Distributed drive torque distribution method, device, equipment and readable storage medium

Abstract

A distributed drive torque distribution method, device, equipment and readable storage medium. The method comprises: solving an optimization target with a constraint condition to obtain a target longitudinal driving force of each wheel, wherein the optimization target comprises minimizing the maximum road adhesion utilization rate of each wheel, minimizing the average value and standard deviation of the road adhesion utilization rate of all wheels, and minimizing the difference between the yaw moment formed by the tire force and the expected yaw moment; based on the target longitudinal driving force of each wheel, the output driving torque of each motor corresponding to each wheel is controlled. Through the present application, the driving force output by each motor is controlled based on the optimization target with the constraint condition, so that the road adhesion utilization rate of the wheel with the maximum road adhesion utilization rate is as small as possible, each wheel of the distributed drive vehicle is as far away from the friction boundary as possible, thereby expanding the stability performance boundary of the whole vehicle and improving the stability of the whole vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, specifically to a distributed drive torque distribution method, device, equipment, and computer-readable storage medium. Background Technology

[0002] In extreme conditions such as high-speed lane changes, distributed drive vehicles are limited by the limited friction of the wheels. When some wheels reach the friction boundary, the lateral friction becomes insufficient, and the whole vehicle is at risk of instability. Summary of the Invention

[0003] This application provides a distributed drive torque distribution method, apparatus, device, and computer-readable storage medium, which can solve the technical problem of high instability risk in distributed drive vehicles in the prior art.

[0004] In a first aspect, embodiments of this application provide a distributed drive torque distribution method, the distributed drive torque distribution method comprising: Within the current control cycle, based on the formula for calculating the road surface adhesion utilization rate of wheel i, the road surface adhesion utilization rate of each wheel at the current moment is calculated, and the wheel with the highest road surface adhesion utilization rate among all wheels is determined as wheel j. An optimization objective with constraints is constructed, wherein the optimization objective includes a first optimization objective, a second optimization objective, and a third optimization objective, and the first optimization objective is the optimized value of the road surface adhesion utilization rate of wheel j. With penalty items The second optimization objective is to minimize the sum of the average and standard deviation of the road adhesion utilization rates of each wheel; the third optimization objective is to minimize the square of the difference between the yaw moment generated by the tire force and the desired yaw moment. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j. The constraints include inequality constraints:

[0005] in, This is the optimized value for the road surface adhesion utilization rate of wheel i; The constrained optimization objective is solved to obtain the target longitudinal driving force of each wheel. Based on the target longitudinal driving force of each wheel, the output driving torque of each motor corresponding to each wheel is controlled.

[0006] In conjunction with the first aspect, in one implementation method, the formula for calculating the road surface adhesion utilization rate of the wheel is:

[0007] in, For the road surface adhesion utilization rate of wheel i, The longitudinal driving force of wheel i, Let be the coefficient of adhesion of the road surface where wheel i is located. Let be the vertical load on wheel i.

[0008] In conjunction with the first aspect, in one embodiment, the wheel includes a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, and the formula for calculating the yaw moment generated by the tire force is:

[0009] in, The yaw moment is caused by the tire force. For the longitudinal driving force of the left front wheel, For the longitudinal driving force of the right front wheel, For the longitudinal driving force of the left rear wheel, For the longitudinal driving force of the right rear wheel, The steering angle of the vehicle's front wheels. The track width between the left and right wheels. This is the distance from the vehicle's center of gravity to the front axle.

[0010] In conjunction with the first aspect, in one implementation, the constraints include each wheel being limited by the motor speed-torque external characteristic curve.

[0011] In conjunction with the first aspect, in one embodiment, the constraint condition includes the tire force of each wheel being located within the friction circle.

[0012] In conjunction with the first aspect, in one implementation, the constraint condition includes the vehicle longitudinal force obtained by combining the target longitudinal driving forces of each wheel to meet the target longitudinal force requirement.

[0013] Secondly, embodiments of this application provide a distributed drive torque distribution device, the distributed drive torque distribution device comprising: The solution module is used to calculate the road adhesion utilization rate of each wheel at the current moment within the current control cycle, based on the calculation formula of the road adhesion utilization rate of wheel i, and to determine the wheel with the highest road adhesion utilization rate as wheel j. It also solves for the constrained optimization objectives to obtain the target longitudinal driving force of each wheel. The optimization objectives include a first optimization objective, a second optimization objective, and a third optimization objective, where the first optimization objective is the optimized value of the road adhesion utilization rate of wheel j. With penalty items The second optimization objective is to minimize the sum of the average and standard deviation of the road adhesion utilization rates of each wheel; the third optimization objective is to minimize the square of the difference between the yaw moment generated by the tire force and the desired yaw moment. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j. The constraints include inequality constraints:

[0014] in, This is the optimized value for the road surface adhesion utilization rate of wheel i; The control module is used to control the output driving torque of each motor corresponding to each wheel based on the target longitudinal driving force of each wheel.

[0015] Thirdly, embodiments of this application provide a vehicle that includes the distributed drive torque distribution device as described in the second aspect.

[0016] Fourthly, embodiments of this application provide a distributed drive torque distribution device, the distributed drive torque distribution device including a processor, a memory, and a distributed drive torque distribution program stored in the memory and executable by the processor, wherein when the distributed drive torque distribution program is executed by the processor, it implements the steps of the distributed drive torque distribution method as described in the first aspect.

[0017] Fifthly, embodiments of this application provide a computer-readable storage medium storing a distributed drive torque allocation program, wherein when the distributed drive torque allocation program is executed by a processor, it implements the steps of the distributed drive torque allocation method as described in the first aspect.

[0018] The beneficial effects of the technical solutions provided in this application include: In this embodiment, an optimization objective with constraints is solved to obtain the target longitudinal driving force of each wheel. The optimization objective includes minimizing the maximum road surface adhesion utilization rate of each wheel, minimizing the average and standard deviation of the road surface adhesion utilization rates of all wheels, and minimizing the difference between the yaw moment generated by tire forces and the desired yaw moment. Based on the target longitudinal driving force of each wheel, the output driving torque of each motor corresponding to each wheel is controlled. Through this embodiment, by controlling the driving force output of each motor based on the optimization objective without constraints, the road surface adhesion utilization rate of the wheel with the highest utilization rate is minimized, and the wheels of the distributed drive vehicle are kept as far away from the friction boundary as possible, thereby expanding the stability performance boundary of the entire vehicle and improving the overall vehicle stability. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating an embodiment of the distributed drive torque distribution method of this application; Figure 2 This is a functional block diagram of an embodiment of the distributed drive torque distribution device of this application; Figure 3 This is a schematic diagram of the hardware structure of the distributed drive torque distribution device involved in the embodiments of this application. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0022] In a first aspect, embodiments of this application provide a distributed drive torque distribution method.

[0023] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the distributed drive torque distribution method of this application. Figure 1 As shown, the distributed drive torque distribution method includes: Step S10: Solve the optimization objective with constraints to obtain the target longitudinal driving force of each wheel. The optimization objective includes minimizing the maximum road surface adhesion utilization rate of each wheel, minimizing the average and standard deviation of the road surface adhesion utilization rate of all wheels, and minimizing the difference between the yaw moment formed by the tire force and the desired yaw moment. In this embodiment, the distributed drive torque distribution method is executed by the lower-level controller in the torque vector control architecture. The torque vector control architecture mainly includes functional modules such as a driver model, a reference model, an upper-level controller, and a lower-level controller. It achieves vehicle power control by adjusting the torque of the four wheels of the distributed drive vehicle. A brief description of each sub-module is as follows.

[0024] 1. Driver model: Used to determine the vehicle's driving force based on the vehicle's driving needs and the mapping relationship between the driver's accelerator pedal and the distributed drive system's overall driving force. Specifically:

[0025] in, For the accelerator pedal, For the driving torque of the whole vehicle, This represents the peak torque of the motor. The vehicle's driving torque, also known as the driving force required for the vehicle to move forward, can be considered as the mapping relationship between the opening of the accelerator pedal and the driving force required to propel the vehicle forward.

[0026] 2. A reference model is used to establish a mapping from the desired control target to the desired yaw rate based on the steering wheel angle operated by the driver and the vehicle's state parameters, generating a desired yaw rate tracking sequence for the torque vector controller. Specifically:

[0027] Among them, the desired yaw rate is a precise value that the driver expects the vehicle to "turn fast" when turning. It is determined by the steering wheel angle and vehicle speed, and is the core target of the vehicle stability control system in judging the driver's intention.

[0028] 3. The upper-level controller calculates the desired yaw moment of the vehicle based on its current driving state, the expected information generated by the reference model, and the control demand analysis information generated by the control demand analysis module, and then inputs this desired yaw moment into the lower-level controller. Specifically:

[0029] The desired yaw moment is a precise "rotational force" that needs to be applied to the vehicle body in order to achieve or maintain the turning state (such as how fast) desired by the driver.

[0030] The aforementioned driver model, reference model, and upper-level controller are not the focus of this application; for specific details, please refer to the description of the prior art.

[0031] 4. The lower-level controller is used to determine the current driving status of the vehicle and the desired yaw torque sent by the upper-level controller. By specifically considering the road adhesion utilization rate of each wheel of the distributed drive electric vehicle, it minimizes the road adhesion utilization rate of the wheel with the highest road adhesion utilization rate and keeps each wheel of the distributed drive vehicle as far away from the friction boundary as possible, thereby expanding the stability performance boundary of the whole vehicle and improving the stability of the whole vehicle.

[0032] For the lower-level controller, the optimization objective with constraints is constructed and solved to obtain the target longitudinal driving force of each wheel, so as to achieve the optimization objective while satisfying the constraints.

[0033] Taking a vehicle with four wheels as an example, the process of constructing the optimization objective is as follows: First, we need to consider the road surface adhesion utilization rate of each wheel, so that the road surface adhesion utilization rate of the wheel with the highest road surface adhesion utilization rate is minimized.

[0034] Optimization objective 1: Minimize the maximum road surface adhesion utilization rate of each wheel.

[0035] Among them, the road surface adhesion utilization rate of wheel i is:

[0036] i = 1, 2, 3, 4 represent the left front, right front, left rear, and right rear wheels of the vehicle, respectively; F xi F yi F zi These are the longitudinal driving force, lateral driving force, and vertical load of wheel i, respectively. Let be the coefficient of adhesion of the road surface where wheel i is located.

[0037] Because the distributed drive motor directly controls the longitudinal driving force of the tires, but cannot directly control the lateral driving force of the tires. Also considering F yi For optimization problems, this is a constant term, and its value has no impact on the optimal solution. To achieve the goal of minimizing tire adhesion utilization and reducing computational complexity by adjusting the longitudinal driving force of each wheel, the formula for calculating the road adhesion utilization of wheel i is simplified as follows:

[0038] in, For the road surface adhesion utilization rate of wheel i, The longitudinal driving force of wheel i, Let be the vertical load on wheel i.

[0039] By distributing driving force to the four drive wheels of a distributed drive vehicle to achieve the longitudinal force and yaw moment required by the driver, the optimal road adhesion utilization vector can be obtained, denoted as:

[0040] To achieve stability in a distributed drive vehicle and enhance tire road grip margin, it is desirable to minimize the road grip utilization rate of all tires. If there are four drive wheels, to ensure the vehicle's road grip utilization rate is minimized, we can minimize the road grip utilization rate of the drive wheel with the highest road grip utilization rate, expressed as follows:

[0041] Here, minmax is the minimum-maximum function, which has no gradient and cannot be solved using gradient-based optimization methods. Typically, minimum-maximum functions require heuristic optimization algorithms for computation, but online computation remains quite difficult. To address this issue, this embodiment designs the following transformation steps 1 and 2 to transform the minimum-maximum function into a more manageable minimization function. The transformed minimization function has a gradient and is easier to process.

[0042] Step 1: Find the tire with the highest road adhesion utilization rate at the current moment. At the current moment, according to the formula for calculating the road adhesion utilization rate of wheel i, the road adhesion utilization rate vector of the four tires is denoted as:

[0043] exist In the current index, the one with the highest road surface adhesion utilization rate is: , where j represents the j-th tire with the highest road surface adhesion utilization rate.

[0044] Transformation Step 2: Minimize the road adhesion utilization rate of the drive wheel that maximizes road adhesion utilization, as expressed below:

[0045] However, simply minimizing the road adhesion utilization of the drive wheel with the highest road adhesion utilization is insufficient to solve this problem. It is also necessary to ensure that the road adhesion utilization of other vehicles is as low as possible. This objective can be stated as follows:

[0046] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0047] Slack variables help make optimization problems solvable, thus avoiding Cases where the condition cannot be met. Taking a four-wheeled vehicle as an example, the number of slack variables is 3. Including the slack variables in the optimization objective function, the expression for the first optimization objective is denoted as:

[0048] in, The optimal value for the road adhesion utilization rate of wheel j, which maximizes road adhesion utilization rate. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j.

[0049] Through specially designed transformation steps 1 and 2, the minimum-maximum optimization objective is transformed into a minimum optimization objective with constraints. These constraints are inequality constraints, expressed as follows:

[0050] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0051] Optimization objective 2: Minimize the mean and dispersion of road surface adhesion consumption rate.

[0052] When distributing longitudinal driving force to the four tires, it is desirable to minimize the road grip utilization of all tires. Besides optimization... In addition, the overall road adhesion utilization rate of multiple tires should also be considered. The expression for the second optimization objective is as follows:

[0053] in, and They are respectively The mean and standard deviation are calculated. Assuming wheel j is the right front wheel, then wheel i includes the left front wheel, left rear wheel, and right rear wheel. The average value is calculated based on the road adhesion utilization rates of the left front wheel, left rear wheel, and right rear wheel. The standard deviation was calculated based on the road adhesion utilization rates of the left front wheel, the left rear wheel, and the right rear wheel. .

[0054] Optimization objective 3: Minimize the difference between the yaw moment generated by the optimized tire force and the desired yaw moment.

[0055] The formula for calculating the yaw moment generated by tire force is:

[0056] in, The yaw moment is caused by the tire force. For the longitudinal driving force of the left front wheel, For the longitudinal driving force of the right front wheel, For the longitudinal driving force of the left rear wheel, For the longitudinal driving force of the right rear wheel, The steering angle of the vehicle's front wheels. The track width between the left and right wheels. This is the distance from the vehicle's center of gravity to the front axle.

[0057] The yaw moment generated by tire force and the desired yaw moment are subject to an equality constraint. This equality constraint is highly unfavorable for optimization problems. Therefore, this equality constraint is rewritten as a soft constraint in the optimization objective, as follows: The expression for the third optimization objective is as follows:

[0058] Where M zd The desired yaw moment.

[0059] In addition to the optimization objective, constructing the optimization problem also requires considering one or more constraints. These constraints include: each wheel being limited by the motor speed-torque external characteristic curve; the tire force of each wheel being within the friction circle; the vehicle's longitudinal force, obtained by combining the target longitudinal driving forces of all wheels, satisfying the target longitudinal force requirement; and at least one of the following inequality constraints: Specifically: Constraint 1: Each wheel is limited by the physical characteristics of the motor (motor speed-torque external characteristic curve), as expressed below:

[0060] Among them, T max R is the peak torque of the motor. e Let be the radius of rotation of the wheel.

[0061] Constraint 2: The tire force of each tire lies within the friction circle, as expressed below:

[0062] Among them, F xi F yi F zi These are the longitudinal driving force, lateral driving force, and vertical load of wheel i, respectively. Let be the coefficient of adhesion of the road surface where wheel i is located.

[0063] Constraint 3: Direct yaw moment control of the vehicle involves distributing the longitudinal forces of the four wheels. Therefore, the resultant torque of the longitudinal forces of the wheels must meet the target yaw moment requirement, and the resultant longitudinal force must also meet the driver's target longitudinal force requirement for the vehicle during driving. The expression is as follows:

[0064] in, Let be the desired longitudinal force of the vehicle.

[0065] Constraint 4: Inequality constraint, expressed as follows:

[0066] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0067] Taking all optimization objectives and constraints into account, the overall constrained optimization objective is expressed as follows:

[0068] By solving the above-mentioned constrained optimization objective, the target longitudinal driving force of each wheel that satisfies the constraints and achieves the optimization objective is obtained.

[0069] Step S20: Based on the target longitudinal driving force of each wheel, control the output driving torque of each motor corresponding to each wheel.

[0070] In this embodiment, the target longitudinal driving force of each wheel is calculated in each control cycle, for example, the target longitudinal driving force of the four wheels is obtained and denoted as F. x1 F x2 F x3 F x4 Then, it can be converted into the target driving torque of the motor using the following formula:

[0071] in, Let be the moment of inertia of the wheel. Let be the radius of rotation of the wheel.

[0072] It's easy to understand that, assuming each of the four wheels is controlled by a separate motor, the target driving torque for each motor in the vehicle can be obtained. This target driving torque is then output to each motor, allowing each motor to output its own driving torque based on the received target driving torque. This ensures that each wheel is as far away from the friction boundary as possible, thereby expanding the overall vehicle's stability performance boundary and improving overall vehicle stability.

[0073] In this embodiment, an optimization objective with constraints is solved to obtain the target longitudinal driving force of each wheel. The optimization objective includes minimizing the maximum road surface adhesion utilization rate of each wheel, minimizing the average and standard deviation of the road surface adhesion utilization rates of all wheels, and minimizing the difference between the yaw moment generated by tire forces and the desired yaw moment. Based on the target longitudinal driving force of each wheel, the output driving torque of each motor corresponding to each wheel is controlled. Through this embodiment, by controlling the driving force output of each motor based on the optimization objective without constraints, the road surface adhesion utilization rate of the wheel with the highest utilization rate is minimized, and the wheels of the distributed drive vehicle are kept as far away from the friction boundary as possible, thereby expanding the stability performance boundary of the entire vehicle and improving the overall vehicle stability.

[0074] Secondly, embodiments of this application also provide a distributed drive torque distribution device.

[0075] In one embodiment, reference is made to Figure 2 , Figure 2 This is a functional block diagram of an embodiment of the distributed drive torque distribution device of this application. Figure 2 As shown, the distributed drive torque distribution device includes: The solution module 10 is used to solve the optimization objective with constraints to obtain the target longitudinal driving force of each wheel. The optimization objective includes minimizing the maximum road surface adhesion utilization rate of each wheel, minimizing the average and standard deviation of the road surface adhesion utilization rate of all wheels, and minimizing the difference between the yaw moment formed by the tire force and the desired yaw moment. The control module 20 is used to control the output driving torque of each motor corresponding to each wheel based on the target longitudinal driving force of each wheel.

[0076] Furthermore, in one embodiment, the formula for calculating the road surface adhesion utilization rate of the wheel is:

[0077] in, For the road surface adhesion utilization rate of wheel i, The longitudinal driving force of wheel i, Let be the coefficient of adhesion of the road surface where wheel i is located. Let be the vertical load on wheel i.

[0078] Furthermore, in one embodiment, the wheel includes a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, and the formula for calculating the yaw moment generated by the tire force is:

[0079] in, The yaw moment is caused by the tire force. For the longitudinal driving force of the left front wheel, For the longitudinal driving force of the right front wheel, For the longitudinal driving force of the left rear wheel, For the longitudinal driving force of the right rear wheel, The steering angle of the vehicle's front wheels. The track width between the left and right wheels. This is the distance from the vehicle's center of gravity to the front axle.

[0080] Furthermore, in one embodiment, the constraints include each wheel being limited by the motor speed-torque external characteristic curve.

[0081] Furthermore, in one embodiment, the constraint condition includes the tire force of each wheel being located within the friction circle.

[0082] Furthermore, in one embodiment, the constraint condition includes the vehicle longitudinal force obtained by combining the target longitudinal driving forces of each wheel to meet the target longitudinal force requirement.

[0083] Furthermore, in one embodiment, the expression for minimizing the maximum road surface adhesion utilization rate of each wheel is:

[0084] in, The optimal value for the road adhesion utilization rate of wheel j, which maximizes road adhesion utilization rate. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j.

[0085] Furthermore, in one embodiment, the constraint condition includes an inequality constraint, expressed as follows:

[0086] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0087] In this embodiment, taking a vehicle with four wheels as an example, the process of constructing the optimization objective is as follows: First, we need to consider the road surface adhesion utilization rate of each wheel, so that the road surface adhesion utilization rate of the wheel with the highest road surface adhesion utilization rate is minimized.

[0088] Optimization objective 1: Minimize the maximum road surface adhesion utilization rate of each wheel.

[0089] Among them, the road surface adhesion utilization rate of wheel i is:

[0090] i = 1, 2, 3, 4 represent the left front, right front, left rear, and right rear wheels of the vehicle, respectively; F xi F yi F zi These are the longitudinal driving force, lateral driving force, and vertical load of wheel i, respectively. Let be the coefficient of adhesion of the road surface where wheel i is located.

[0091] Because the distributed drive motor directly controls the longitudinal driving force of the tires, but cannot directly control the lateral driving force of the tires. Also considering F yi For optimization problems, this is a constant term, and its value has no impact on the optimal solution. To achieve the goal of minimizing tire adhesion utilization and reducing computational complexity by adjusting the longitudinal driving force of each wheel, the formula for calculating the road adhesion utilization of wheel i is simplified as follows:

[0092] in, For the road surface adhesion utilization rate of wheel i, The longitudinal driving force of wheel i, Let be the vertical load on wheel i.

[0093] By distributing driving force to the four drive wheels of a distributed drive vehicle to achieve the longitudinal force and yaw moment required by the driver, the optimal road adhesion utilization vector can be obtained, denoted as:

[0094] To achieve stability in a distributed drive vehicle and enhance tire road grip margin, it is desirable to minimize the road grip utilization rate of all tires. If there are four drive wheels, to ensure the vehicle's road grip utilization rate is minimized, we can minimize the road grip utilization rate of the drive wheel with the highest road grip utilization rate, expressed as follows:

[0095] Here, minmax is the minimum-maximum function, which has no gradient and cannot be solved using gradient-based optimization methods. Typically, minimum-maximum functions require heuristic optimization algorithms for computation, but online computation remains quite difficult. To address this issue, this embodiment designs the following transformation steps 1 and 2 to transform the minimum-maximum function into a more manageable minimization function. The transformed minimization function has a gradient and is easier to process.

[0096] Step 1: Find the tire with the highest road adhesion utilization rate at the current moment. At the current moment, according to the formula for calculating the road adhesion utilization rate of wheel i, the road adhesion utilization rate vector of the four tires is denoted as:

[0097] exist In the current context, the index with the highest current adhesion coefficient consumption is... , where j represents the j-th tire with the highest road surface adhesion utilization rate.

[0098] Transformation Step 2: Minimize the road adhesion utilization rate of the drive wheel that maximizes road adhesion utilization, as expressed below:

[0099] However, simply minimizing the road adhesion utilization of the drive wheel with the highest road adhesion utilization is insufficient to solve this problem. It is also necessary to ensure that the road adhesion utilization of other vehicles is as low as possible. This objective can be stated as follows:

[0100] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0101] Slack variables help make optimization problems solvable, thus avoiding Cases where the condition cannot be met. Taking a four-wheeled vehicle as an example, the number of slack variables is 3. Including the slack variables in the optimization objective function, the expression for the first optimization objective is denoted as:

[0102] in, The optimal value for the road adhesion utilization rate of wheel j, which maximizes road adhesion utilization rate. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j.

[0103] Through specially designed transformation steps 1 and 2, the minimum-maximum optimization objective is transformed into a minimum optimization objective with constraints. These constraints are inequality constraints, expressed as follows:

[0104] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0105] Optimization objective 2: Minimize the mean and dispersion of road surface adhesion consumption rate.

[0106] When distributing longitudinal driving force to the four tires, it is desirable to minimize the road grip utilization of all tires. Besides optimization... In addition, the overall road adhesion utilization rate of multiple tires should also be considered. The expression for the second optimization objective is as follows:

[0107] in, and They are respectively The mean and standard deviation are calculated. Assuming wheel j is the right front wheel, then wheel i includes the left front wheel, left rear wheel, and right rear wheel. The average value is calculated based on the road adhesion utilization rates of the left front wheel, left rear wheel, and right rear wheel. The standard deviation was calculated based on the road adhesion utilization rates of the left front wheel, the left rear wheel, and the right rear wheel. .

[0108] Optimization objective 3: Minimize the difference between the yaw moment generated by the optimized tire force and the desired yaw moment.

[0109] The formula for calculating the yaw moment generated by tire force is:

[0110] in, The yaw moment is caused by the tire force. For the longitudinal driving force of the left front wheel, For the longitudinal driving force of the right front wheel, For the longitudinal driving force of the left rear wheel, For the longitudinal driving force of the right rear wheel, The steering angle of the vehicle's front wheels. The track width between the left and right wheels. This is the distance from the vehicle's center of gravity to the front axle.

[0111] The yaw moment generated by tire force and the desired yaw moment are subject to an equality constraint. This equality constraint is highly unfavorable for optimization problems. Therefore, this equality constraint is rewritten as a soft constraint in the optimization objective, as follows: The expression for the third optimization objective is as follows:

[0112] Where M zd The desired yaw moment.

[0113] In addition to the optimization objective, constructing the optimization problem also requires considering one or more constraints. These constraints include: each wheel being limited by the motor speed-torque external characteristic curve; the tire force of each wheel being within the friction circle; the vehicle's longitudinal force, obtained by combining the target longitudinal driving forces of all wheels, satisfying the target longitudinal force requirement; and at least one of the following inequality constraints: Specifically: Constraint 1: Each wheel is limited by the physical characteristics of the motor (motor speed-torque external characteristic curve), as expressed below:

[0114] Among them, T max R is the peak torque of the motor. e Let be the radius of rotation of the wheel.

[0115] Constraint 2: The tire force of each tire lies within the friction circle, as expressed below:

[0116] Among them, F xi F yi F zi These are the longitudinal driving force, lateral driving force, and vertical load of wheel i, respectively. Let be the coefficient of adhesion of the road surface where wheel i is located.

[0117] Constraint 3: Direct yaw moment control of the vehicle involves distributing the longitudinal forces of the four wheels. Therefore, the resultant torque of the longitudinal forces of the wheels must meet the target yaw moment requirement, and the resultant longitudinal force must also meet the driver's target longitudinal force requirement for the vehicle during driving. The expression is as follows:

[0118] in, Let be the desired longitudinal force of the vehicle.

[0119] Constraint 4: Inequality constraint, expressed as follows:

[0120] in, This is the optimized value for the road surface adhesion utilization rate of wheel i.

[0121] Taking all optimization objectives and constraints into account, the overall constrained optimization objective is expressed as follows:

[0122] By solving the above-mentioned constrained optimization objective, the target longitudinal driving force of each wheel that satisfies the constraints and achieves the optimization objective is obtained.

[0123] By solving for the target longitudinal driving force of each wheel in each control cycle, for example, the target longitudinal driving force of four wheels is obtained, denoted as F. x1 F x2 F x3 F x4 Then, it can be converted into the target driving torque of the motor using the following formula:

[0124] in, Let be the moment of inertia of the wheel. Let be the radius of rotation of the wheel.

[0125] It's easy to understand that, assuming each of the four wheels is controlled by a separate motor, the target driving torque for each motor in the vehicle can be obtained. This target driving torque is then output to each motor, allowing each motor to output its own driving torque based on the received target driving torque. This ensures that each wheel is as far away from the friction boundary as possible, thereby expanding the overall vehicle's stability performance boundary and improving overall vehicle stability.

[0126] In this embodiment, an optimization objective with constraints is solved to obtain the target longitudinal driving force of each wheel. The optimization objective includes minimizing the maximum road surface adhesion utilization rate of each wheel, minimizing the average and standard deviation of the road surface adhesion utilization rates of all wheels, and minimizing the difference between the yaw moment generated by tire forces and the desired yaw moment. Based on the target longitudinal driving force of each wheel, the output driving torque of each motor corresponding to each wheel is controlled. Through this embodiment, by controlling the driving force output of each motor based on the optimization objective without constraints, the road surface adhesion utilization rate of the wheel with the highest utilization rate is minimized, and the wheels of the distributed drive vehicle are kept as far away from the friction boundary as possible, thereby expanding the stability performance boundary of the entire vehicle and improving the overall vehicle stability.

[0127] Thirdly, embodiments of this application provide a vehicle.

[0128] In one embodiment, the vehicle includes a distributed drive torque distribution device as described in the second aspect. Specific embodiments are described in the second aspect and will not be repeated here.

[0129] Fourthly, embodiments of this application provide a distributed drive torque distribution device, which may be a driver assistance controller, motor controller, or other device with data processing capabilities.

[0130] Reference Figure 3 , Figure 3 This is a schematic diagram of the hardware structure of the distributed drive torque distribution device involved in the embodiments of this application. In the embodiments of this application, the distributed drive torque distribution device may include a processor, a memory, a communication interface, and a communication bus.

[0131] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0132] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting devices within the distributed drive torque distribution device, as well as interfaces used for interconnecting the distributed drive torque distribution device with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0133] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0134] The processor can be a general-purpose processor, which can call the distributed drive torque allocation program stored in memory and execute the distributed drive torque allocation method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the distributed drive torque allocation program is called can be referred to in various embodiments of the distributed drive torque allocation method of this application, and will not be repeated here.

[0135] Those skilled in the art will understand that Figure 3 The hardware structure shown does not constitute a limitation of this application and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0136] Fifthly, embodiments of this application also provide a computer-readable storage medium.

[0137] The present application has a computer-readable storage medium storing a distributed drive torque allocation program, wherein when the distributed drive torque allocation program is executed by a processor, it implements the steps of the distributed drive torque allocation method as described above.

[0138] The method implemented when the distributed drive torque distribution program is executed can be referred to in various embodiments of the distributed drive torque distribution method of this application, and will not be repeated here.

[0139] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0140] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0141] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0142] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0143] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0144] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0145] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A distributed drive torque distribution method, characterized in that, The distributed drive torque distribution method includes: Within the current control cycle, based on the formula for calculating the road surface adhesion utilization rate of wheel i, the road surface adhesion utilization rate of each wheel at the current moment is calculated, and the wheel with the highest road surface adhesion utilization rate among all wheels is determined as wheel j. An optimization objective with constraints is constructed, wherein the optimization objective includes a first optimization objective, a second optimization objective, and a third optimization objective, and the first optimization objective is the optimized value of the road surface adhesion utilization rate of wheel j. With penalty items The second optimization objective is to minimize the sum of the average and standard deviation of the road adhesion utilization rates of each wheel; the third optimization objective is to minimize the square of the difference between the yaw moment generated by the tire force and the desired yaw moment. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j. The constraints include inequality constraints: in, This is the optimized value for the road surface adhesion utilization rate of wheel i; The constrained optimization objective is solved to obtain the target longitudinal driving force of each wheel. Based on the target longitudinal driving force of each wheel, the output driving torque of each motor corresponding to each wheel is controlled.

2. The distributed drive torque distribution method as described in claim 1, characterized in that, The formula for calculating the road surface adhesion utilization rate of a wheel is: in, For the road surface adhesion utilization rate of wheel i, The longitudinal driving force of wheel i, Let be the coefficient of adhesion of the road surface where wheel i is located. Let be the vertical load on wheel i.

3. The distributed drive torque distribution method as described in claim 1, characterized in that, The wheels include the left front wheel, right front wheel, left rear wheel, and right rear wheel. The formula for calculating the yaw moment caused by the tire forces is: in, The yaw moment is caused by the tire force. For the longitudinal driving force of the left front wheel, For the longitudinal driving force of the right front wheel, For the longitudinal driving force of the left rear wheel, For the longitudinal driving force of the right rear wheel, The steering angle of the vehicle's front wheels. The track width between the left and right wheels. This is the distance from the vehicle's center of gravity to the front axle.

4. The distributed drive torque distribution method as described in claim 1, characterized in that, The constraints include each wheel being limited by the motor speed-torque external characteristic curve.

5. The distributed drive torque distribution method as described in claim 1, characterized in that, The constraints include the tire force of each wheel being located within the friction circle.

6. The distributed drive torque distribution method as described in claim 1, characterized in that, The constraints include ensuring that the vehicle longitudinal force, obtained by combining the target longitudinal driving forces of each wheel, meets the target longitudinal force requirement.

7. A distributed drive torque distribution device, characterized in that, The distributed drive torque distribution device includes: The solution module is used to calculate the road adhesion utilization rate of each wheel at the current moment within the current control cycle, based on the calculation formula of the road adhesion utilization rate of wheel i, and to determine the wheel with the highest road adhesion utilization rate as wheel j. It also solves for the constrained optimization objectives to obtain the target longitudinal driving force of each wheel. The optimization objectives include a first optimization objective, a second optimization objective, and a third optimization objective, where the first optimization objective is the optimized value of the road adhesion utilization rate of wheel j. With penalty items The second optimization objective is to minimize the sum of the average and standard deviation of the road adhesion utilization rates of each wheel; the third optimization objective is to minimize the square of the difference between the yaw moment generated by the tire force and the desired yaw moment. The penalty coefficient is... Let i be the slack variable corresponding to wheel i, where wheel i is any wheel other than wheel j. The constraints include inequality constraints: in, This is the optimized value for the road surface adhesion utilization rate of wheel i; The control module is used to control the output driving torque of each motor corresponding to each wheel based on the target longitudinal driving force of each wheel.

8. A vehicle, characterized in that, The vehicle includes the distributed drive torque distribution device as described in claim 7.

9. A distributed drive torque distribution device, characterized in that, The distributed drive torque distribution device includes a processor, a memory, and a distributed drive torque distribution program stored in the memory and executable by the processor, wherein when the distributed drive torque distribution program is executed by the processor, it implements the steps of the distributed drive torque distribution method as described in claim 1.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a distributed drive torque allocation program, wherein when the distributed drive torque allocation program is executed by a processor, it implements the steps of the distributed drive torque allocation method as described in claim 1.

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