have been placed on the testing and verification of key components such as the vehicle's electric drive system, vehicle controller, and battery management system. The HIL simulation system (Hardware-in-Loop Simulation) has emerged to address this need. It integrates a hardware platform, simulation model, and software platform. By connecting real hardware such as motors and motor controllers into a virtual vehicle environment constructed from a high-precision model, the controller sends vehicle control commands to the actuators on the vehicle. The vehicle then performs corresponding actions based on these commands, and sensors on the vehicle monitor vehicle status information and feed it back to the controller. The vehicle's distributed drive system consists of multiple motors, steering mechanisms, braking systems, and control systems. The drive motors are placed directly near the wheels or integrated into the wheel hubs to achieve independent control of wheel torque.

[0003] However, changes in driving conditions, operating modes, and structural parameters of distributed drive vehicles can significantly impact vehicle dynamics. The lack of coordinated control among coupled subsystems within the vehicle chassis inevitably leads to deterioration in overall vehicle performance under certain complex driving conditions. In existing HIL simulation systems for distributed drive systems, the mapping between vehicle driving input and chassis control is not smooth; there are discrepancies between the software algorithm's control allocation of driving torque and yaw moment and the actual response of the vehicle chassis; and existing vehicle speed control models do not consider real-world loading characteristics, resulting in insufficient simulation accuracy during the testing phase. Summary of the Invention

[0004] The purpose of this invention is to address the technical problem of insufficient simulation accuracy of existing distributed drive systems in HIL simulation systems, and to provide a method for smooth mapping and coordinated control to match real hardware, and to achieve closed-loop coupling between software and hardware in a virtual environment. Its core lies in the joint feedback control of the torque and speed of the four wheels, and the construction of a closed-loop verification system between the driver, the vehicle and the environment.

[0005] In a first aspect, embodiments of the present invention provide an adaptive distributed drive chassis driving control method, the method comprising: The pedal input signal and steering wheel angle signal are acquired, and after mapping and filtering smoothing, the smooth driving torque and smooth yaw torque of the whole vehicle are obtained. Based on the fusion distribution model of driving force and yaw moment, the smooth driving moment and smooth yaw moment are distributed to the four wheels to obtain the target torque of each wheel. The target torque of each wheel is sent to the actual vehicle chassis test bench via the HIL real-time communication bus. After receiving the target torque, the actual vehicle chassis test bench controls each on-board motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. At the same time, the actual vehicle chassis test bench transmits the actual torque and actual vehicle speed back to the HIL simulation controller in real time via the HIL real-time communication bus. Based on the actual torque of each wheel, the target angular velocity corresponding to each wheel that the four load motors need to track is generated by calculating through vehicle dynamics and kinematics models. The target angular velocity of each load motor is then sent to the actual vehicle chassis test bench through the HIL real-time communication bus, and each load motor is controlled to track its corresponding target angular velocity. Based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, the torque command of the on-board motor corresponding to that wheel is dynamically adjusted to achieve linkage balance between the on-board motors and the load motors on the four wheels. The actual vehicle speed of each on-board motor is input into the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle; and input into the vehicle environment model to calculate the external resistance loss and internal torque loss, and feed the external resistance loss and internal torque loss back to the vehicle dynamics model to form a system-level closed-loop control.

[0006] Optionally, based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, the torque command of the on-board motor corresponding to that wheel is dynamically adjusted, including: For each wheel, the gain coefficient is adaptively adjusted based on the difference between the actual angular velocity of the on-board motor corresponding to the wheel and the target angular velocity of the load motor corresponding to the wheel. Based on the gain coefficient, the difference, and the target torque of the wheel, the adjusted torque command of the wheel is calculated. Specifically, when the actual angular velocity is less than the target angular velocity, the gain coefficient is increased to increase the torque command; When the actual angular velocity is greater than the target angular velocity, the gain coefficient is reduced to decrease the torque command; When the actual angular velocity equals the target angular velocity, maintain the current torque command.

[0007] Optionally, the pedal input signal and steering wheel angle signal are acquired, and after mapping and filtering smoothing, the smooth driving torque and smooth yaw torque of the whole vehicle are obtained, including: Based on the curve mapping relationship table between driving torque and pedal opening, and the curve mapping relationship table between yaw moment and steering wheel angle, the pedal input signal and steering wheel angle signal are mapped to the initial driving torque requirement and the initial yaw moment requirement respectively by curve lookup and interpolation. The initial driving torque requirement and the initial yaw torque requirement are smoothed by passing them through a first-order low-pass filter to obtain the smoothed driving torque and smoothed yaw torque.

[0008] Optionally, based on the fusion distribution model of driving force and yaw moment, the smooth driving torque and smooth yaw moment are distributed to the four wheels to obtain the target torque of each wheel, which is achieved through the following constraints: The sum of the longitudinal forces of the four wheels is equal to the smooth driving torque; The sum of the longitudinal forces of the right front wheel and the left rear wheel minus the sum of the longitudinal forces of the left front wheel and the right rear wheel is proportional to the smooth yaw moment, and the proportionality coefficient is the reciprocal of the vehicle's left and right track width. After distributing the longitudinal forces to each wheel under the above constraints, the longitudinal forces are divided by the wheel radius to obtain the target torque of the corresponding wheel.

[0009] Optionally, the vehicle dynamics and kinematics model includes a vehicle dynamics model and a vehicle kinematics model; the step of calculating and generating the target angular velocities corresponding to each wheel that the four load motors need to track based on the actual torque of each wheel through the vehicle dynamics and kinematics model includes: Based on the actual torque of each wheel, the actual vehicle driving torque and the actual vehicle yaw torque are synthesized. The actual vehicle driving torque and actual vehicle yaw torque are input into the vehicle dynamics model; so that the vehicle dynamics model calculates the vehicle's longitudinal acceleration and yaw acceleration based on the vehicle's mass and moment of inertia parameters, and in combination with the external drag loss and internal torque loss fed back by the vehicle environment model. Integrate the calculated longitudinal acceleration and yaw acceleration to obtain the vehicle's longitudinal velocity and yaw rate; The longitudinal velocity and yaw rate are input into the vehicle kinematics model so that the vehicle kinematics model combines the longitudinal velocity and yaw rate into the target linear velocity of the four wheels according to the vehicle's left and right wheel track, and converts the target linear velocity of the four wheels into the target angular velocity of the corresponding load motor.

[0010] Optionally, the actual vehicle speed of each on-board motor is input into the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the entire vehicle, including: Convert the actual vehicle speed of each on-board motor into the actual angular velocity of the corresponding wheel; The actual angular velocities of each wheel are input into the vehicle speed and angular velocity synthesis module, so that the vehicle speed and angular velocity synthesis module can synthesize the actual longitudinal speed and actual yaw rate of the whole vehicle based on the actual angular velocities of each wheel, the wheel radius and the left and right wheel distance of the vehicle. Wherein, the actual longitudinal speed of the whole vehicle is the average of the linear speeds corresponding to the actual angular velocities of the four wheels; The actual yaw rate of the vehicle is proportional to the difference between the actual angular velocities of the left and right front wheels, and the proportionality coefficient is the ratio of the wheel radius to the wheel track.

[0011] Optionally, the vehicle environment model determines the external drag loss and internal torque loss, including: Calculate the air resistance based on the actual longitudinal speed of the vehicle, the preset air resistance coefficient, the vehicle's frontal area, and the air density; Calculate the slope resistance and rolling resistance based on the actual longitudinal speed of the vehicle, the corresponding road slope angle, the vehicle mass, and the gravitational acceleration. The external resistance loss is obtained by summing the air resistance, slope resistance, and rolling resistance: The internal torque loss is calculated based on the vehicle's required torque and the preset transmission system efficiency, wherein the vehicle's required torque is the sum of the target torques of each wheel.

[0012] In a second aspect, embodiments of the present invention provide an adaptive distributed drive chassis driving control device, comprising: The signal input and preprocessing module is used to acquire pedal input signals and steering wheel angle signals, and after mapping and filtering smoothing, obtain the smooth driving torque and smooth yaw torque of the whole vehicle. The torque distribution module is used to distribute the smooth driving torque and smooth yaw torque to the four wheels based on the driving force and yaw torque fusion distribution model, so as to obtain the target torque of each wheel. The vehicle motor control module is used to send the target torque of each wheel to the actual vehicle chassis test bench via the HIL real-time communication bus. After receiving the target torque, the actual vehicle chassis test bench controls each vehicle motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. At the same time, the actual vehicle chassis test bench transmits the actual torque and actual vehicle speed back to the HIL simulation controller in real time via the HIL real-time communication bus. The load motor control module is used to calculate the target angular velocity corresponding to each wheel that the four load motors need to track based on the actual torque of each wheel through vehicle dynamics and kinematics models, and to send the target angular velocity of each load motor to the actual vehicle chassis test bench through the HIL real-time communication bus, so as to control each load motor to track its corresponding target angular velocity. The on-board motor feedback module is used to dynamically adjust the torque command of the on-board motor corresponding to each wheel based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, so as to achieve linkage balance between the on-board motor and the load motor on the four wheels. The load motor feedback module is used to input the actual vehicle speed of each on-board motor into the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle; and input the vehicle environment model to calculate the external resistance loss and internal torque loss, and feed the external resistance loss and internal torque loss back to the vehicle dynamics model to form a system-level closed-loop control.

[0013] Optionally, the chassis driving control device includes an on-board controller, a host computer controller, a real vehicle chassis test bench, and a distributed drive actuator; The actual vehicle chassis test bench includes a mechanical frame, an on-board motor and an on-board motor control unit, a load motor and a load motor control unit; The distributed drive actuator includes at least two independently driven hub motors and their control units, an on-board encoder, a load encoder, and a torque sensor, and is mechanically mounted on the actual vehicle chassis test bench to simulate real wheels; The host computer controller runs the HIL simulation model, and the vehicle controller sends control commands to the actual vehicle chassis test bench through the HIL real-time communication interface unit at a fixed simulation step size; and receives the real-time running data returned by the actual vehicle chassis test bench at the same step size. The HIL real-time communication interface unit is connected to the host computer controller and the distributed drive actuator, respectively.

[0014] Thirdly, embodiments of the present invention provide an electronic device, including: a processor, a memory, a communication interface, and a communication bus. The processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction that causes the processor to perform operations as described in the first aspect of the chassis control method.

[0015] The technical solution provided in this invention involves acquiring pedal input signals and steering wheel angle signals, and then performing mapping and filtering smoothing processes to obtain the smooth driving torque and smooth yaw torque of the entire vehicle. Based on a fusion distribution model of driving force and yaw torque, the smooth driving torque and smooth yaw torque are distributed to the four wheels to obtain the target torque for each wheel. The target torque of each wheel is then sent to a real vehicle chassis test bench, so that after receiving the target torque, the test bench controls each on-board motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. Based on the actual torque of each wheel, the target angular velocity corresponding to each wheel is generated by calculating using a vehicle dynamics and kinematics model, and each load motor is controlled to track its corresponding target angular velocity.

[0016] Next, the torque command of the on-board motor corresponding to each wheel is dynamically adjusted so that the actual angular velocity of the on-board motor of each wheel approaches the target angular velocity of the load motor. By dynamically correcting the deviation of the torque command, the actual driving speed of the vehicle is ensured to closely follow the target driving curve in real time. When high-risk and complex working conditions occur in the real vehicle test, the chassis hardware is dynamically matched and responded. The on-board motor and the load motor jointly generate the actual angular velocity on the mechanical shaft system to achieve system-level closed-loop control. The external resistance loss and internal torque loss calculated by the vehicle environment model are fed back to the vehicle dynamics model to reproduce the real scenario. By dynamically loading road resistance, vehicle inertia and coupled dynamics that conform to physical laws, controllable delays, noise and faults are introduced and fed back to the driving control to build a closed-loop verification system between the driver, vehicle and environment. This allows the software control strategy to obtain the real vehicle response and make further adjustments during the test. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a distributed drive chassis control method based on HIL according to the present invention.

[0018] Figure 2 This is a signal route diagram for torque control of the vehicle's motor.

[0019] Figure 3 This is a diagram showing the relationship between speed control and torque control principles.

[0020] Figure 4 This is a schematic diagram of the signal preprocessing and torque distribution process.

[0021] Figure 5 This is a flowchart of the algorithm for vehicle dynamics and motion model.

[0022] Figure 6 Signal route diagram for speed control load motor.

[0023] Figure 7 This is a schematic diagram of a distributed drive chassis control device based on HIL according to the present invention. Detailed Implementation

[0024] The present invention will be described in detail below through embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0025] In this invention, the terms "in one possible embodiment," "exemplary," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "in one possible embodiment," "exemplary," or "for example" in this invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "in one possible embodiment," "exemplary," or "for example" is intended to present the relevant concepts in a specific manner.

[0026] Distributed drive technology equips each wheel with an independent hub motor, independently controlling the longitudinal force and yaw moment of the four wheels. It deeply integrates the engine and steering wheel. The torque command of any wheel will simultaneously affect the longitudinal acceleration and yaw motion of the vehicle, making it impossible for the control algorithm to reproduce the real coupling effect in the actual vehicle system in the simulation environment, resulting in insufficient simulation accuracy.

[0027] In the distributed drive system testing of existing HIL simulation systems, the distributed drive chassis domain controller under test is typically simulated using high-fidelity models of the four wheel hub motors and load motors it controls. While the signals in the HIL system are regular, the torque vector algorithm that runs perfectly in testing and verification may exhibit unacceptable jitter in yaw torque in a real vehicle environment due to electromagnetic interference, bus load fluctuations, and other noise. This could be caused by a single frame delay on the bus.

[0028] While the distributed drive chassis exhibits strong internal control coupling, it lacks coordination between torque and driving control responses, making it difficult to quickly verify the effectiveness of the overall vehicle control strategy. For example, in a real vehicle environment, the process of a driver pressing the accelerator pedal to control the vehicle involves "pedal sensor, controller algorithm, motor inverter switching, electromagnetic field establishment, rotor torque output, tire slippage, and vehicle acceleration." However, the HIL simulation system can only simulate the algorithm and signal control of the distributed drive chassis, failing to verify potential issues in the actual vehicle environment such as motor torque response lag and power electronic switch delays. Furthermore, it cannot achieve system-level collaborative simulation and control optimization.

[0029] Therefore, how to design a chassis driving control method that can realize closed-loop coupling of software and hardware, torque coordination and driving control closed-loop verification in the HIL simulation system is a technical problem that urgently needs to be solved in this field.

[0030] This invention relates to the field of chassis driving control technology, and more specifically, to a technology for distributed drive torque coordination and software algorithm coupling with a real controller in a HIL simulation system. The aim is to solve the technical problems of unsmooth mapping of driving control to vehicle chassis control and deviation between the control allocation results of the software algorithm and the real vehicle chassis response in existing HIL simulation systems.

[0031] Firstly, embodiments of the present invention provide a distributed drive chassis control method based on HIL (Hardware-Integrated Circuit). For example... Figure 1 As shown, the specific steps include: S110 acquires the pedal input signal and steering wheel angle signal, and after mapping and filtering smoothing, obtains the smooth driving torque and smooth yaw torque of the whole vehicle.

[0032] Specifically, the pedal input signal and steering wheel angle signal are sampled at a fixed sampling frequency and stored as input signals according to the time sequence. The host computer controller receives the input signal from the analog-to-digital converter interface, and performs lookup table and interpolation processing based on the mapping relationship between driving force and pedal opening curve, and the mapping relationship between yaw moment and steering wheel angle curve, further mapping the input signal into the original driving force requirement and yaw moment requirement. At the same time, a first-order low-pass filter is used to smooth the original driving force requirement and yaw moment requirement, filtering out high-frequency signals such as noise and abnormal changes, to obtain smooth driving torque and smooth yaw moment.

[0033] S120, based on the fusion distribution model of driving force and yaw moment, distributes smooth driving torque and smooth yaw moment to the four wheels to obtain the target torque of each wheel.

[0034] The smoothed driving torque and smoothed yaw torque from step S110 are input into the driving force and yaw torque fusion allocation model located in the HIL simulation system. This driving force and yaw torque fusion allocation model performs the following operations: First, the total driving torque is decomposed into basic longitudinal force components for the four wheels. Second, to achieve the target yaw moment, based on the vehicle's left and right track widths, the incremental longitudinal force to be applied to the right front wheel and left rear wheel, and the equivalent reduction in longitudinal force to be applied to the left front wheel and right rear wheel are calculated. Finally, the basic longitudinal force components of each wheel are algebraically added to their corresponding incremental or reduction longitudinal force to obtain the final longitudinal force for each wheel. This final force is then divided by the wheel radius to output the target torque for each wheel.

[0035] S130: The target torque of each wheel is sent to the actual vehicle chassis test bench via the HIL real-time communication bus. After receiving the target torque, the actual vehicle chassis test bench controls each on-board motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. At the same time, the actual vehicle chassis test bench transmits the actual torque and actual vehicle speed back to the HIL simulation controller in real time via the HIL real-time communication bus.

[0036] The host computer controller encodes the target torque of each wheel calculated in step S120 into a torque control command that can be transmitted via the CAN bus and sends it to the vehicle controller. The motor control unit in the vehicle controller receives and parses the torque control command, drives the corresponding vehicle motor on the actual vehicle chassis test bench to output the actual torque, thereby driving the wheels to rotate and generating actual wheel speed. The actual wheel speed of each wheel is measured by the vehicle encoder installed on the test bench, and the actual angular velocity of each vehicle motor is calculated based on the actual rotational speed of each wheel.

[0037] like Figure 2 As shown, the actual vehicle chassis hardware receives and executes the on-board motor torque control signal on the ring test bench. This on-board motor torque control signal carries a torque command (including the target torque for the left front wheel). Target torque for the right front wheel Target torque for the left rear wheel Target torque for the right rear wheel Each of these drives its corresponding on-board motor to generate actual torque. During the output process, torque sensors are used to monitor the actual torque of each wheel. .

[0038] Meanwhile, the actual rotational speed of each wheel's onboard motor is monitored by the onboard encoder. The actual angular velocity of the corresponding on-board motor was calculated. The formula is as follows:

[0039] in, For the wheel radius, It can be the actual speed of the onboard motors of each wheel. (Including the actual speed of the left front wheel motor, the actual speed of the right front wheel motor, the actual speed of the left rear wheel motor, and the actual speed of the right rear wheel motor); then, based on The actual angular velocity of the on-board motors of each wheel was calculated. The formula is as follows:

[0040] in, It can be the actual angular velocity of the on-board motors of each wheel. (Including the actual angular velocity of the left front wheel, the actual angular velocity of the right front wheel, the actual angular velocity of the left rear wheel, and the actual angular velocity of the right rear wheel).

[0041] Finally, the monitored actual torque and the calculated actual angular velocity are fed back to the host computer and HIL simulation system via the on-board controller to form a torque control closed loop.

[0042] S140, based on the actual torque of each wheel, calculates the target angular velocity corresponding to each wheel that the four load motors need to track through the vehicle dynamics and kinematics model, and sends the target angular velocity of each load motor to the actual vehicle chassis test bench through the HIL real-time communication bus, and controls each load motor to track its corresponding target angular velocity.

[0043] In the HIL system, the actual torque of each wheel obtained in step S130 is input into the driving force and yaw moment fusion distribution model for fusion, and the actual vehicle driving torque and actual vehicle yaw moment are calculated.

[0044] The vehicle's longitudinal velocity and yaw rate are calculated using a vehicle dynamics model. Based on the vehicle's kinematics model, these velocities are combined to form the target linear velocities of the four wheel load motors, which are then further converted into corresponding target angular velocities. The host computer controller maps the target linear velocities of each wheel into speed control commands, which are transmitted via the CAN bus to the load motor control unit in the on-board controller. This drives the distributed actuators to generate the actual linear velocities of each wheel load motor on the actual vehicle chassis test bench, thereby controlling each load motor on the test bench to track its corresponding target angular velocity.

[0045] S150 dynamically adjusts the torque command of the on-board motor corresponding to each wheel based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, thereby achieving linkage balance between the on-board motors and the load motors on all four wheels.

[0046] By adaptively adjusting the gain coefficient and combining the difference between the actual angular velocity of the on-board motor and the target angular velocity of the load motor, the torque correction amount of the on-board controller is calculated. This correction is then added to the torque command to generate an updated torque command. The online updated torque command is fed back to the on-board motor driver and used to drive the on-board motor of that wheel. Through this closed-loop adjustment, the actual angular velocity of the on-board motor of each wheel approaches the target angular velocity of its load motor, thereby achieving linkage balance and coordinated tracking between the on-board motor and the load motor on all four wheels.

[0047] S160 inputs the actual vehicle speed of each on-board motor to the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle; and inputs the vehicle environment model to calculate the drag loss and internal torque loss, and feeds the external drag loss and internal torque loss back to the vehicle dynamics model to form a system-level closed-loop control.

[0048] The actual angular velocities of each on-board motor returned in step S130 are input to the vehicle speed and angular velocity synthesis module. This module combines the actual angular velocities of the four wheels to calculate the actual longitudinal velocity and yaw rate of the vehicle as a whole, representing the overall motion of the vehicle.

[0049] The actual longitudinal velocity and yaw rate of the vehicle are input into the vehicle environment model. This vehicle environment model simulates the external driving resistance (including air resistance, gradient resistance, and rolling resistance) and the torque loss of the internal transmission system experienced by the vehicle under the current motion state, and calculates the corresponding resistance loss value and internal torque loss value.

[0050] The calculated external drag loss and internal torque loss are fed back to the vehicle dynamics model in the HIL simulation system. These loss values ​​serve as input for the next simulation cycle, correcting the vehicle's force balance and thus forming a system-level closed-loop control from the real physical response to the virtual simulation model.

[0051] The technical solution provided in this invention involves acquiring pedal input signals and steering wheel angle signals, and then performing mapping and filtering smoothing processes to obtain the smooth driving torque and smooth yaw torque of the entire vehicle. Based on a fusion distribution model of driving force and yaw torque, the smooth driving torque and smooth yaw torque are distributed to the four wheels to obtain the target torque for each wheel. The target torque of each wheel is then sent to a real vehicle chassis test bench, so that after receiving the target torque, the test bench controls each on-board motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. Based on the actual torque of each wheel, the target angular velocity corresponding to each wheel is generated by calculating using a vehicle dynamics and kinematics model, and each load motor is controlled to track its corresponding target angular velocity.

[0052] Next, the torque command of the on-board motor corresponding to each wheel is dynamically adjusted so that the actual angular velocity of the on-board motor of each wheel approaches the target angular velocity of the load motor. By dynamically correcting the deviation of the torque command, the actual driving speed of the vehicle is ensured to closely follow the target driving curve in real time. When high-risk and complex working conditions occur in the real vehicle test, the chassis hardware is dynamically matched and responded. The on-board motor and the load motor jointly generate the actual angular velocity on the mechanical shaft system to achieve system-level closed-loop control. The external resistance loss and internal torque loss calculated by the vehicle environment model are fed back to the vehicle dynamics model to reproduce the real scenario. By dynamically loading road resistance, vehicle inertia and coupled dynamics that conform to physical laws, controllable delays, noise and faults are introduced and fed back to the driving control to build a closed-loop verification system between the driver, vehicle and environment. This allows the software control strategy to obtain the real vehicle response and make further adjustments during the test.

[0053] Based on the above embodiments, as one implementation of the present invention, the torque command of the on-board motor corresponding to each wheel is dynamically adjusted according to the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel.

[0054] To ensure the plan is clearly described, the following will combine... Figure 3 The technical solutions of the embodiments of the present invention will be described. Figure 3 A diagram illustrating the relationship between speed control and torque control principles provided in an embodiment of the present invention is shown. Figure 3 As shown, the specific process and module correspondence are as follows: Step a1: When the on-board motor executes the torque command, it generates the actual torque. and actual angular velocity The actual torque Feedback is fed back into the dynamic model, incorporating the actual angular velocity. Send to the feedback calculation module.

[0055] Step a2: In the HIL simulation system, the target angular velocity of the load motor calculated by the dynamic model is... The expected torque command of the on-board motor obtained from the model calculation The formula is as follows: (Sent to the feedback calculation module)

[0056] in, The gain coefficient is adjusted adaptively. The magnitude of the value, combined with the difference and the onboard motor torque command, is used to calculate the adjusted torque command for each wheel. .

[0057] Step a3: Adjust the torque command for each wheel The signal is sent to the vehicle motor, which then performs further torque control.

[0058] The specific torque control method is as follows: 1. When the actual angular velocity Less than the target angular velocity At that time, increase the gain coefficient The value of this value increases the torque command, causing the on-board motor to perform acceleration, thus balancing the on-board motor and the load motor. 2. When the actual angular velocity greater than the target angular velocity When, reduce the gain coefficient The value of this value reduces the torque command, causing the on-board motor to perform a deceleration operation, which helps the on-board motor and the load motor to reach a balance. 3. When the actual angular velocity Equal to target angular velocity This indicates that the on-board motor and the load motor are currently in a balanced state, maintaining the current torque command.

[0059] This implementation feeds back the target angular velocity of the load motor to the HIL system, dynamically correcting torque command deviations and ensuring that the vehicle speed closely follows the target driving curve in real time, resulting in the following two significant benefits: Firstly, the difference between the target angular velocity of the load motor and the actual angular velocity of the on-board motor characterizes the instantaneous deviation between the driving torque and load torque of a single wheel, and the macroscopic deviation between the actual driving state of the vehicle and the target driving curve. This implementation dynamically adjusts the torque command of the on-board motor to eliminate microscopic wheel speed deviations in real time, thereby ensuring a high degree of consistency between the vehicle's actual speed and dynamic operating conditions. At the HIL system level, the vehicle controller verifies the speed-following performance of the vehicle under real dynamic loads.

[0060] Secondly, when simulating extreme conditions such as low-traction road surfaces, single-wheel slippage, and motor torque response delay, the load motor will instantly apply drastically changing loads, resulting in a significant difference in angular velocity between the on-board motor and the load motor. This implementation method can quickly adjust the torque command to counteract these sudden changes. When wheel slippage occurs, the torque command value is rapidly reduced to prevent abnormal component overheating; when the coefficient of friction returns to normal, the torque command value is rapidly increased to ensure power response.

[0061] exist Figure 4 Based on the illustrated embodiment, as an implementation method of this invention, the pedal input signal and steering wheel angle signal are acquired, and after mapping filtering and smoothing processing, the smooth driving torque and smooth yaw torque of the entire vehicle are obtained. The specific process is as follows: Step b1: Receive and process driver input signals.

[0062] The driver input module is pre-set with a fixed sampling frequency. It collects the driver's raw operation signals in real time through sensors and stores them as an array in time sequence. Figure 4 The pedal opening signal Acc / Brk shown is related to the steering wheel angle δ.

[0063] Step b2: Map the original input signal to the basic torque requirement at the vehicle level.

[0064] The pedal opening signal Acc / Brk is input to the driver's drive module. After performing lookup table and interpolation processing based on the mapping relationship between drive force and pedal opening curve, the original drive force requirement is projected. ;like Figure 4 As shown, Eco represents energy-saving mode, Normal represents normal mode, and Sport represents sport mode. The specific mapping requirements are as follows: 1. When the vehicle is in Eco mode, the original driving force requirement is obtained by looking up a table based on the mapping curve between driving force and pedal opening labeled Eco, and then performing interpolation. ; 2. When the vehicle is in normal mode, the driving force and pedal opening mapping curve marked "Normal" is looked up in a table and interpolated to project the original driving force requirement. ; 3. When the vehicle is in Sport mode, the driving force and pedal opening mapping curve marked "Sport" is looked up in a table and interpolated to project the original driving force requirement. .

[0065] The steering wheel angle δ is input to the driver's steering module. After table lookup and interpolation processing based on the mapping relationship between yaw moment and steering wheel angle curve, the required yaw moment is projected. ;like Figure 4 As shown, H-spd represents high speed, M-spd represents medium speed, and L-spd represents low speed. The specific mapping requirements are as follows: 1. When the vehicle is at high speed, the required yaw moment is obtained by looking up a table based on the mapping curve between the yaw moment and steering wheel angle marked H-spd, and then performing interpolation. ; 2. When the vehicle is at medium speed, the required yaw moment is obtained by looking up a table based on the mapping curve between yaw moment and steering wheel angle marked M-spd, and then performing interpolation. ; 3. When the vehicle is at low speed, the required yaw moment is obtained by looking up a table based on the mapping curve between the yaw moment and steering wheel angle marked L-spd, and then performing interpolation. .

[0066] Step b3: Smoothing and filtering.

[0067] Figure 4 The driving force smoothing filtering module is a first-order low-pass filter, which filters out the original driving force requirements. High-frequency noise in the signal is used to obtain a smoothed driving torque. ; Figure 4 The yaw moment smoothing filtering module is a first-order low-pass filter, which filters out the required yaw moment. High-frequency noise in the image is used to obtain a smoothed yaw moment after smoothing. .

[0068] This implementation can filter high-frequency noise caused by mechanical clearance of the pedal / steering wheel, road bumps, etc., so that a predictable mapping relationship can be established between steering wheel operation and vehicle response. It ensures that the rate of change of torque command sent to the motor controller is always within the range allowed by hardware safety, and can avoid mechanical shock to the vehicle transmission system in case of sudden start and stop.

[0069] exist Figure 4 Based on the illustrated embodiment, as an implementation of the present invention, the smooth driving torque and smooth yaw torque are distributed to the four wheels based on the driving force and yaw torque fusion distribution model to obtain the target torque of each wheel.

[0070] Specifically, based on the driving force and yaw moment fusion distribution model designed in the HIL simulation system, the calculation formula is as follows:

[0071] in, The longitudinal force is on the left front wheel. The longitudinal force is on the right front wheel. The longitudinal force is on the left rear wheel. The longitudinal force on the right rear wheel; characterizing the smooth driving torque. It is the vector sum of the longitudinal forces of the four wheels.

[0072]

[0073] in, The left and right track widths of the vehicle are given; next, the longitudinal forces of the four tires are obtained: , , ,

[0074] The final target torque for all four tires is obtained: =

[0075] in, For the wheel radius, The longitudinal force of all four tires (including the longitudinal force of the left front tire) Longitudinal force of the right front wheel Longitudinal force of the left rear wheel Longitudinal force of the right rear wheel ), Target torque for all four tires (including target torque for the left front tire) Target torque for the right front wheel Target torque for the left rear wheel Target torque for the right rear wheel ).

[0076] The operation performed by the fusion distribution model of driving force and yaw moment is described as follows: First, the total driving torque is decomposed into the basic longitudinal force components of the four wheels; Secondly, in order to achieve the target yaw moment, based on the vehicle's left and right track widths, the increase in longitudinal force to be applied to the right front wheel and the left rear wheel, as well as the equal decrease in longitudinal force to be applied to the left front wheel and the right rear wheel, are calculated. Finally, the basic longitudinal force component of each wheel is algebraically added to the corresponding longitudinal force increment or longitudinal force decrement to obtain the final longitudinal force of each wheel. This final longitudinal force is then divided by the wheel radius to output the target torque of each wheel.

[0077] This implementation method can directly and quantitatively verify whether the software algorithm of the host computer controller conforms to physical laws. It enables the HIL simulation system to calculate the target torque of the four wheels under current operating conditions in a dynamic testing environment, verifying the vehicle's power performance at the torque numerical level and providing precise wheel steering assistance. Simultaneously, based on the dynamic balance equations, an optimized distribution algorithm is constructed. When on low-traction surfaces or during aggressive starts, it can intelligently distribute the total driving force to the wheels with the highest vertical load and highest coefficient of friction to maintain vehicle stability.

[0078] exist Figure 5 Based on the illustrated embodiment, as one implementation of this invention, the target angular velocities corresponding to each wheel that the four load motors need to track are generated through vehicle dynamics and kinematics models, based on the actual torque of each wheel. The specific process and the relationship between the corresponding modules are as follows: Step c1: Calculate the actual torque of each on-board motor. In the input driving force and yaw moment fusion distribution model, the actual vehicle driving torque is obtained through fusion. Compared with the actual yaw moment of the whole vehicle .

[0079] Step c2: Convert the actual vehicle driving torque Compared with the actual yaw moment of the whole vehicle The longitudinal acceleration and yaw rate are calculated by inputting the data into the vehicle dynamics model. The specific calculation formulas are as follows:

[0080] in This refers to the total weight of the vehicle. For longitudinal acceleration, For external resistance loss, Let Z be the moment of inertia along the Z-axis. This is the yaw acceleration. This represents the internal torque loss. The vehicle dynamics model, based on vehicle mass and moment of inertia parameters, and incorporating external drag loss and internal torque loss obtained from feedback from the vehicle environment model, calculates the vehicle's longitudinal acceleration and yaw rate.

[0081] Next, the calculated longitudinal acceleration Perform integration to obtain the vehicle's overall longitudinal velocity. ; for yaw acceleration Perform integration to obtain the yaw rate of the entire vehicle. .

[0082] Step c3: Calculate the longitudinal speed of the entire vehicle. and the yaw rate of the whole vehicle Input into the vehicle kinematics model, based on the vehicle's left and right wheelbases With yaw rate The target linear velocity of the four wheel-loaded motors is calculated using the following formula:

[0083] in, The target linear velocity of the left front wheel. The target linear velocity of the right front wheel. The target linear velocity of the left rear wheel. The target linear velocity of the right rear wheel.

[0084] Simultaneously, the target linear velocity is converted into the target angular velocity corresponding to the load motor of each wheel. .

[0085] Next, as Figure 6As shown, the target linear speed of the four wheel load motors is encoded into load motor speed control signals that can be transmitted via the CAN bus and transmitted to the vehicle controller. The load motor control unit in the vehicle controller receives and parses the load motor control signals and drives the four wheels on the actual vehicle chassis hardware test bench to output speed.

[0086] The actual wheel speed of each wheel is measured by a load encoder installed on the test bench, and the actual linear velocity is obtained based on the actual wheel speed of the corresponding wheel load motor. The actual angular velocity of each on-board motor was calculated. And the actual angular velocity of each wheel Gradually approaching the target angular velocity of the corresponding wheel .

[0087] This implementation dynamically couples the resistance of the load motor with the real-time motion state of the vehicle, realizing the response and coordination between torque and driving control. It can quickly verify the effectiveness of the overall vehicle control strategy and achieve vehicle system-level collaborative simulation and control optimization.

[0088] exist Figure 5 Based on the illustrated embodiment, as one implementation of the present invention, the actual vehicle speed of each on-board motor is input to the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle.

[0089] Specifically, the actual rotational speed is obtained by monitoring the on-board motors of each wheel using an on-board encoder. The actual angular velocity of the corresponding on-board motor was calculated. The formula is as follows:

[0090] in, It can be the actual speed of the onboard motors of each wheel. (Including the actual speed of the left front wheel motor, the actual speed of the right front wheel motor, the actual speed of the left rear wheel motor, and the actual speed of the right rear wheel motor); then, based on The actual angular velocity of the on-board motors of each wheel was calculated. The formula is as follows:

[0091] in, It can be the actual angular velocity of the on-board motors of each wheel. (including the actual angular velocity of the left front wheel) Actual angular velocity of the right front wheel Actual angular velocity of the left rear wheel Actual angular velocity of the right rear wheel ).

[0092] Next, the actual angular velocity of each vehicle motor is... The input is sent to the vehicle speed and angular velocity synthesis module, whose specific calculation formula is shown below:

[0093]

[0094] in, This represents the actual longitudinal speed of the entire vehicle. This represents the actual yaw rate of the entire vehicle.

[0095] The above formula means converting the speed difference of the front wheels into the angular velocity of the vehicle body around the centerline, and dividing by the left and right track widths to obtain the actual yaw rate of the entire vehicle. The relevant explanations are as follows: First, when the actual angular velocity of the right front wheel Greater than the actual angular velocity of the left front wheel At this time, the vehicle tends to turn left, thus avoiding tire slippage and wear; Second, when the actual angular velocity of the right front wheel Less than the actual angular velocity of the left front wheel At this time, the vehicle tends to turn right, thus avoiding tire slippage and wear.

[0096] Ultimately, the vehicle speed and angular velocity synthesis module outputs the actual longitudinal speed of the entire vehicle. Compared with the actual yaw rate of the whole vehicle .

[0097] This implementation provides control parameters for the vehicle environment model to simulate the actual vehicle operating state. It uses the vehicle's inherent wheel speed to estimate the actual vehicle yaw rate in real time, providing timely state input for the stability control system and advanced driver assistance system. It combines the measurable characteristics of the distributed drive system with the vehicle's yaw stability, enabling the vehicle to infer the global state from local monitoring.

[0098] exist Figure 5 Based on the illustrated embodiment, as one implementation of the present invention, the vehicle environment model determines the external drag loss and internal torque loss, and the specific steps are as follows: Step d1: Calculate the actual longitudinal speed of the entire vehicle. Compared with the actual yaw rate of the whole vehicle The data is input into the vehicle environment model to calculate air resistance, slope resistance, and rolling resistance. The specific calculation formulas for this vehicle environment model are as follows: First, based on the actual longitudinal speed of the whole vehicle Preset air resistance coefficient vehicle frontal area and air density Calculate air resistance The formula is as follows:

[0099] First, based on the road slope angle Total vehicle weight and gravitational acceleration Calculate the slope resistance separately. With rolling resistance The specific formula is as follows: ，

[0100] Third, calculate the external resistance loss. air resistance Slope resistance With rolling resistance The sum is as follows:

[0101] Step d2: Based on the torque requirements of the entire vehicle and preset transmission system efficiency Calculate internal torque loss The specific formula is shown below:

[0102] Step d3: Calculate the external resistance loss and internal torque loss The feedback is fed back into the vehicle dynamics model to calculate the target speed of the load motor and form a closed-loop control. The specific steps have been explained in the above embodiments.

[0103] This implementation inputs the vehicle's driving state into the vehicle environment model to simulate the vehicle's real energy consumption and range, enabling the HIL simulation system to reproduce and verify the power attenuation phenomenon caused by system overheating in real hardware. At the same time, the internal and external loss results are fed back into the vehicle dynamics model, enabling the HIL simulation system to accurately simulate driving details and dynamically respond to the actual situation of the chassis hardware through software algorithms. It takes into account the real loading characteristics of the vehicle and improves the simulation accuracy during the testing phase.

[0104] Secondly, embodiments of the present invention also provide a distributed drive chassis control device 70 based on HIL, such as... Figure 7 As shown, it includes: The signal input and preprocessing module 710 is used to acquire the pedal input signal and the steering wheel angle signal, and after mapping and filtering smoothing, obtain the smooth driving torque and smooth yaw torque of the whole vehicle.

[0105] The torque distribution module 720 is used to distribute the smooth driving torque and smooth yaw torque to the four wheels based on the driving force and yaw torque fusion distribution model, so as to obtain the target torque of each wheel.

[0106] The vehicle motor control module 730 is used to send the target torque of each wheel to the actual vehicle chassis test bench via the HIL real-time communication bus, so that after receiving the target torque, the actual vehicle chassis test bench controls each vehicle motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel; at the same time, the actual vehicle chassis test bench transmits the actual torque and actual vehicle speed back to the HIL simulation controller in real time via the HIL real-time communication bus.

[0107] The load motor control module 740 is used to calculate the target angular velocity corresponding to each wheel that the four load motors need to track based on the actual torque of each wheel through the vehicle dynamics and kinematics model, and to send the target angular velocity of each load motor to the actual vehicle chassis test bench through the HIL real-time communication bus, so as to control each load motor to track its corresponding target angular velocity.

[0108] The on-board motor feedback module 750 is used to dynamically adjust the torque command of the on-board motor corresponding to each wheel based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, so as to realize the linkage balance between the on-board motor and the load motor on the four wheels.

[0109] The load motor feedback module 760 is used to input the actual vehicle speed of each on-board motor to the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle; and input the vehicle environment model to calculate the external resistance loss and internal torque loss, and feed the external resistance loss and internal torque loss back to the vehicle dynamics model to form a system-level closed-loop control.

[0110] exist Figure 7 Based on the illustrated embodiment, as one implementation of the present invention, the chassis driving control device 70 includes an on-board controller, a host computer controller, a real vehicle chassis test bench, and a distributed drive actuator. The actual vehicle chassis test bench includes a mechanical frame, an on-board motor and on-board motor control unit, a load motor and load motor control unit.

[0111] The distributed drive actuator includes at least two independently driven hub motors and their control units, an on-board encoder, a load encoder, and a torque sensor, and is mechanically mounted on the actual vehicle chassis test bench to simulate real wheels.

[0112] The host computer controller runs the HIL simulation model, and the vehicle controller sends control commands to the actual vehicle chassis test bench through the HIL real-time communication interface unit with a fixed simulation step size; and receives real-time running data transmitted back from the actual vehicle chassis test bench with the same step size.

[0113] The vehicle-mounted controller is electrically connected to the distributed actuator; the host computer controller is communicatively connected to the vehicle-mounted controller; and the actual vehicle chassis test bench is mechanically coupled to the distributed drive actuator.

[0114] Specifically, the process of executing instructions between the HIL simulation system and the actual hardware test includes at least one of the following steps: Step e1: The vehicle controller receives the execution command from the host computer controller.

[0115] Step e2: The on-board controller drives the distributed drive actuator to generate the actual torque of the on-board motor and the actual speed of the load motor on the actual vehicle chassis test bench.

[0116] Step e3: The vehicle controller receives the actual torque of the vehicle motor, the actual vehicle speed of the vehicle motor, and the actual vehicle speed of the load motor from the measurements returned by the distributed drive actuator.

[0117] Step e4: The on-board encoder monitors the actual vehicle speed of the on-board motor, the load encoder monitors the actual vehicle speed of the load motor, and the torque sensor monitors the actual torque of the on-board motor.

[0118] Thirdly, embodiments of the present invention also provide an electronic device, comprising: The processor, memory, communication interface, and communication bus communicate with each other through the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the chassis control method as described in any one of claims 1 to 7.

[0119] The technical solution provided in this invention involves acquiring pedal input signals and steering wheel angle signals, and then performing mapping and filtering smoothing processes to obtain the smooth driving torque and smooth yaw torque of the entire vehicle. Based on a fusion distribution model of driving force and yaw torque, the smooth driving torque and smooth yaw torque are distributed to the four wheels to obtain the target torque for each wheel. The target torque of each wheel is then sent to a real vehicle chassis test bench, so that after receiving the target torque, the test bench controls each on-board motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. Based on the actual torque of each wheel, the target angular velocity corresponding to each wheel is generated by calculating using a vehicle dynamics and kinematics model, and each load motor is controlled to track its corresponding target angular velocity.

[0120] Next, the torque command of the on-board motor corresponding to each wheel is dynamically adjusted so that the actual angular velocity of the on-board motor of each wheel approaches the target angular velocity of the load motor. By dynamically correcting the deviation of the torque command, the actual driving speed of the vehicle is ensured to closely follow the target driving curve in real time. When high-risk and complex working conditions occur in the real vehicle test, the chassis hardware is dynamically matched and responded. The on-board motor and the load motor jointly generate the actual angular velocity on the mechanical shaft system to achieve system-level closed-loop control. The external resistance loss and internal torque loss calculated by the vehicle environment model are fed back to the vehicle dynamics model to reproduce the real scenario. By dynamically loading road resistance, vehicle inertia and coupled dynamics that conform to physical laws, controllable delays, noise and faults are introduced and fed back to the driving control to build a closed-loop verification system between the driver, vehicle and environment. This allows the software control strategy to obtain the real vehicle response and make further adjustments during the test.

[0121] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A distributed drive chassis control method based on HIL, characterized in that, include: The pedal input signal and steering wheel angle signal are acquired, and after mapping and filtering smoothing, the smooth driving torque and smooth yaw torque of the whole vehicle are obtained. Based on the fusion distribution model of driving force and yaw moment, the smooth driving moment and smooth yaw moment are distributed to the four wheels to obtain the target torque of each wheel. The target torque of each wheel is sent to the actual vehicle chassis test bench via the HIL real-time communication bus. After receiving the target torque, the actual vehicle chassis test bench controls each on-board motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. At the same time, the actual vehicle chassis test bench transmits the actual torque and actual vehicle speed back to the HIL simulation controller in real time via the HIL real-time communication bus. Based on the actual torque of each wheel, the target angular velocity corresponding to each wheel that the four load motors need to track is generated by vehicle dynamics and kinematics model calculation. The target angular velocity of each load motor is sent to the actual vehicle chassis test bench through HIL real-time communication bus, and each load motor is controlled to track its corresponding target angular velocity. Based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, the torque command of the on-board motor corresponding to that wheel is dynamically adjusted to achieve linkage balance between the on-board motors and the load motors on the four wheels. The actual vehicle speed of each on-board motor is input into the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle; and input into the vehicle environment model to calculate the external resistance loss and internal torque loss, and feed the external resistance loss and internal torque loss back to the vehicle dynamics model to form a system-level closed-loop control.

2. The method according to claim 1, characterized in that, Based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, the torque command of the on-board motor corresponding to that wheel is dynamically adjusted, including: For each wheel, the gain coefficient is adaptively adjusted based on the difference between the actual angular velocity of the on-board motor corresponding to the wheel and the target angular velocity of the load motor corresponding to the wheel. Based on the gain coefficient, the difference, and the target torque of the wheel, the adjusted torque command of the wheel is calculated. Specifically, when the actual angular velocity is less than the target angular velocity, the gain coefficient is increased to increase the torque command; When the actual angular velocity is greater than the target angular velocity, the gain coefficient is reduced to decrease the torque command; When the actual angular velocity equals the target angular velocity, maintain the current torque command.

3. The method according to claim 1, characterized in that, The pedal input signal and steering wheel angle signal are acquired, and after mapping and filtering smoothing, the smooth driving torque and smooth yaw torque of the whole vehicle are obtained, including: Based on the curve mapping relationship table between driving torque and pedal opening, and the curve mapping relationship table between yaw moment and steering wheel angle, the pedal input signal and steering wheel angle signal are mapped to the initial driving torque requirement and the initial yaw moment requirement respectively by curve lookup and interpolation. The initial driving torque requirement and the initial yaw torque requirement are smoothed by passing them through a first-order low-pass filter to obtain the smoothed driving torque and smoothed yaw torque.

4. The method according to claim 1, characterized in that, Based on the fusion distribution model of driving force and yaw moment, the smooth driving torque and smooth yaw moment are distributed to the four wheels to obtain the target torque of each wheel, which is achieved through the following constraints: The sum of the longitudinal forces of the four wheels is equal to the smooth driving torque; The sum of the longitudinal forces of the right front wheel and the left rear wheel minus the sum of the longitudinal forces of the left front wheel and the right rear wheel is proportional to the smooth yaw moment, and the proportionality coefficient is the reciprocal of the vehicle's left and right track width. After distributing the longitudinal forces to each wheel under the above constraints, the longitudinal forces are divided by the wheel radius to obtain the target torque of the corresponding wheel.

5. The method according to claim 1, characterized in that, The vehicle dynamics and kinematics model includes a vehicle dynamics model and a vehicle kinematics model; the calculation based on the actual torque of each wheel, using the vehicle dynamics and kinematics model, generates the target angular velocities corresponding to each wheel that the four load motors need to track, including: Based on the actual torque of each wheel, the actual vehicle driving torque and the actual vehicle yaw torque are synthesized. The actual vehicle driving torque and actual vehicle yaw torque are input into the vehicle dynamics model; so that the vehicle dynamics model calculates the vehicle's longitudinal acceleration and yaw acceleration based on the vehicle's mass and moment of inertia parameters, and in combination with the external drag loss and internal torque loss fed back by the vehicle environment model. Integrate the calculated longitudinal acceleration and yaw acceleration to obtain the vehicle's longitudinal velocity and yaw rate; The longitudinal velocity and yaw rate are input into the vehicle kinematics model so that the vehicle kinematics model combines the longitudinal velocity and yaw rate into the target linear velocity of the four wheels according to the left and right wheel track of the vehicle, and converts the target linear velocity of the four wheels into the target angular velocity of the corresponding load motor.

6. The method according to claim 1, characterized in that, The actual vehicle speed of each on-board motor is input into the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the entire vehicle, including: Convert the actual vehicle speed of each on-board motor into the actual angular velocity of the corresponding wheel; The actual angular velocities of each wheel are input into the vehicle speed and angular velocity synthesis module, so that the vehicle speed and angular velocity synthesis module can synthesize the actual longitudinal speed and actual yaw rate of the whole vehicle based on the actual angular velocities of each wheel, the wheel radius and the left and right wheel distance of the vehicle. Wherein, the actual longitudinal speed of the whole vehicle is the average of the linear speeds corresponding to the actual angular velocities of the four wheels; The actual yaw rate of the vehicle is proportional to the difference between the actual angular velocities of the left and right front wheels, and the proportionality coefficient is the ratio of the wheel radius to the wheel track.

7. The method according to claim 1, characterized in that, The vehicle environment model determines the external drag loss and internal torque loss, including: Calculate the air resistance based on the actual longitudinal speed of the vehicle, the preset air resistance coefficient, the vehicle's frontal area, and the air density; Calculate the slope resistance and rolling resistance based on the actual longitudinal speed of the vehicle, the corresponding road slope angle, the vehicle mass, and the gravitational acceleration. The external resistance loss is obtained by summing the air resistance, slope resistance, and rolling resistance: The internal torque loss is calculated based on the vehicle's required torque and the preset transmission system efficiency, wherein the vehicle's required torque is the sum of the target torques of each wheel.

8. A distributed drive chassis control device based on HIL, characterized in that, include: The signal input and preprocessing module is used to acquire pedal input signals and steering wheel angle signals, and after mapping and filtering smoothing, obtain the smooth driving torque and smooth yaw torque of the whole vehicle. The torque distribution module is used to distribute the smooth driving torque and smooth yaw torque to the four wheels based on the driving force and yaw torque fusion distribution model, so as to obtain the target torque of each wheel. The vehicle motor control module is used to send the target torque of each wheel to the actual vehicle chassis test bench via the HIL real-time communication bus. After receiving the target torque, the actual vehicle chassis test bench controls each vehicle motor to output the corresponding actual torque and actual vehicle speed, and calculates the corresponding actual angular velocity based on the actual vehicle speed of each wheel. At the same time, the actual vehicle chassis test bench transmits the actual torque and actual vehicle speed back to the HIL simulation controller in real time via the HIL real-time communication bus. The load motor control module is used to calculate the target angular velocity corresponding to each wheel that the four load motors need to track based on the actual torque of each wheel through vehicle dynamics and kinematics models. It then sends the target angular velocity of each load motor to the actual vehicle chassis test bench through the HIL real-time communication bus, and controls each load motor to track its corresponding target angular velocity. The on-board motor feedback module is used to dynamically adjust the torque command of the on-board motor corresponding to each wheel based on the difference between the actual angular velocity of the on-board motor corresponding to each wheel and the target angular velocity of the load motor corresponding to that wheel, so as to achieve linkage balance between the on-board motor and the load motor on the four wheels. The load motor feedback module is used to input the actual vehicle speed of each on-board motor into the vehicle speed and angular velocity synthesis module to obtain the actual longitudinal speed and actual yaw rate of the whole vehicle; and input the vehicle environment model to calculate the external resistance loss and internal torque loss, and feed the external resistance loss and internal torque loss back to the vehicle dynamics model to form a system-level closed-loop control.

9. The apparatus according to claim 8, characterized in that, The chassis driving control device includes an on-board controller, a host computer controller, a real vehicle chassis test bench, and a distributed drive actuator. The actual vehicle chassis test bench includes a mechanical frame, an on-board motor and an on-board motor control unit, a load motor and a load motor control unit; The distributed drive actuator includes at least two independently driven hub motors and their control units, an on-board encoder, a load encoder, and a torque sensor, and is mechanically mounted on the actual vehicle chassis test bench to simulate real wheels; The host computer controller runs the HIL simulation model, and the vehicle controller sends control commands to the actual vehicle chassis test bench through the HIL real-time communication interface unit at a fixed simulation step size; and receives the real-time running data returned by the actual vehicle chassis test bench at the same step size. The HIL real-time communication interface unit is connected to the host computer controller and the distributed drive actuator, respectively.

10. An electronic device, characterized in that, include: Processor, memory, communication interface and communication bus, The processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction that causes the processor to perform the operation of the chassis control method as described in any one of claims 1 to 7.

Images