Embodiments of the present disclosure provide an EMB failure control method, device, platform, medium and program product.

Abstract

The application discloses an EMB failure control method, device, platform, medium and program product. The method comprises the following steps: acquiring vehicle state data; the vehicle state data comprises feedback braking force of a plurality of EMB actuators, vehicle body longitudinal acceleration, vehicle body mass center side slip angle and vehicle body yaw rate; determining whether there is a first EMB actuator that fails according to the feedback braking force of the plurality of EMB actuators; if there is, determining the effective braking force of the first EMB actuator according to the total vehicle braking force determined by the vehicle body longitudinal acceleration and the feedback braking force of a second EMB actuator; solving the optimization problem of the prediction model of the MPC in the rolling time domain according to the effective braking force, the vehicle body mass center side slip angle and the vehicle body yaw rate; the optimization problem is constructed based on the total vehicle braking force, the expected yaw rate and the expected mass center side slip angle; and determining the braking force distributed to the second EMB actuator and the target turning angle of the rear wheel turning actuator in the plurality of actuators according to the solving result.

Description

Technical Field

[0001] This application relates to the field of automotive chassis integrated control technology, and in particular to an EMB failure control method, device, platform, medium and program product. Background Technology

[0002] With the development of automotive drive-by-wire technology, EMB (Electro-Mechanical Brake) is gradually replacing traditional hydraulic braking systems due to its advantages such as fast response, compact structure, and ease of integration. EMB systems typically have an independent actuator for each wheel, achieving complete decoupling and precise control of braking. However, this distributed architecture also introduces the risk of single-point failure. When an EMB actuator fails due to mechanical, electrical, or control software malfunctions (such as failing to provide braking force or outputting abnormal braking force), it can lead to an imbalance of braking force between the left and right sides of the vehicle, generating unexpected yaw moments and seriously threatening the vehicle's driving stability.

[0003] Therefore, there is an urgent need for a solution that can effectively control single-point failures in EMB. Summary of the Invention

[0004] This application provides an EMB failure control method, apparatus, platform, medium, and program product.

[0005] Firstly, this application provides an EMB failure control method, which includes: Acquire vehicle status data; vehicle status data includes feedback braking force of multiple EMB actuators among multiple actuators, longitudinal acceleration of the vehicle body, sideslip angle of the vehicle center of gravity, and yaw rate of the vehicle body. The presence of a failed first EMB actuator is determined based on the feedback braking force from multiple EMB actuators. If it exists, the effective braking force of the first EMB actuator is determined based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among multiple EMB actuators. The optimization problem of the prediction model of MPC is solved in the rolling time domain based on the effective braking force, the vehicle center of gravity sideslip angle, and the vehicle yaw rate. The optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate, and the desired center of gravity sideslip angle. Based on the solution results, determine the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators.

[0006] Optionally, if the vehicle status data also includes actuator diagnostic messages, then determining whether there is a failed first EMB actuator based on the feedback braking force of multiple EMB actuators includes: Calculate the difference between the target braking force and the feedback braking force for each EMB actuator; If the difference detected by the first EMB actuator is greater than or equal to the first threshold, the timer is reset to zero. If the difference detected by the first EMB actuator is less than the first threshold, the timing is increased; If the timing reaches the second threshold, the first EMB actuator is determined to have failed. If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to have failed; otherwise, the first EMB actuator is confirmed to have not failed.

[0007] Optionally, the effective braking force of the first EMB actuator is determined based on the total braking force of the vehicle determined by the vehicle's longitudinal acceleration and the feedback braking force of the second EMB actuator among multiple EMB actuators, including: Estimate the total braking force of the vehicle based on the longitudinal acceleration of the vehicle body; The estimated braking force of the first EMB actuator is determined based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among multiple EMB actuators. The effective braking force of the first EMB actuator is determined by comparing the estimated braking force with the feedback braking force recorded last before the failure of the first EMB actuator.

[0008] Optionally, the effective braking force of the first EMB actuator is determined based on a comparison between the estimated braking force and the feedback braking force last recorded before the failure of the first EMB actuator, including: Determine the estimated braking force The feedback braking force last recorded before the failure of the first EMB actuator The difference between them; If the difference is less than or equal to the third threshold, then feedback braking force will be applied. As the effective braking force of the first EMB actuator ; If the difference is greater than the third threshold, then the estimated braking force value will be... As the effective braking force of the first EMB actuator .

[0009] Optionally, based on the effective braking force, the sideslip angle of the vehicle's center of gravity, and the vehicle's yaw rate, the optimization problem of the prediction model for MPC is solved in the rolling time domain, including: The optimization problem of constructing a prediction model for MPC is centered on the total braking force of the vehicle, the desired yaw rate, and the desired sideslip angle of the center of gravity as the tracking targets. In each control cycle, based on the effective braking force, the sideslip angle of the vehicle's center of gravity, and the vehicle's yaw rate, the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain is solved. Based on the solution results, the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined, including: The braking force assigned to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined based on the first control variable in the optimal control sequence.

[0010] Optionally, if the first EMB actuator of wheel fl fails, then in each control cycle, based on the effective braking force, the vehicle body center of gravity sideslip angle, and the vehicle body yaw rate, the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain is solved, including: In each control cycle, the currently acquired vehicle yaw rate and vehicle center of gravity sideslip angle are used as the predicted initial state, and the external disturbance inputs are set within a preset step size. Remain unchanged; Under the constraints of the optimization problem, the minimum value of the multi-objective optimization function J within the next N prediction steps is obtained to get the optimal control sequence; where the disturbance input... Including the effective braking force of the first EMB actuator of the first wheel configuration and / or the front axle steering angle. The boundaries of the constraints include the maximum braking force of each wheel. and / or maximum steering angle .

[0011] Optionally, if the first EMB actuator configured on the fl wheel of the vehicle fails, the prediction model for MPC is determined based on the following steps: Constructing a dynamic model:

[0012] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. The yaw rate of the vehicle body; This is the acceleration due to the yaw of the vehicle body; The sideslip angle is the angle between the vehicle's center of gravity and its body. The sideslip angular velocity of the vehicle's center of gravity; , These are the front and rear axle lateral stiffness, respectively. , These are the front and rear axle rotation angles, respectively. Let Z be the moment of inertia of the vehicle about the z-axis; , These are the distances from the front and rear axles to the center of mass, respectively. 1 represents the wheelbase; Feedback braking force of the EMB actuator configured for the fr wheel; Effective braking force of the EMB actuator configured for wheel fl; Feedback braking force of the EMB actuator configured for the rr wheel; Feedback braking force of the EMB actuator configured for the rl wheel; by The dynamic model is transformed into a state-space model in matrix form: To build a predictive model for MPC:

[0013] in, For state variables; For control variables; Interference input Including front axle steering angle and the effective braking force of the first EMB actuator ; The rate of change of state; The state matrix; For control matrix; This is the interference matrix.

[0014] Optionally, the formula for the multi-objective optimization function of the optimization problem is:

[0015] Where N is the prediction time domain length; These are the weighting coefficients for the stability term; To control the weighting coefficients of the incremental terms; The tracking weight for the total braking force; Predicted total braking force provided for all second EMB actuators; For the expected total braking force; , and These are the desired yaw rate and the desired sideslip angle of the center of mass, respectively. Let K be the state variable for the k-th control cycle. For the control variable in the k-th control cycle; T stands for transpose; And / or, The constraints of the optimization problem include EMB actuator constraints and / or braking force constraints: Among them, the rear wheel steering angle constraint is set to not exceed the mechanical limit angle of the rear wheel steering actuator; Braking force constraints are determined based on the following steps: In the initial state, the upper limit of braking force of each EMB actuator in the second EMB actuator is set to its own physical limit value; During the operation of the control cycle, when it is detected that the target EMB actuator in the second EMB actuator triggers ABS anti-lock braking control after performing the target braking force, the upper limit of the braking force of the target EMB actuator will be updated to the actual braking force value corresponding to the activation time of ABS anti-lock braking control in the next control cycle.

[0016] Optionally, the EMB failure control method further includes: The desired yaw rate was calculated using a two-degree-of-freedom vehicle model. Desired centroid side slip angle :

[0017]

[0018] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. , These are the distances from the front and rear axles to the center of mass, respectively. This refers to the wheelbase; Front axle steering angle; , These are the front and rear axle lateral stiffness, respectively.

[0019] Optionally, the vehicle body center of gravity sideslip angle is calculated based on the following formula:

[0020] in, , These refer to longitudinal and lateral vehicle speeds, respectively. To Integrate over t; The derivative of t; This refers to the lateral acceleration of the vehicle body. t represents time.

[0021] Secondly, this application provides an EMB failure control method applied to an intelligent vehicle platform, which includes an electronic control unit, multiple EMB actuators, and a rear wheel steering actuator; wherein the electronic control unit is used to execute the EMB failure control method described in the first aspect.

[0022] Thirdly, this application provides an EMB failure control device, which includes: The data input module is used to acquire vehicle status data; the vehicle status data includes the feedback braking force of multiple EMB actuators among multiple actuators, the longitudinal acceleration of the vehicle body, the sideslip angle of the vehicle center of gravity, and the yaw rate of the vehicle body; The actuator failure detection module is used to determine whether there is a failed first EMB actuator based on the feedback braking force of multiple EMB actuators. The braking force determination module is used to determine the effective braking force of the first EMB actuator, if present, based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among multiple EMB actuators. The solution module is used to solve the optimization problem of the prediction model of MPC in the rolling time domain based on the effective braking force, the vehicle center of gravity sideslip angle, and the vehicle yaw rate; the optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate, and the desired center of gravity sideslip angle. The allocation module is used to determine the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among multiple actuators based on the solution results.

[0023] Optionally, if the vehicle status data also includes actuator diagnostic messages, the actuator failure detection module is further configured to: Calculate the difference between the target braking force and the feedback braking force for each EMB actuator; If the difference detected by the first EMB actuator is greater than or equal to the first threshold, the timer is reset to zero. If the difference detected by the first EMB actuator is less than the first threshold, the timing is increased; If the timing reaches the second threshold, the first EMB actuator is determined to have failed. If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to have failed; otherwise, the first EMB actuator is confirmed to have not failed.

[0024] Optionally, the braking force determination module includes: The first estimation unit is used to estimate the total braking force of the vehicle based on the longitudinal acceleration of the vehicle body. The second estimation unit is used to determine the estimated braking force of the first EMB actuator based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among multiple EMB actuators. The braking force determination unit is used to determine the effective braking force of the first EMB actuator based on the comparison between the estimated braking force value and the feedback braking force last recorded before the failure of the first EMB actuator.

[0025] Optionally, the braking force determining unit is further used for: Determine the estimated braking force The feedback braking force last recorded before the failure of the first EMB actuator The difference between them; If the difference is less than or equal to the third threshold, then feedback braking force will be applied. As the effective braking force of the first EMB actuator ; If the difference is greater than the third threshold, then the estimated braking force value will be... As the effective braking force of the first EMB actuator .

[0026] Optionally, the solver module includes: The building unit is used to construct an optimization problem of the prediction model of MPC with the total braking force of the vehicle, the desired yaw rate and the desired center of gravity sideslip angle as the tracking targets. The solution unit is used to solve for the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain, based on the effective braking force, the sideslip angle of the vehicle center of gravity, and the yaw rate of the vehicle in each control cycle. The allocation module is further used for: The braking force assigned to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined based on the first control variable in the optimal control sequence.

[0027] Optionally, if the first EMB actuator configured on wheel fl fails, the solution unit is further configured to: In each control cycle, the currently acquired vehicle yaw rate and vehicle center of gravity sideslip angle are used as the predicted initial state, and the external disturbance inputs are set within a preset step size. Remain unchanged; Under the constraints of the optimization problem, the minimum value of the multi-objective optimization function J of the optimization problem within the next N prediction steps is obtained to obtain the optimal control sequence; Among them, interference input Including the effective braking force of the first EMB actuator of the first wheel configuration and / or the front axle steering angle. The boundaries of the constraints include the maximum braking force of each wheel. and / or maximum steering angle .

[0028] Optionally, if the first EMB actuator configured on the fl wheel of the vehicle fails, the prediction model for MPC is determined based on the following steps: Constructing a dynamic model:

[0029] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. The yaw rate of the vehicle body; This is the acceleration due to the yaw of the vehicle body; The sideslip angle is the angle between the vehicle's center of gravity and its body. The sideslip angular velocity of the vehicle's center of gravity; , These are the front and rear axle lateral stiffness, respectively. , These are the front and rear axle rotation angles, respectively. Let Z be the moment of inertia of the vehicle about the z-axis; , These are the distances from the front and rear axles to the center of mass, respectively. 1 represents the wheelbase; Feedback braking force of the EMB actuator configured for the fr wheel; Effective braking force of the EMB actuator configured for wheel fl; Feedback braking force of the EMB actuator configured for the rr wheel; Feedback braking force of the EMB actuator configured for the rl wheel; by The dynamic model is transformed into a state-space model in matrix form: To build a predictive model for MPC:

[0030] in, For state variables; The sideslip angle is the angle between the vehicle's center of gravity and its body. The yaw rate of the vehicle body; For control variables; The rear wheel steering angle; Interference input Including the front axle steering angle controlled by the driver and the effective braking force of the first EMB actuator ; The rate of change of state; The state matrix; For control matrix; This is the interference matrix.

[0031] Optionally, the formula for the multi-objective optimization function of the optimization problem is:

[0032] Where N is the prediction time domain length; These are the weighting coefficients for the stability term; To control the weighting coefficients of the incremental terms; The tracking weight for the total braking force; Predicted total braking force provided for all second EMB actuators; For the expected total braking force; , and These are the desired yaw rate and the desired sideslip angle of the center of mass, respectively. Let K be the state variable for the k-th control cycle. Here, T represents the control variable for the k-th control cycle; T is the transpose. And / or, The constraints of the optimization problem include EMB actuator constraints and / or braking force constraints: Among them, the rear wheel steering angle constraint is set to not exceed the mechanical limit angle of the rear wheel steering actuator; Braking force constraints are determined based on the following steps: In the initial state, the upper limit of braking force of each EMB actuator in the second EMB actuator is set to its own physical limit value; During the operation of the control cycle, when it is detected that the target EMB actuator in the second EMB actuator triggers ABS anti-lock braking control after performing the target braking force, the upper limit of the braking force of the target EMB actuator will be updated to the actual braking force value corresponding to the activation time of ABS anti-lock braking control in the next control cycle.

[0033] Optionally, the EMB failure control device further includes: The estimation module is used to calculate the desired yaw rate using a two-degree-of-freedom vehicle model. Desired centroid side slip angle :

[0034]

[0035] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. , These are the distances from the front and rear axles to the center of mass, respectively. This refers to the wheelbase; Front axle steering angle; , These are the front and rear axle lateral stiffness, respectively.

[0036] Optionally, the vehicle body center of gravity sideslip angle is calculated based on the following formula:

[0037] in, , These refer to longitudinal and lateral vehicle speeds, respectively. To Integrate over t; The derivative of t; Let t be the lateral acceleration of the vehicle body, and t be the time.

[0038] Fourthly, this application provides an intelligent vehicle platform, including: an electronic control unit, a plurality of EMB actuators and a rear wheel steering actuator; wherein the electronic control platform is used to execute the EMB failure control method as described in either the first or second aspect.

[0039] Fifthly, this application provides a computer-readable storage medium storing computer instructions that, when executed by a computer, are used to perform an EMB failure control method as described in the first or second aspect.

[0040] In a sixth aspect, this application provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the EMB failure control method as described in the first or second aspect.

[0041] The technical solution of this application has the following technical advantages over the prior art: The EMB failure control method provided in this application acquires vehicle state data, including feedback braking force of multiple EMB actuators, vehicle longitudinal acceleration, vehicle center of gravity sideslip angle, and vehicle yaw rate. Then, based on the feedback braking force of the multiple EMB actuators, it determines whether a first EMB actuator has failed. When the first EMB actuator is determined to be failed, the effective braking force of the first EMB actuator is determined based on the total vehicle braking force determined by the vehicle longitudinal acceleration and the feedback braking force of the second EMB actuator among the multiple EMB actuators. Then, based on the effective braking force, vehicle center of gravity sideslip angle, and vehicle yaw rate, an optimization problem of the MPC prediction model is solved in the rolling time domain. The optimization problem is constructed based on the total vehicle braking force, the desired yaw rate, and the desired center of gravity sideslip angle. Finally, based on the solution results, the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined. When the failure of the first EMB actuator is determined, this application does not simply restrict the output of other normal EMBs. Instead, it dynamically adjusts the braking force distribution of the second EMB actuator by determining the effective braking force and solving the prediction model of the MPC, so that the total braking force of the vehicle can be as close as possible to the driver's expected request. This is especially crucial in emergency braking conditions, avoiding the dangerous situation of excessive braking distance or even complete braking failure due to brake failure, and fundamentally ensuring the longitudinal braking safety of the vehicle. In addition, based on braking control, a rear wheel steering actuator is introduced, and the rear wheel steering angle and braking force distribution are co-optimized using the prediction model of MPC. This can actively and accurately generate compensating yaw moment, effectively counteracting the disturbing yaw moment caused by the lack or abnormality of braking force in a single wheel. This allows the vehicle's body yaw rate and center of gravity sideslip angle to closely track the ideal values ​​under fault conditions, greatly improving the vehicle's handling stability and directional controllability. Attached Figure Description

[0042] The preferred embodiments of this application will be described in detail below with reference to the accompanying drawings, which will help to understand the purpose and advantages of this application, wherein: Figure 1A flowchart of an EMB failure control method provided in an embodiment of this application; Figure 2 A schematic diagram illustrating an EMB failure as provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of vehicle status data provided in an embodiment of this application; Figure 4 A flowchart for fault detection of a failed actuator provided in an embodiment of this application; Figure 5 A flowchart of the method for confirming the braking force of a failed actuator provided in this application embodiment; Figure 6 A schematic diagram illustrating the principle of the cooperative control algorithm based on model predictive control provided in this application embodiment; Figure 7 A flowchart of an EMB failure control method provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an EMB failure control device provided in an embodiment of this application. Detailed Implementation

[0043] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0044] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0045] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0046] Furthermore, the technical features involved in the different embodiments of this application described below can be combined with each other as long as they do not conflict with each other.

[0047] With the development of automotive steer-by-wire technology, EMB (Electronic Braking Brake) is gradually replacing traditional hydraulic braking systems due to its advantages such as fast response, compact structure, and ease of integration. EMB systems typically have an independent actuator for each wheel, achieving complete decoupling and precise control of braking. However, this distributed architecture also introduces the risk of single-point failure. When an EMB actuator fails due to mechanical, electrical, or control software malfunctions (such as failing to provide braking force or outputting abnormal braking force), it can lead to an imbalance of braking force on the left and right sides of the vehicle, generating unexpected yaw moments and seriously threatening the vehicle's driving stability.

[0048] Existing control strategies for handling single-point EMB failures typically employ the following approach: once an EMB failure is detected, the output braking force of other functioning EMB actuators is immediately limited or reduced by a specific ratio. The aim is to avoid vehicle loss of control due to excessive braking force differences between the two sides by sacrificing some braking efficiency. For example, if the EMB on the front wheel fails, the braking force of the opposite front wheel and the diagonally opposite rear wheel will be limited accordingly to balance the yaw moment. However, existing control strategies have the following problems: Severe sacrifice in braking performance: Under emergency braking conditions, limiting the feedback braking force output of the normal EMB will result in a total braking force that is far lower than the driver's request, greatly extending the braking distance and potentially making it impossible to avoid rear-end collisions and other accidents, thus failing to meet basic braking safety requirements.

[0049] The control strategy is passive and rigid: simply limiting braking force is a "one-size-fits-all" passive defense strategy that fails to adapt to the actual dynamic state of the vehicle. It only considers avoiding instability, completely sacrificing braking performance, and fails to seek the optimal balance between the two.

[0050] Figure 1 The flowchart illustrates an EMB failure control method provided in this application embodiment, where the executing entity can be an electronic control unit. Figure 1 As shown, the EMB failure control method includes the following steps: Step 101: Obtain vehicle status data; vehicle status data includes feedback braking force of multiple EMB actuators among multiple actuators, longitudinal acceleration of the vehicle body, sideslip angle of the vehicle body center of gravity, and yaw rate of the vehicle body; Step 102: Determine whether there is a failed first EMB actuator based on the feedback braking force of multiple EMB actuators; Step 103: If it exists, then determine the effective braking force of the first EMB actuator based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among the multiple EMB actuators. Step 104: Based on the effective braking force, the vehicle center of gravity sideslip angle, and the vehicle yaw rate, solve the optimization problem of the MPC prediction model in the rolling time domain; the optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate, and the desired center of gravity sideslip angle. Step 105: Determine the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators based on the solution results.

[0051] The EMB failure control method provided in this application acquires vehicle state data, including feedback braking force of multiple EMB actuators, vehicle longitudinal acceleration, vehicle center of gravity sideslip angle, and vehicle yaw rate. Then, based on the feedback braking force of the multiple EMB actuators, it determines whether a first EMB actuator has failed. When the first EMB actuator is determined to be failed, the effective braking force of the first EMB actuator is determined based on the total vehicle braking force determined by the vehicle longitudinal acceleration and the feedback braking force of the second EMB actuator among the multiple EMB actuators. Then, based on the effective braking force, vehicle center of gravity sideslip angle, and vehicle yaw rate, an optimization problem of the MPC prediction model is solved in the rolling time domain. The optimization problem is constructed based on the total vehicle braking force, the desired yaw rate, and the desired center of gravity sideslip angle. Finally, based on the solution results, the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined. When the failure of the first EMB actuator is determined, this application does not simply restrict the output of other normal EMBs. Instead, it dynamically adjusts the braking force distribution of the second EMB actuator by determining the effective braking force and solving the prediction model of the MPC, so that the total braking force of the vehicle can be as close as possible to the driver's expected request. This is especially crucial in emergency braking conditions, avoiding the dangerous situation of excessive braking distance or even complete braking failure due to brake failure, and fundamentally ensuring the longitudinal braking safety of the vehicle. In addition, based on braking control, a rear wheel steering actuator is introduced, and the rear wheel steering angle and braking force distribution are co-optimized using the prediction model of MPC. This can actively and accurately generate compensating yaw moment, effectively counteracting the disturbing yaw moment caused by the lack or abnormality of braking force in a single wheel. This allows the vehicle's body yaw rate and center of gravity sideslip angle to closely track the ideal values ​​under fault conditions, greatly improving the vehicle's handling stability and directional controllability.

[0052] The EMB failure control method provided in this application is applicable to scenarios of EMB single-point failure: in this scenario, the vehicle may have at least two wheels, and is applicable to vehicles with at least two wheels, such as four-wheeled vehicles, six-wheeled vehicles, etc. Each wheel is equipped with an EMB actuator.

[0053] In the following text, the left front wheel of a four-wheeled vehicle (e.g.) Figure 2 The failure of the EMB actuator in the configuration of wheel fl shown is an example; the failure of the EMB actuators in the configurations of the other wheels can be deduced by analogy.

[0054] In addition to configuring EMB actuators on each wheel, this application also needs to incorporate the chassis cooperative control potential: that is, the vehicle also needs to be equipped with RWS (Rear Wheel Steering) actuators. RWS can directly generate compensating yaw moment by actively changing the rear wheel steering angle, so as to compensate for the differential torque generated by the failure of the EMB actuator configured on the left front wheel without changing (limiting or reducing) the feedback braking force of other normal EMB actuators, and still maintain the balance of the vehicle.

[0055] The EMB failure control method provided in this application controls the rear wheel steering angle to generate lateral force to compensate for the differential torque caused by the unbalanced braking due to the failure of the EMB actuator configured on the left front wheel. At the same time, it adjusts the braking force of other EMB actuators that have not failed to achieve a balance between stability and braking performance, thereby realizing the coordination between braking control and the rear wheel steering actuator and solving the contradiction between braking and stability.

[0056] In addition, in vehicle dynamics, clamping force is the normal pressure applied to the brake disc by the EMB actuator, while braking force is the tangential force that ultimately acts on the tire. The two are related through the coefficient of friction and the effective radius.

[0057] The following is a detailed description of step 101 (i.e., acquiring vehicle status data; the vehicle status data includes the feedback braking force of multiple EMB actuators among multiple actuators, the longitudinal acceleration of the vehicle body, the sideslip angle of the vehicle body center of gravity, and the yaw rate of the vehicle body).

[0058] In this step, the vehicle status data includes at least two of the following: real-time acquired data and estimated status data; status data based on actuator feedback; and status data from the ABS (Anti-lock Braking System) controller. The real-time acquired data can be obtained from various sensors, and the estimated status data can be estimated from data acquired by the sensors. The status data based on actuator feedback can be used to characterize the status data fed back by the EMB actuator during operation, and may include, but is not limited to, at least one of the following: feedback braking force and actuator diagnostic messages.

[0059] The feedback braking force can be used to characterize the actual braking force output by the EMB actuator. Actuator diagnostic messages can be used to report actuator fault conditions in message form.

[0060] exist Figure 3 In the process, vehicle status data includes: feedback braking force (e.g., to the EMB actuators configured for each of the four wheels) Figure 3 F in break ), diagnostic messages from the EMB underlying controller (such as Figure 3 The DiagMessage shown), the vehicle speed of the ABS controller (such as...) Figure 3 The Vx shown) and activation flag (such as Figure 3 The ABS Active and front axle steering angle shown are indicated. Vehicle yaw rate (YawRate), vehicle lateral acceleration (Ay), vehicle longitudinal acceleration (Ax), and the desired total braking force F obtained from the brake pedal opening collected by the pedal sensor. tag ,according to The desired centroid sideslip angle is obtained by estimating Ax (i.e., calculating the target value). and expected yaw rate The sideslip angle of the vehicle's center of gravity is estimated based on Vx and Ay. .

[0061] in, Ay is acquired by the angle sensor; Ay is acquired by the IMU (Inertial Measurement Unit).

[0062] In one example, for the vehicle's center of gravity sideslip angle It can be estimated using integration:

[0063] in, This refers to the longitudinal speed of the vehicle. This refers to the lateral speed. To Integrate over t; The derivative of t; t represents the lateral acceleration of the vehicle body; t represents time.

[0064] In one example, the EMB failure control method also includes: The desired yaw rate was calculated using a two-degree-of-freedom vehicle model. Desired centroid side slip angle :

[0065] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. This is the distance from the front axle to the center of gravity. This is the distance from the rear axle to the center of mass. This refers to the wheelbase; Front axle steering angle; For front axle lateral stiffness; This refers to the rear axle lateral stiffness.

[0066] It should also be noted that the multiple actuators in the embodiments of this application may include at least a steering actuator and an EMB actuator.

[0067] In addition, the aforementioned steering actuator can be a rear-wheel steering actuator, which is generally concentrated in the rear axle area of ​​the vehicle, for example, in the center of the rear subframe (rear axle assembly), near the steering knuckles (steering knuckles) of the left and right rear wheels, or on the tie rod assembly of the rear axle.

[0068] The following describes step 102 (i.e., determining whether there is a failed first EMB actuator based on the feedback braking force of multiple EMB actuators) in detail.

[0069] In this step, for each wheel's EMB actuator, the presence or absence of a failed first EMB actuator can be determined based on the feedback braking force of each wheel's EMB actuator and the corresponding first threshold.

[0070] Continuing from the previous text, the EMB actuator configured on the left front wheel is taken as the first EMB actuator.

[0071] Here, failure can refer to failure caused by mechanical, electrical, or control software malfunctions; for example, if the first EMB actuator fails to provide braking force or outputs abnormal braking force, it can be determined that the first EMB actuator is at risk of failure.

[0072] To more accurately detect whether the EMB actuator has failed, the actuator diagnostic message can also be used to determine whether the first EMB actuator has failed.

[0073] In one example, if the vehicle status data also includes actuator diagnostic messages, then step 102 may include: Calculate the difference between the target braking force and the feedback braking force for each EMB actuator; If the difference detected by the first EMB actuator is greater than or equal to the first threshold, the timer is reset to zero. If the difference detected by the first EMB actuator is less than the first threshold, the timing is increased; If the timing reaches the second threshold, the first EMB actuator is determined to have failed. If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to have failed; otherwise, the first EMB actuator is confirmed to have not failed.

[0074] In this example, single-point failure is detected through dual verification. If the absolute value of the difference between the target braking force and the actual feedback braking force of a certain EMB actuator is greater than a first threshold (which is related to the braking force control accuracy and response speed of the underlying controller of the EMB actuator) for a continuous period of time; or if the diagnostic message includes fault codes such as "motor overcurrent" or "communication interruption" for the first EMB actuator, then the first EMB actuator is determined to have failed.

[0075] Among them, dual verification is used to detect single-point failures, such as... Figure 4 As shown. In Figure 4 In this context, dual verification for detecting single-point failures includes the following steps: Step 1: Read the actuator fault message and feedback braking force (actual clamping force); The second step is to calculate the difference between the target braking force and the feedback braking force of each EMB actuator; if the difference is greater than the first threshold, proceed to the third step; if the difference is less than the first threshold, proceed to the fourth step. Following the previous text, the third or fourth step below can be determined based on the relationship between braking force and clamping force; alternatively, it can also be determined based on the difference between the expected clamping force and the feedback clamping force of each EMB actuator.

[0076] The third step is to reset the timer. Step 4: Increase the timer (continue timing); Fifth step: when the timer reaches the second threshold, the first EMB actuator is determined to have failed; Step 6: If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to be faulty; otherwise, the first EMB actuator is confirmed to be not faulty.

[0077] This application improves the system's reliability and fault tolerance: through a dual verification mechanism of "single-point failure detection" and "failure actuator braking force confirmation," it can quickly and accurately diagnose faults and assess the current braking state, providing reliable state input for subsequent MPC optimization control. This significantly enhances the robustness and reliability of the brake-by-wire system, increasing driver confidence in the event of a fault.

[0078] The following describes step 103 (i.e., if it exists, determine the effective braking force of the first EMB actuator based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among the multiple EMB actuators) in detail.

[0079] In this step, when the first EMB actuator fails, the total braking force of the vehicle is determined based on the vehicle's longitudinal acceleration; then, based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among the multiple EMB actuators, the effective braking force of the first EMB actuator is determined.

[0080] In one example, step 103 may include: Estimate the total braking force of the vehicle based on the longitudinal acceleration of the vehicle body; The estimated braking force of the first EMB actuator is determined based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among multiple EMB actuators. The effective braking force of the first EMB actuator is determined by comparing the estimated braking force with the feedback braking force recorded last before the failure of the first EMB actuator.

[0081] Following the previous text, using a four-wheeled vehicle as an example; multiple EMB actuators include a first EMB actuator and three second EMB actuators.

[0082] Optionally, in this example, the braking force estimate of the first EMB actuator is determined based on the following steps: exist Figure 5 In the middle, read the current longitudinal acceleration of the vehicle body. Vehicle quality and the feedback braking force of the three second EMB actuators. , , The normal braking force value fed back by the first EMB actuator at the last moment before the failure occurred. (That is, the feedback braking force last recorded before the first EMB actuator failed). According to Newton's second law, the estimated braking force of the first EMB actuator is calculated by subtracting the sum of the feedback braking forces of the three second EMB actuators from the total braking force of the entire vehicle: .in, It can be used as the total braking force for the entire vehicle.

[0083] Optionally, in this example, the effective braking force of the first EMB actuator is determined based on a comparison between the estimated braking force and the feedback braking force last recorded before the failure of the first EMB actuator, including: Determine the estimated braking force The feedback braking force last recorded before the failure of the first EMB actuator The difference between them; If the difference is less than or equal to the third threshold, then feedback braking force will be applied. As the effective braking force of the first EMB actuator ; If the difference is greater than the third threshold, then the estimated braking force value will be... As the effective braking force of the first EMB actuator .

[0084] exist Figure 5 Next, the reliability of the estimated braking force is assessed, specifically as follows: Calculate the difference Set a third threshold. This third threshold takes into account accelerometer noise and tire model error. If Then the estimated value of (braking force) is considered to be With memory value (i.e., This matches quite well, so we can use it directly. As the finally confirmed effective braking force Otherwise, considering the significant uncertainty in the estimation process, and based on the principle of safety and conservatism, the estimated value should be used first. As This is because acceleration better reflects the instantaneous dynamics of the vehicle. This step ensures that the system state data upon which the subsequent model predictive control (MPC) controller is based is accurate.

[0085] The following describes step 104 (i.e., solving the optimization problem of the prediction model of MPC in the rolling time domain based on the effective braking force, the body center of gravity sideslip angle and the body yaw rate; the optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate and the desired center of gravity sideslip angle) in detail.

[0086] In this step, an optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate, and the desired center of gravity sideslip angle. Then, based on the effective braking force, the center of gravity sideslip angle, and the vehicle yaw rate, the optimization problem of the prediction model of MPC (Model Predictive Control) is solved in the rolling time domain.

[0087] In one example, step 104 may include: The optimization problem of constructing a prediction model for MPC is centered on the total braking force of the vehicle, the desired yaw rate, and the desired sideslip angle of the center of gravity as the tracking targets. In each control cycle, based on the effective braking force, the sideslip angle of the vehicle's center of gravity, and the vehicle's yaw rate, the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain is solved. Based on the solution results, the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined, including: The braking force assigned to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined based on the first control variable in the optimal control sequence.

[0088] In this example, a prediction model incorporating rear-wheel steering and differential braking torque (i.e., the prediction model of MPC) is established. Using the total braking force of the vehicle, the desired yaw rate, and the desired sideslip angle as tracking targets, a multi-objective optimization function for the optimization problem is constructed. In each control cycle, the optimal control sequence that minimizes the multi-objective optimization function in the future time domain is solved in real time using the MPC algorithm. The braking force of the three second EMB actuators and the target steering angle of the rear-wheel steering actuator among the multiple actuators are then allocated based on the first control variable of the optimal control sequence.

[0089] This application achieves multi-objective collaborative optimization of safety and performance: The MPC prediction model in this application is based on the MPC control framework, unifying the two competing control objectives of "total braking force tracking" and "yaw stability control" into a single optimization problem. Through online rolling optimization, the globally optimal rear wheel steering angle and braking force combination can be calculated in each control cycle, thereby providing the maximum possible braking force while ensuring that the vehicle does not lose control, achieving the best balance between safety and braking performance.

[0090] Optionally, if the first EMB actuator of wheel fl fails, then in each control cycle, based on the effective braking force, the vehicle body center of gravity sideslip angle, and the vehicle body yaw rate, the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain is solved, including: In each control cycle, the currently acquired vehicle yaw rate and vehicle center of gravity sideslip angle are used as the predicted initial state, and the external disturbance inputs are set within a preset step size. Remain unchanged; Under the constraints of the optimization problem, the minimum value of the multi-objective optimization function J within the next N prediction steps is obtained to get the optimal control sequence; where the disturbance input... Including the effective braking force of the first EMB actuator of the first wheel configuration and / or the front axle steering angle. The boundaries of the constraints include the maximum braking force of each wheel. and / or maximum steering angle .

[0091] exist Figure 6 In the online rolling optimization: at each sampling time k, the MPC controller of the MPC predictive control takes the currently measured vehicle yaw rate and vehicle center of gravity sideslip angle X(0) as the initial state, and assumes that the disturbance input d remains unchanged within a preset step size. Under the premise of satisfying the control constraints, it solves for the minimum value of the multi-objective optimization function J within the next N prediction steps, and obtains a series of optimal control sequences {u(k), u(k+1), ... u(k+N-1)}; where the disturbance input d includes the effective braking force of the first EMB actuator configured on the fl wheel and the front axle steering angle corresponding to the driver's operation (intention). .

[0092] Output control quantity: The first control quantity u(0) in this sequence is actually output to the braking force F of the second EMB actuator configured on the fr wheel. fr The braking force F of the second EMB actuator configured on the rl wheel rl The braking force F of the second EMB actuator configured on the rr wheel rr and the target turning angle of the steering actuator. At the next sampling time, the above process is repeated to achieve closed-loop rolling optimization control.

[0093] Here, the MPC controller receives the effective braking force from the first EMB actuator. The MPC controller incorporates a vehicle dynamics prediction model and MPC optimization algorithm, ultimately outputting two sets of control commands: one is the target braking force distribution command for the three second EMB actuators; the other is the target steering angle for the rear wheel steering actuators. This application successfully incorporates rear-wheel steering into brake fault-tolerant control and utilizes the powerful multivariable, constrained optimization capabilities of MPC to achieve an intelligent, adaptive optimal balance between braking performance and vehicle stability after a single-point failure of EMB, significantly improving the functional safety and performance of intelligent vehicles.

[0094] In one example, this application uses the MPC prediction model to consider rear-wheel steering based on a two-degree-of-freedom vehicle model and adds yaw moment due to differential braking; wherein, the MPC prediction model is determined based on the following steps: Constructing a dynamic model:

[0095] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. The yaw rate of the vehicle body; This is the acceleration due to the yaw of the vehicle body; The sideslip angle is the angle between the vehicle's center of gravity and its body. The sideslip angular velocity of the vehicle's center of gravity; , These are the front and rear axle lateral stiffness, respectively. , These are the front and rear axle rotation angles, respectively. Let Z be the moment of inertia of the vehicle about the z-axis; , These are the distances from the front and rear axles to the center of mass, respectively. 1 represents the wheelbase; Feedback braking force of the EMB actuator configured for the fr wheel; Effective braking force of the EMB actuator configured for wheel fl; Feedback braking force of the EMB actuator configured for the rr wheel; Feedback braking force of the EMB actuator configured for the rl wheel; by The dynamic model is transformed into a state-space model in matrix form: To build a predictive model for MPC:

[0096] in, For state variables; The sideslip angle is the angle between the vehicle's center of gravity and its body. The yaw rate of the vehicle body; For control variables; The rear wheel steering angle; Interference input Front axle steering angle controlled by the driver And the confirmed effective braking force of the first EMB actuator ; The rate of change of state; The state matrix; For control matrix; This is the interference matrix.

[0097] Optionally, the formula for the multi-objective optimization function of the optimization problem is:

[0098] Where N is the prediction time domain length; These are the weighting coefficients for the stability term; To control the weighting coefficients of the incremental terms; The tracking weight for the total braking force; Predicted total braking force provided for all second EMB actuators; For the expected total braking force; , and These are the desired yaw rate and the desired sideslip angle of the center of mass, respectively. Let K be the state variable for the k-th control cycle. For the control variable in the k-th control cycle; T stands for transpose; And / or, The constraints of the optimization problem include EMB actuator constraints and / or braking force constraints: EMB actuator constraints include rear wheel steering angle constraints and braking force constraints; Among them, the rear wheel steering angle constraint is set to not exceed the mechanical limit angle of the rear wheel steering actuator; The braking force constraint adopts a dynamic upper limit strategy, which specifically includes: In the initial state, the upper limit of braking force for each normal EMB actuator is set to the physical limit value of the EMB actuator hardware itself; During the control cycle, if any normal (second) EMB actuator triggers ABS anti-lock braking control after applying the target braking force, the upper limit of the braking force of that EMB actuator will be updated to the actual braking force value corresponding to the ABS activation time in the next control cycle. Here, all second EMB actuators refer to the three second EMB actuators mentioned above.

[0099] The following is a detailed description of step 105 (i.e., determining the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators based on the solution results).

[0100] After outputting two sets of control commands in step 104, the control commands are assigned to the corresponding actuators: one is the target braking force assignment command for the three second EMB actuators; the other is the target steering angle command for the rear wheel steering actuator. .

[0101] In some examples of this application, the EMB failure control method is applicable to an intelligent vehicle platform that integrates an EMB actuator and an RWS actuator; additionally, the upper-level controller of the intelligent vehicle platform (such as an ECU (Electronic Control Unit) or a Domain Controller (DCU)) is used to execute the EMB failure control method. For ease of explanation, the following will consistently use left front wheel EMB failure as an example; other EMB failure scenarios can be deduced similarly. Figure 7 As shown, when this application is implemented, the rear wheel steering angle will be controlled to generate lateral force to counteract the differential torque caused by single-point failure unbalanced braking, while the effective braking force of the first EMB actuator will be adjusted to achieve a balance between stability and braking performance.

[0102] exist Figure 7 The overall process consists of three steps: Step 1) Data Acquisition, Step 2) Failure Detection and Confirmation, Step 3) Braking Force Confirmation, and Step 4) MPC (Controller) Cooperative Control. The specific details are as follows: It should be noted that the intelligent vehicle platform also includes an EMB failure control device, which includes a data input module, an actuator failure detection module, a braking force confirmation module, a solution module, and an allocation module.

[0103] Step 1) Obtain vehicle status data: The data input module outputs vehicle status data, which includes feedback braking force (e.g., to the EMB actuators configured on each of the four wheels) for each wheel. Figure 3 F in break ), diagnostic messages from the EMB underlying controller (such as Figure 3 The DiagMessage shown), the vehicle speed of the ABS controller (such as...) Figure 3The Vx shown) and activation flag (such as Figure 3 The figures shown are ABSActive, steering wheel angle, and front axle angle. Vehicle yaw rate (YawRate), vehicle lateral acceleration (Ay), vehicle longitudinal acceleration (Ax), and the desired total braking force F obtained from the brake pedal opening collected by the pedal sensor. tag ,according to The expected centroid sideslip angle is obtained by estimating with Ax. and expected yaw rate The sideslip angle of the vehicle's center of gravity is estimated based on Vx and Ay. .

[0104] in, Ay is acquired by the angle sensor; Ay is acquired by the IMU (Inertial Measurement Unit).

[0105] In one example, for the vehicle's center of gravity sideslip angle It can be estimated using integration:

[0106] in, This refers to the longitudinal speed of the vehicle. This refers to the lateral speed. To Integrate over t; The derivative of t; Let t be the lateral acceleration of the vehicle body, and t be the time.

[0107] In one example, the EMB failure control method also includes: The desired yaw rate was calculated using a two-degree-of-freedom vehicle model. Desired centroid side slip angle :

[0108] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. This is the distance from the front axle to the center of gravity. This is the distance from the rear axle to the center of mass. This refers to the wheelbase; Front axle steering angle; For front axle lateral stiffness; This refers to the rear axle lateral stiffness.

[0109] Step 2) The actuator failure detection module receives data from the data input module and detects single-point failures through dual verification. When it is detected that the absolute value of the difference between the target braking force and the actual feedback braking force of a certain EMB actuator is greater than a first threshold (this first threshold is related to the braking force control accuracy and response speed of the underlying controller of the EMB actuator) for a continuous period of time; or when the diagnostic message confirms that the first EMB actuator has a fault code such as "motor overcurrent" or "communication interruption", then the first EMB actuator is determined to have failed.

[0110] Step 3) Estimate the total braking force of the vehicle based on the vehicle's longitudinal acceleration sensor, and by subtracting the feedback braking force of the other normal EMB actuators, back-calculate the estimated actual braking force of the first EMB actuator; compare this estimated value with the last recorded normal feedback value before failure, and take the value with higher confidence as the current effective braking force of the first EMB actuator: The braking force determination module first reads the current longitudinal acceleration of the vehicle body. Vehicle quality and the feedback braking force of the three second EMB actuators. , , The normal braking force value fed back by the first EMB actuator at the last moment before the failure occurred. According to Newton's second law, estimate the braking force of the first EMB actuator by subtracting the sum of the feedback braking forces of the three second EMB actuators from the total braking force of the entire vehicle.

[0111] Perform a credibility assessment. Calculate the difference. Set a threshold. This threshold takes into account accelerometer noise and tire model error. If If the estimated value matches the remembered value well, then it can be used directly. As the final confirmed value Otherwise, considering the significant uncertainty in the estimation process, and based on the principle of safety and conservatism, the estimated value should be used first. As This is because acceleration better reflects the instantaneous dynamics of a vehicle. This step ensures that the system state data upon which the subsequent MPC controller is based is as accurate as possible.

[0112] Step 4) Establish a predictive model that includes rear-wheel steering and differential braking torque; using the driver's requested total vehicle braking force, desired yaw rate, and desired sideslip angle as tracking targets, construct a multi-objective optimization function; in each control cycle, use the MPC (Model Predictive Control) algorithm to solve in real time the control sequence that minimizes the optimization function in the future time domain, and output the first control variable, namely the target braking force distribution scheme of the remaining normal EMB actuators and the target steering angle of the rear wheels, to each actuator. For details, refer to [link to relevant documentation]. Figure 6 : The solution module receives the effective braking force from the first EMB actuator from the MPC controller. The MPC controller also receives various vehicle status data from the data input module. It incorporates a vehicle dynamics prediction model and MPC optimization algorithm, ultimately outputting two sets of control commands: one for the target braking force distribution to the three second EMB actuators; and the other for the target steering angle of the active rear wheel steering actuator. : The prediction model used in this application considers rear-wheel steering based on the classic two-degree-of-freedom vehicle model and adds yaw moment caused by differential braking:

[0113] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. This refers to the yaw rate; The sideslip angle is the angle between the vehicle's center of gravity and its body. , For the front and rear axle lateral stiffness; , For front and rear axle rotation angles; Let Z be the moment of inertia of the vehicle about the z-axis; , These are the distances from the front and rear axles to the center of mass; Wheelbase; Feedback braking force of the EMB actuator configured for the fr wheel; Effective braking force of the EMB actuator configured for wheel fl; Feedback braking force of the EMB actuator configured for the rr wheel; Feedback braking force of the EMB actuator configured for the rl wheel; Transform the dynamic model into a matrix-form state-space model:

[0114] Among them, state variables Select as centroid sideslip angle and yaw rate Control variables Feedback braking force for rear wheel steering angle and three second EMB actuators; disturbance input The front axle steering angle controlled by the driver and the effective braking force of the first EMB actuator; that is:

[0115] The system matrix is ​​as follows:

[0116]

[0117]

[0118] A multi-objective optimization function J is constructed to simultaneously optimize braking tracking and stability.

[0119]

[0120] Where N is the prediction time domain length; State weight matrix It is the weighting coefficient of the stability term, reflecting the degree of importance attached to yaw stability; Control input weights It is the weighting coefficient for controlling the incremental term, used to prevent the control action from being too drastic; It is the total braking force tracking weight; It is the predicted value of the sum of the braking forces of three normal EMB systems; It is the expected total braking force determined by the driver's brake pedal request (i.e., the driver's intention); , and These are the expected yaw rate and expected centroid sideslip angle from the data input module.

[0121] Constraints are set: The optimization problem needs to satisfy multiple constraints, and the rear wheel steering angle cannot exceed the mechanical limit (i.e., the maximum steering angle). ); Upper limit of brake actuator The braking force limit of each normal actuator is dynamically changed. In the initial state, the upper limit of braking force of each normal actuator is set to the limit of the EMB hardware itself. When a normal actuator triggers ABS after performing the target braking force, the upper limit of braking force of that actuator is updated according to the braking force when ABS is activated in the next control cycle.

[0122] Online rolling optimization: At each sampling time k, the MPC controller adjusts the vehicle state based on the currently measured parameters. Given the initial state, and assuming that the input is disturbed within a preset step size. Without changing the control constraints, we solve for the minimum value of the multi-objective optimization function J over the next N prediction steps to obtain a series of optimal control sequences. ; The corresponding output control quantity of the allocation module: the first control quantity in the sequence. The actual output is sent to the actuator. At the next sampling time, the above process is repeated to achieve closed-loop rolling optimization control.

[0123] Through the above specific implementation methods, this application successfully introduces rear-wheel steering into brake fault-tolerant control, and utilizes the powerful multivariable and constrained optimization capabilities of MPC to achieve an intelligent and adaptive optimal balance between braking performance and vehicle stability after a single-point failure of EMB, significantly improving the functional safety and performance of intelligent vehicles.

[0124] Compared with the prior art, this application has the following significant advantages: This ensures braking performance and guarantees basic safety: In the event of a single EMB actuator failure, this application does not simply limit the output of other normal EMBs. Instead, it dynamically adjusts the feedback braking force distribution of the remaining three second EMB actuators through the MPC controller, allowing the vehicle's total braking force to approach the driver's expected request as closely as possible. This is particularly crucial in emergency braking conditions, avoiding the dangerous situation of excessively long braking distances or even complete brake failure due to brake failure, fundamentally guaranteeing the vehicle's longitudinal braking safety.

[0125] Actively maintaining yaw stability enhances handling safety: By introducing RWS technology and utilizing the MPC controller to collaboratively optimize rear wheel steering angle and braking force distribution, it can actively and precisely generate compensating yaw moment, effectively counteracting the disturbing yaw moment caused by the lack or abnormal braking force of a single wheel. This allows the vehicle's yaw rate and sideslip angle under fault conditions to closely track ideal values, greatly improving the vehicle's handling stability and directional controllability, and preventing secondary accidents such as fishtailing and instability.

[0126] This application achieves multi-objective collaborative optimization of safety and performance: The MPC prediction model is based on the MPC control framework, unifying the two competing control objectives of "total braking force tracking" and "yaw stability control" into a single optimization problem. Through online rolling optimization, the globally optimal rear wheel steering angle and braking force combination can be calculated in each control cycle, thereby providing the maximum possible braking force while ensuring the vehicle does not lose control, achieving the best balance between safety and braking performance.

[0127] The system's reliability and fault tolerance have been improved: Through a dual verification mechanism of "single-point failure detection" and "failed actuator braking force confirmation," the system can quickly and accurately diagnose faults and assess the current braking state, providing reliable state input for subsequent MPC optimization control. This significantly enhances the robustness and reliability of the brake-by-wire system, increasing driver confidence in the event of a fault.

[0128] Figure 8 A schematic diagram of an EMB failure control device provided in an embodiment of this application. This EMB failure control device is used to perform... Figure 1 or Figure 7 The EMB failure control method shown is as follows. Figure 8 As shown, the EMB failure control device includes: The data input module 801 is used to acquire vehicle status data; the vehicle status data includes the feedback braking force of multiple EMB actuators among multiple actuators, the longitudinal acceleration of the vehicle body, the sideslip angle of the vehicle center of gravity, and the yaw rate of the vehicle body. The actuator failure detection module 802 is used to determine whether there is a failed first EMB actuator based on the feedback braking force of multiple EMB actuators. The braking force determination module 803 is used to determine the effective braking force of the first EMB actuator if it exists, based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among multiple EMB actuators. The solver module 804 is used to solve the optimization problem of the prediction model of MPC in the rolling time domain based on the effective braking force, the vehicle center of gravity sideslip angle and the vehicle yaw rate; the optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate and the desired center of gravity sideslip angle. The allocation module 805 is used to determine the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators based on the solution results.

[0129] Optionally, if the vehicle status data also includes actuator diagnostic messages, the actuator failure detection module 802 is further configured to: Calculate the difference between the target braking force and the feedback braking force for each EMB actuator; If the difference detected by the first EMB actuator is greater than or equal to the first threshold, the timer is reset to zero. If the difference detected by the first EMB actuator is less than the first threshold, the timing is increased; If the timing reaches the second threshold, the first EMB actuator is determined to have failed. If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to have failed; otherwise, the first EMB actuator is confirmed to have not failed.

[0130] Optionally, the braking force determination module 803 includes: The first estimation unit is used to estimate the total braking force of the vehicle based on the longitudinal acceleration of the vehicle body. The second estimation unit is used to determine the estimated braking force of the first EMB actuator based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among multiple EMB actuators. The braking force determination unit is used to determine the effective braking force of the first EMB actuator based on the comparison between the estimated braking force value and the feedback braking force last recorded before the failure of the first EMB actuator.

[0131] Optionally, the braking force determining unit is further used for: Determine the estimated braking force The feedback braking force last recorded before the failure of the first EMB actuator The difference between them; If the difference is less than or equal to the third threshold, then feedback braking force will be applied. As the effective braking force of the first EMB actuator ; If the difference is greater than the third threshold, then the estimated braking force value will be... As the effective braking force of the first EMB actuator .

[0132] Optionally, the solver module 804 includes: The building unit is used to construct an optimization problem of the prediction model of MPC with the total braking force of the vehicle, the desired yaw rate and the desired center of gravity sideslip angle as the tracking targets. The solution unit is used to solve for the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain, based on the effective braking force, the sideslip angle of the vehicle center of gravity, and the yaw rate of the vehicle in each control cycle. The allocation module 805 is further used for: The braking force assigned to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined based on the first control variable in the optimal control sequence.

[0133] Optionally, if the first EMB actuator configured on wheel fl fails, the solution unit is further configured to: In each control cycle, the currently acquired vehicle yaw rate and vehicle center of gravity sideslip angle are used as the predicted initial state, and the external disturbance inputs are set within a preset step size. Remain unchanged; Under the constraints of the optimization problem, the minimum value of the multi-objective optimization function J within the next N prediction steps is obtained to get the optimal control sequence; where the disturbance input... Including the effective braking force of the first EMB actuator of the first wheel configuration and / or the front axle steering angle. The boundaries of the constraints include the maximum braking force of each wheel. and / or maximum steering angle .

[0134] Optionally, if the first EMB actuator configured on the fl wheel of the vehicle fails, the prediction model for MPC is determined based on the following steps: Constructing a dynamic model:

[0135] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. The yaw rate of the vehicle body; The sideslip angle is the angle between the vehicle's center of gravity and its body. , These are the front and rear axle lateral stiffness, respectively. , These are the front and rear axle rotation angles, respectively. Let Z be the moment of inertia of the vehicle about the z-axis; , These are the distances from the front and rear axles to the center of mass, respectively. 1 represents the wheelbase; Feedback braking force of the EMB actuator configured for the fr wheel; Effective braking force of the EMB actuator configured for wheel fl; Feedback braking force of the EMB actuator configured for the rr wheel; Feedback braking force of the EMB actuator configured for the rl wheel; by The dynamic model is transformed into a state-space model in matrix form: To build a predictive model for MPC:

[0136] in, For state variables; The sideslip angle is the angle between the vehicle's center of gravity and its body. The yaw rate of the vehicle body; For control variables; The rear wheel steering angle; Interference input Front axle steering angle controlled by the driver and the effective braking force of the first EMB actuator .

[0137] Optionally, the formula for the multi-objective optimization function of the optimization problem is:

[0138] Where N is the prediction time domain length; These are the weighting coefficients for the stability term; To control the weighting coefficients of the incremental terms; The tracking weight for the total braking force; Predicted total braking force provided for all second EMB actuators; For the expected total braking force; , and These are the desired yaw rate and the desired sideslip angle of the center of mass, respectively. Let K be the state variable for the k-th control cycle. For the control variable in the k-th control cycle; T stands for transpose; And / or, The constraints of the optimization problem include EMB actuator constraints and / or braking force constraints: Among them, the rear wheel steering angle constraint is set to not exceed the mechanical limit angle of the rear wheel steering actuator; Braking force constraints are determined based on the following steps: In the initial state, the upper limit of braking force of each EMB actuator in the second EMB actuator is set to its own physical limit value; During the operation of the control cycle, when it is detected that the target EMB actuator in the second EMB actuator triggers ABS anti-lock braking control after performing the target braking force, the upper limit of the braking force of the target EMB actuator will be updated to the actual braking force value corresponding to the activation time of ABS anti-lock braking control in the next control cycle.

[0139] Optionally, the EMB failure control device further includes: The estimation module is used to calculate the desired yaw rate using a two-degree-of-freedom vehicle model. Desired centroid side slip angle :

[0140]

[0141] in, For vehicle weight; This refers to the longitudinal speed of the vehicle. , These are the distances from the front and rear axles to the center of mass, respectively. This refers to the wheelbase; Front axle steering angle; , These are the front and rear axle lateral stiffness, respectively.

[0142] Optionally, the vehicle body center of gravity sideslip angle is calculated based on the following formula:

[0143] in, , These refer to longitudinal and lateral vehicle speeds, respectively. To Integrate over t; The derivative of t; Let t be the lateral acceleration of the vehicle body, and t be the time.

[0144] This application provides an intelligent vehicle platform that integrates multiple EMB actuators and a rear wheel steering actuator. The electronic control unit of the intelligent vehicle platform is used to execute the steps of the EMB failure control method described in any of the above schemes.

[0145] This application provides a computer-readable storage medium storing program information. After reading the program information, the computer executes the steps of the EMB failure control method described in any of the above schemes.

[0146] This application provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the EMB failure control method described in any of the above schemes.

[0147] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this application.

Claims

1. An EMB failure control method, characterized in that, The method includes: Acquire vehicle status data; the vehicle status data includes the feedback braking force of multiple EMB actuators among multiple actuators, the longitudinal acceleration of the vehicle body, the sideslip angle of the vehicle center of gravity, and the yaw rate of the vehicle body. The presence of a failed first EMB actuator is determined based on the feedback braking force from multiple EMB actuators. If it exists, the effective braking force of the first EMB actuator is determined based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among multiple EMB actuators. The optimization problem of the prediction model of MPC is solved in the rolling time domain based on the effective braking force, the vehicle center of gravity sideslip angle, and the vehicle yaw rate. The optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate, and the desired center of gravity sideslip angle. Based on the solution results, determine the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators.

2. The EMB failure control method according to claim 1, characterized in that, If the vehicle status data also includes actuator diagnostic messages, then determining whether a first failed EMB actuator exists based on the feedback braking force of multiple EMB actuators includes: Calculate the difference between the target braking force and the feedback braking force for each EMB actuator; If the difference detected by the first EMB actuator is greater than or equal to the first threshold, the timer is reset to zero. If the difference detected by the first EMB actuator is less than the first threshold, the timing is increased; If the timing reaches the second threshold, the first EMB actuator is determined to have failed. If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to have failed; otherwise, the first EMB actuator is confirmed to have not failed.

3. The EMB failure control method according to claim 1, characterized in that, The determination of the effective braking force of the first EMB actuator based on the total braking force of the vehicle determined by the vehicle's longitudinal acceleration and the feedback braking force of the second EMB actuator among multiple EMB actuators includes: Estimate the total braking force of the vehicle based on the longitudinal acceleration of the vehicle body; The estimated braking force of the first EMB actuator is determined based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among the multiple EMB actuators. The effective braking force of the first EMB actuator is determined by comparing the estimated braking force with the feedback braking force recorded last before the failure of the first EMB actuator.

4. The EMB failure control method according to claim 3, characterized in that, The step of determining the effective braking force of the first EMB actuator based on the comparison between the estimated braking force and the feedback braking force last recorded before the failure of the first EMB actuator includes: Determine the estimated braking force The feedback braking force last recorded before the failure of the first EMB actuator The difference between them; If the difference is less than or equal to the third threshold, then feedback braking force will be applied. As the effective braking force of the first EMB actuator ; If the difference is greater than the third threshold, then the estimated braking force value will be... As the effective braking force of the first EMB actuator .

5. The EMB failure control method according to claim 1, characterized in that, The optimization problem of the MPC prediction model in the rolling time domain, based on the effective braking force, the vehicle's center of gravity sideslip angle, and the vehicle's yaw rate, includes: The optimization problem of constructing a prediction model for MPC is centered on the total braking force of the vehicle, the desired yaw rate, and the desired sideslip angle of the center of gravity as the tracking targets. In each control cycle, based on the effective braking force, the sideslip angle of the vehicle's center of gravity, and the vehicle's yaw rate, the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain is solved. The step of determining the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among multiple actuators based on the solution results includes: The braking force assigned to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined based on the first control quantity in the optimal control sequence.

6. The EMB failure control method according to claim 5, characterized in that, If the first EMB actuator of wheel fl fails, then in each control cycle, based on the effective braking force, the vehicle's center of gravity sideslip angle, and the vehicle's yaw rate, the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain is solved, including: In each control cycle, the currently acquired vehicle yaw rate and vehicle center of gravity sideslip angle are used as the predicted initial state, and the external disturbance inputs are set within a preset step size. Remain unchanged; Under the constraints of the optimization problem, the minimum value of the multi-objective optimization function J within the next N prediction steps is obtained to get the optimal control sequence; where the disturbance input... Including the effective braking force of the first EMB actuator of the first wheel configuration and / or the front axle steering angle. The boundaries of the constraints include the maximum braking force of each wheel. and / or maximum steering angle .

7. The EMB failure control method according to claim 1 or 5, characterized in that, If the first EMB actuator configured on the fl wheel of the vehicle fails, the MPC prediction model is determined based on the following steps: Constructing a dynamic model: in, For vehicle weight; This refers to the longitudinal speed of the vehicle. The yaw rate of the vehicle body; This is the acceleration due to the yaw of the vehicle body; The sideslip angle is the angle between the vehicle's center of gravity and its body. The sideslip angular velocity of the vehicle's center of gravity; , These are the front and rear axle lateral stiffness, respectively. , These are the front and rear axle rotation angles, respectively. Let Z be the moment of inertia of the vehicle about the z-axis; , These are the distances from the front and rear axles to the center of mass, respectively. 1 represents the wheelbase; Feedback braking force of the EMB actuator configured for the fr wheel; Effective braking force of the EMB actuator configured for wheel fl; Feedback braking force of the EMB actuator configured for the rr wheel; Feedback braking force of the EMB actuator configured for the rl wheel; by The dynamic model is transformed into a state-space model in matrix form: To build a predictive model for MPC: in, For state variables; For control variables; interference input Including front axle steering angle and the effective braking force of the first EMB actuator ; The rate of change of state; The state matrix; For control matrix; This is the interference matrix.

8. The EMB failure control method according to claim 5 or 6, characterized in that, The formula for the multi-objective optimization function of the optimization problem is: Where N is the prediction time domain length; These are the weighting coefficients for the stability term; To control the weighting coefficients of the incremental terms; The tracking weight for the total braking force; Predicted total braking force provided for all second EMB actuators; For the expected total braking force; , and These are the desired yaw rate and the desired sideslip angle of the center of mass, respectively. Let K be the state variable for the k-th control cycle. Here, T represents the control variable for the k-th control cycle; T is the transpose. And / or, The constraints of the optimization problem include EMB actuator constraints and / or braking force constraints: Among them, the rear wheel steering angle constraint is set to not exceed the mechanical limit angle of the rear wheel steering actuator; The braking force constraint is determined based on the following steps: In the initial state, the upper limit of braking force of each EMB actuator in the second EMB actuator is set to its own physical limit value; During the operation of the control cycle, when it is detected that the target EMB actuator in the second EMB actuator triggers ABS anti-lock braking control after performing the target braking force, the upper limit of the braking force of the target EMB actuator will be updated to the actual braking force value corresponding to the activation time of ABS anti-lock braking control in the next control cycle.

9. The EMB failure control method according to claim 5, characterized in that, The method further includes: The desired yaw rate was calculated using a two-degree-of-freedom vehicle model. Desired centroid side slip angle : in, For vehicle weight; This refers to the longitudinal speed of the vehicle. , These are the distances from the front and rear axles to the center of mass, respectively. Wheelbase Front axle steering angle; , These are the front and rear axle lateral stiffness, respectively.

10. The EMB failure control method according to any one of claims 1-6, characterized in that, The vehicle body center of gravity sideslip angle is calculated based on the following formula: in, , These are the longitudinal and lateral vehicle speeds, respectively. To Integrate over t. For the differential of t, Let t be the lateral acceleration of the vehicle body, and t be the time.

11. An EMB failure control method, characterized in that, The method is applied to an intelligent vehicle platform that integrates multiple EMB actuators and a rear wheel steering actuator. The intelligent vehicle platform also includes an electronic control unit for executing the EMB failure control method as described in any one of claims 1-10.

12. An EMB failure control device, characterized in that, The device includes: The data input module is used to acquire vehicle status data, which includes the feedback braking force of multiple EMB actuators among multiple actuators, the longitudinal acceleration of the vehicle body, the sideslip angle of the vehicle body center of gravity, and the yaw rate of the vehicle body. The actuator failure detection module is used to determine whether there is a failed first EMB actuator based on the feedback braking force of multiple EMB actuators. The braking force determination module is used to determine the effective braking force of the first EMB actuator, if present, based on the total braking force of the vehicle determined by the longitudinal acceleration of the vehicle body and the feedback braking force of the second EMB actuator among multiple EMB actuators. The solution module is used to solve the optimization problem of the prediction model of MPC in the rolling time domain based on the effective braking force, the vehicle center of gravity sideslip angle, and the vehicle yaw rate; the optimization problem is constructed based on the total braking force of the vehicle, the desired yaw rate, and the desired center of gravity sideslip angle. The allocation module is used to determine the braking force allocated to the second EMB actuator and the target steering angle of the rear wheel steering actuator among multiple actuators based on the solution results.

13. The EMB failure control device according to claim 12, characterized in that, If the vehicle status data also includes actuator diagnostic messages, the actuator failure detection module is further configured to: Calculate the difference between the target braking force and the feedback braking force for each EMB actuator; If the difference detected by the first EMB actuator is greater than or equal to the first threshold, the timer is reset to zero. If the difference detected by the first EMB actuator is less than the first threshold, the timing is increased; If the timing reaches the second threshold, the first EMB actuator is determined to have failed. If the timing does not reach the second threshold and a fault code for the first EMB actuator is found in the actuator diagnostic message, then the first EMB actuator is confirmed to have failed; otherwise, the first EMB actuator is confirmed to have not failed.

14. The EMB failure control device according to claim 12, characterized in that, Braking force determination module, including: The first estimation unit is used to estimate the total braking force of the vehicle based on the longitudinal acceleration of the vehicle body. The second estimation unit is used to determine the estimated braking force of the first EMB actuator based on the total braking force of the vehicle and the feedback braking force of the second EMB actuator among the multiple EMB actuators. The braking force determination unit is used to determine the effective braking force of the first EMB actuator based on the comparison result between the estimated braking force value and the feedback braking force last recorded before the failure of the first EMB actuator.

15. The EMB failure control device according to claim 14, characterized in that, The braking force determining unit is further used for: Determine the estimated braking force The feedback braking force last recorded before the failure of the first EMB actuator The difference between them; If the difference is less than or equal to the third threshold, then feedback braking force will be applied. As the effective braking force of the first EMB actuator ; If the difference is greater than the third threshold, then the estimated braking force value will be... As the effective braking force of the first EMB actuator .

16. The EMB failure control device according to claim 12, characterized in that, The solution module includes: The building unit is used to construct an optimization problem of the prediction model of MPC with the total braking force of the vehicle, the desired yaw rate and the desired center of gravity sideslip angle as the tracking targets. The solution unit is used to solve for the optimal control sequence that minimizes the multi-objective optimization function of the optimization problem in the rolling time domain, based on the effective braking force, the sideslip angle of the vehicle center of gravity, and the yaw rate of the vehicle in each control cycle. The allocation module is further used for: The braking force assigned to the second EMB actuator and the target steering angle of the rear wheel steering actuator among the multiple actuators are determined based on the first control quantity in the optimal control sequence.

17. The EMB failure control device according to claim 16, characterized in that, If the first EMB actuator configured on wheel fl fails, the solution unit is further used for: In each control cycle, the currently acquired vehicle yaw rate and vehicle center of gravity sideslip angle are used as the predicted initial state, and the external disturbance inputs are set within a preset step size. Remain unchanged; Under the constraints of the optimization problem, the minimum value of the multi-objective optimization function J within the next N prediction steps is obtained to get the optimal control sequence; where the disturbance input... Including the effective braking force of the first EMB actuator of the first wheel configuration and / or the front axle steering angle. The boundaries of the constraints include the maximum braking force of each wheel. and / or maximum steering angle .

18. An intelligent vehicle platform, characterized in that, include: An electronic control unit, multiple EMB actuators, and a rear wheel steering actuator; wherein the electronic control platform is used to execute the EMB failure control method as described in any one of claims 1-11.

19. A storage medium, characterized in that, The storage medium stores computer instructions, which, when executed by the computer, are used to perform the EMB failure control method as described in any one of claims 1-11.

20. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the EMB failure control method as described in any one of claims 1-11.

Images