A method for controlling wheel transmission instability power redistribution in automobiles

Abstract

The present invention provides a power redistribution control method for wheel transmission instability of an automobile, which specifically includes the following steps: step S1, obtaining vehicle operation data through high-precision sensors, the vehicle operation data including vehicle operation status data and vehicle surrounding environment data, the high-precision sensors including wheel speed sensors, acceleration sensors, gyroscopes, environment perception cameras and radars; step S2, analyzing the vehicle operation data to identify early signs of wheel instability; step S3, when it is identified that a wheel has an instability risk, starting a dynamic power redistribution mechanism to optimize the torque output of each wheel and correct the instability; step S4, comprehensively considering the control objectives of wheel slip rate, lateral stability and trajectory tracking capability, using a multi-objective optimization algorithm to balance conflicts between the objectives and obtain an optimal power distribution plan.

Description

Technical Field

[0001] The present invention relates to the field of automobile control, and in particular to a power redistribution control method for automobile wheel transmission instability. Background Art

[0002] With the rapid development of electric vehicle technology, requirements for EV range, power performance, and driving safety are increasing. However, during driving, especially under complex and changing road conditions, the wheel drive system of electric vehicles often faces the risk of instability. This instability can be caused by a variety of factors, such as uneven road surfaces, tire wear, and improper drive motor control. These factors can lead to wheel slippage, skidding, or even loss of control, seriously compromising vehicle stability and safety.

[0003] Traditional wheel drive control strategies often focus on optimizing a single objective, such as wheel slip control or trajectory tracking, while ignoring the interplay and constraints of other control objectives. This single-objective optimization approach often fails to meet the comprehensive performance requirements of electric vehicles under complex operating conditions and may even lead to vehicle loss of control or accidents in certain situations.

[0004] Furthermore, electric vehicle wheel drive systems face the risk of sensor and actuator failure. Sensor failure can prevent the vehicle from accurately perceiving its surroundings and its own status, while actuator failure can affect power output and response speed. These failures can severely impact vehicle stability and safety, particularly at high speeds or in emergency situations.

[0005] Therefore, to improve the wheel transmission stability and safety of electric vehicles, it is necessary to develop a power redistribution control strategy that comprehensively considers multiple control objectives. This strategy should be able to monitor vehicle status and environmental changes in real time and dynamically adjust the torque output of each wheel to correct instability and maintain vehicle stability. Furthermore, this strategy should include fault diagnosis and fault-tolerant control capabilities, automatically adjusting the control strategy in the event of sensor or actuator failure to ensure safe and stable vehicle operation. To this end, a power redistribution control strategy for wheel transmission instability in electric vehicles is proposed. Summary of the Invention

[0006] The main purpose of the present invention is to provide a method for controlling power redistribution in the event of instability in the wheel transmission of an automobile, which is used to redistribute power when the automobile is in an unstable state to ensure safe and stable operation of the vehicle.

[0007] To achieve the above objectives, the present invention adopts a technical solution: a method for controlling power redistribution in case of wheel transmission instability in an automobile, characterized in that it specifically comprises the following steps:

[0008] Step S1: acquiring vehicle operation data through high-precision sensors, wherein the vehicle operation data includes vehicle operation status data and vehicle surrounding environment data. The high-precision sensors include wheel speed sensors, acceleration sensors, gyroscopes, environment perception cameras, and radars.

[0009] Step S2: analyzing the vehicle operation data to identify early signs of wheel instability;

[0010] Step S3: When a wheel is identified as having an instability risk, a dynamic power redistribution mechanism is activated to optimize the torque output of each wheel and correct the instability;

[0011] Step S4: Comprehensively consider the control objectives of wheel slip rate, lateral stability, and trajectory tracking ability, use a multi-objective optimization algorithm to balance the conflicts between the objectives, and obtain the optimal power distribution plan.

[0012] Preferably, step S3 specifically includes the following steps:

[0013] Step S301: Define the vehicle state vector X = [x, y, θ, v, ω] T , where x and y represent the position of the vehicle's center of mass in the global coordinate system, θ represents the vehicle's heading angle, v represents the vehicle's speed, and ω represents the yaw rate;

[0014] Step S302: Define the control input vector U = [T_lf, T_rf, T_lr, T_rr] T , where T_lf, T_rf, T_lr, and T_rr represent the driving torques of the left front, right front, left rear, and right rear wheels, respectively;

[0015] Step S303: Establish a state space equation X=f(X,U) based on the vehicle dynamics model, where f(X,U) represents the state transfer function of the vehicle dynamics model;

[0016] Step S304: When wheel transmission instability is detected, solve the following optimization problem to obtain the optimal control input U:

[0017]

[0018] The constraints are:

[0019] X=f(X,U),X(0)=X0,U min ≤U≤U max

[0020] Among them, X des is the desired vehicle state vector, X0 is the initial state vector, U prev is the control input of the previous moment, λ is the weight coefficient, W is the weight matrix, Umin and U max are the minimum and maximum values ​​of the control input respectively.

[0021] Preferably, in step S304, a sliding mode control SMC algorithm is used for solving the problem. The sliding mode control SMC algorithm uses a sliding mode surface in the following form:

[0022] s=c1e+c2e,

[0023] Where e represents the vehicle state error, c1 and c2 are positive constants used to adjust the convergence speed and stability of the sliding surface.

[0024] Preferably, the multi-objective optimization algorithm in step S4 specifically includes the following steps:

[0025] Step S401: Determine the control targets of wheel slip rate control, lateral stability control, and trajectory tracking ability control, and establish corresponding objective functions respectively. Let each objective function be J i (U), i=1,2,...,n;

[0026] Step S402: standardize the objective function;

[0027] Step S403: Using a weighted sum method, multiple standardized objective functions are combined into a comprehensive objective function:

[0028]

[0029] Among them, J(U) is the comprehensive objective function, ω is the weight coefficient of each control objective, and it satisfies

[0030] Step S404: Use the gradient descent method or Newton's method to solve the minimum value of J(U) to obtain the optimal control input U.

[0031] Preferably, the method further includes: step S6, a fault diagnosis and fault-tolerant control method, wherein step S6 specifically includes the following steps:

[0032] Step S601: using redundant sensor information, data verification, and threshold judgment methods to monitor the working status of the sensor in real time and diagnose whether the high-precision sensor has a fault;

[0033] Step S602: Determine whether the actuator has failed or its performance has degraded by monitoring the actuator's response speed and output torque parameters;

[0034] Step S603: When a high-precision sensor or actuator fault is diagnosed, the fault handling strategy is immediately initiated:

[0035] If a high-precision sensor fails, redundant sensor data replacement, estimated value replacement, or faulty sensor isolation is used;

[0036] If an actuator fails, the backup actuator can be switched, the control strategy can be adjusted, or the performance requirements can be reduced.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1) By integrating high-precision sensors and monitoring the vehicle's operating status in real time, the present invention can quickly identify early signs of wheel drive instability, immediately activate the dynamic power redistribution mechanism, and accurately calculate and optimize the torque output of each wheel, effectively correcting the instability and preventing the vehicle from slipping, sliding, or losing control, thereby significantly improving the driving stability and safety of electric vehicles in complex operating conditions.

[0039] 2) This invention utilizes a multi-objective optimization algorithm, comprehensively considering the control objectives of wheel slip rate, lateral stability, and trajectory tracking capability, and solves for the optimal control input through a weighted sum method. It also features fault diagnosis and fault-tolerant control capabilities, enabling real-time monitoring of the operating status of sensors and actuators. Upon detection of a fault, it immediately initiates a fault-handling strategy and adjusts the parameters and models within the control strategy. This ensures stable vehicle operation in the event of a sensor or actuator failure, reducing safety risks associated with such failures and improving vehicle reliability and durability. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0042] A method for controlling power redistribution in case of wheel transmission instability in an automobile comprises the following steps:

[0043] Step S1: acquiring vehicle operation data through high-precision sensors, wherein the vehicle operation data includes vehicle operation status data and vehicle surrounding environment data. The high-precision sensors include wheel speed sensors, acceleration sensors, gyroscopes, environment perception cameras, and radars.

[0044] Step S2: analyzing the vehicle operation data to identify early signs of wheel instability;

[0045] Step S3: When a wheel is identified as having an instability risk, a dynamic power redistribution mechanism is activated to optimize the torque output of each wheel and correct the instability;

[0046] Step S4: comprehensively considering the control objectives of wheel slip rate, lateral stability, and trajectory tracking capability, using a multi-objective optimization algorithm to balance the conflicts between the objectives and obtain the optimal power distribution plan;

[0047] Step S5: Based on the actual vehicle operation data, the control parameters and algorithm model are continuously optimized using an adaptive algorithm or a reinforcement learning algorithm to improve the adaptability and effectiveness of the control strategy.

[0048] The step S3 specifically includes the following steps:

[0049] Step S301: Define the vehicle state vector X = [x, y, θ, v, ω] T , where x and y represent the position of the vehicle's center of mass in the global coordinate system, θ represents the vehicle's heading angle, v represents the vehicle's speed, and ω represents the yaw rate;

[0050] Step S302: Define the control input vector U = [T_lf, T_rf, T_lr, T_rr] T , where T_lf, T_rf, T_lr, and T_rr represent the driving torques of the left front, right front, left rear, and right rear wheels, respectively;

[0051] Step S303: Establish a state space equation X=f(X,U) based on the vehicle dynamics model, where f(X,U) represents the state transfer function of the vehicle dynamics model;

[0052] Step S304: When wheel transmission instability is detected, the SMC or MPC algorithm is used to solve the following optimization problem to obtain the optimal control input U:

[0053]

[0054] The constraints are:

[0055] X=f(X,U),X(0)=X0,U min ≤U≤U max

[0056] Among them, X des is the desired vehicle state vector, X0 is the initial state vector, U prev is the control input of the previous moment, λ is the weight coefficient, W is the weight matrix, U min and U max are the minimum and maximum values ​​of the control input respectively.

[0057] The sliding mode control SMC algorithm uses the following sliding mode surface:

[0058] s=c1e+c2e,

[0059] Where e represents the vehicle state error, c1 and c2 are positive constants used to adjust the convergence speed and stability of the sliding surface.

[0060] The multi-objective optimization algorithm in step S4 specifically includes the following steps:

[0061] Step S401: Determine the control targets of wheel slip rate control, lateral stability control, and trajectory tracking ability control, and establish corresponding objective functions respectively. Let each objective function be J i (U), i=1,2,...,n, n is the number of control targets; where the objective function J i (U) Using the Min-max normalization function type in the prior art;

[0062] Step S402: Standardize the objective function. Since the dimensions and importance of each control objective are different, each objective function needs to be standardized to make it comparable.

[0063] Step S403: Using a weighted sum method, multiple standardized objective functions are combined into a comprehensive objective function:

[0064]

[0065] Among them, J(U) is the comprehensive objective function, ω is the weight coefficient of each control objective, and it satisfies

[0066] Step S404: Use the gradient descent method or Newton's method to solve the minimum value of J(U) to obtain the optimal control input U.

[0067] Preferably, the wheel transmission instability power redistribution control method further includes: step S6, a fault diagnosis and fault tolerance control method, wherein step S6 specifically includes the following steps:

[0068] Step S601: using redundant sensor information, data verification, and threshold judgment methods to monitor the working status of the sensor in real time and diagnose whether the high-precision sensor has a fault;

[0069] Step S602: Determine whether the actuator has failed or its performance has degraded by monitoring the actuator's response speed and output torque parameters;

[0070] Step S603: When a high-precision sensor or actuator fault is diagnosed, the fault handling strategy is immediately initiated:

[0071] If a high-precision sensor fails, redundant sensor data replacement, estimated value replacement, or faulty sensor isolation is used;

[0072] If an actuator fails, use a backup actuator switch, adjust the control strategy, or reduce performance requirements;

[0073] Step S604: Based on the fault handling, the parameters and models in the control strategy are adjusted to adapt to the vehicle dynamic characteristics after the fault. By monitoring the vehicle status and control effect in real time, the control strategy is continuously optimized to ensure that the vehicle can still operate safely and stably in the event of a fault.

[0074] The fault diagnosis and fault-tolerant control mechanism also includes fault alarm and recording steps, which record the fault diagnosis results and fault-tolerant control process, trigger the fault alarm mechanism, and promptly notify the driver or maintenance personnel for processing. At the same time, the fault data and fault-tolerant control experience are accumulated to optimize future fault diagnosis and fault-tolerant control strategies.

[0075] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling wheel transmission instability power redistribution for an automobile, characterized in that: The specific steps include: Step S1: acquiring vehicle operation data through high-precision sensors, wherein the vehicle operation data includes vehicle operation status data and vehicle surrounding environment data. The high-precision sensors include wheel speed sensors, acceleration sensors, gyroscopes, environment perception cameras, and radars. Step S2: analyzing the vehicle operation data to identify early signs of wheel instability; Step S3: When a wheel is identified as having an instability risk, a dynamic power redistribution mechanism is activated to optimize the torque output of each wheel and correct the instability; Step S4: comprehensively considering the control objectives of wheel slip rate, lateral stability, and trajectory tracking capability, using a multi-objective optimization algorithm to balance the conflicts between the objectives and obtain the optimal power distribution plan; The step S3 specifically includes the following steps: Step S301: Define the vehicle state vector X = [x, y, θ, v, ω] T , where x and y represent the position of the vehicle's center of mass in the global coordinate system, θ represents the vehicle's heading angle, v represents the vehicle's speed, and ω represents the yaw rate; Step S302: Define the control input vector U = [T_lf, T_rf, T_lr, T_rr] T , where T_lf, T_rf, T_lr, and T_rr represent the driving torques of the left front, right front, left rear, and right rear wheels, respectively; Step S303: Establish a state space equation X=f(X,U) based on the vehicle dynamics model, where f(X,U) represents the state transfer function of the vehicle dynamics model; Step S304: When wheel transmission instability is detected, solve the following optimization problem to obtain the optimal control input U: The constraints are: X=f(X,U),X(0)=X0,U min ≤U≤U max Among them, X des is the desired vehicle state vector, X0 is the initial state vector, U prev is the control input of the previous moment, λ is the weight coefficient, W is the weight matrix, U min and U max are the minimum and maximum values ​​of the control input respectively.

2. The method for controlling wheel transmission instability power redistribution for an automobile according to claim 1, characterized in that: In step S304, a sliding mode control SMC algorithm is used to solve the problem. The sliding mode control SMC algorithm uses a sliding surface in the following form: s=c1e+c2e, Where e represents the vehicle state error, c1 and c2 are positive constants used to adjust the convergence speed and stability of the sliding surface.

3. The method for controlling wheel transmission instability power redistribution for an automobile according to claim 1, characterized in that: The multi-objective optimization algorithm in step S4 specifically includes the following steps: Step S401: Determine the control targets of wheel slip rate control, lateral stability control, and trajectory tracking ability control, and establish corresponding objective functions respectively. Let each objective function be J i (U), i=1,2,...,n; Step S402: standardize the objective function; Step S403: Using a weighted sum method, multiple standardized objective functions are combined into a comprehensive objective function: Among them, J(U) is the comprehensive objective function, ω is the weight coefficient of each control objective, and it satisfies Step S404: Use the gradient descent method or Newton's method to solve the minimum value of J(U) to obtain the optimal control input U.

4. The method for controlling wheel transmission instability power redistribution for an automobile according to claim 1, characterized in that: The method further includes: step S6, a fault diagnosis and fault-tolerant control method, wherein step S6 specifically includes the following steps: Step S601: using redundant sensor information, data verification, and threshold judgment methods to monitor the working status of the sensor in real time and diagnose whether the high-precision sensor has a fault; Step S602: Determine whether the actuator has failed or its performance has degraded by monitoring the actuator's response speed and output torque parameters; Step S603: When a high-precision sensor or actuator fault is diagnosed, the fault handling strategy is immediately initiated: If a high-precision sensor fails, redundant sensor data replacement, estimated value replacement, or faulty sensor isolation is used; If an actuator fails, the backup actuator can be switched, the control strategy can be adjusted, or the performance requirements can be reduced.

Images