A method for improving the safety of distributed drive electric vehicles through soft interference

Abstract

This invention relates to the field of automotive safety control technology, and discloses a method for improving the safety of distributed drive electric vehicles through soft interference, belonging to the field of active safety control technology for distributed drive electric vehicles. The method includes: constructing a two-layer judgment condition based on a multi-dimensional state space and driver operation state to determine the vehicle state; determining whether the electric power steering (EPS) system and wheel hub motors generate soft interference to alert and softly limit driver erroneous operations; and introducing an enhancement factor to increase the control intensity of the additional yaw moment when the vehicle is in a dangerous state, thereby enhancing the vehicle's stability. This invention can softly limit the effects of driver erroneous input, correct vehicle posture, and improve vehicle safety, handling, and stability.

Description

Technical Field

[0001] This invention relates to the field of automotive safety control technology, and in particular to a method for improving the safety of distributed drive electric vehicles through soft interference. Background Technology

[0002] With the rapid development of automotive chassis electronic control technology, distributed drive electric vehicles, due to their independently adjustable drive torque for each wheel, have shown great potential in terms of handling stability and safety. Existing vehicle stability control research largely focuses on forcibly intervening in vehicle attitude through methods such as Direct Yaw Control (DYC) or Active Rear Steering (ARS). However, in emergency situations where the vehicle approaches its physical limits or becomes unstable (such as on icy or low-traction roads, or high-speed emergency obstacle avoidance), driver error due to psychological pressure is a significant factor, and continued forced intervention would exacerbate the danger. To address these issues, existing technologies leverage the characteristics of Electric Power Steering (EPS) systems, forcibly intervening by limiting the maximum steering wheel angle and maximum steering angular velocity, or guiding driver operation through vibration waves, and increasing damping to limit excessively fast or large steering. However, the aforementioned technologies still have the following drawbacks: 1. When the driver has correctly steered to stop the vehicle, the system continues to apply damping, or applies vibration waves and damping simultaneously. This can lead to cognitive errors in the driver, hindering their correct operation. Furthermore, the damping does not consider ergonomic factors, potentially increasing the driver's workload. 2. The advantages of distributed drive electric vehicles are not fully utilized. While intervening through EPS, the unique advantages of in-wheel motors are used to actively create a trend opposite to the driver's erroneous operation to reduce the severity of the error and minimize direct intervention in the driver's actions. 3. When the vehicle enters an extremely dangerous situation, continued hard intervention may hinder the driver's instinctive rescue actions, creating a human-machine conflict. Therefore, to solve the above problems, this invention proposes a method to improve the safety of distributed drive electric vehicles through soft intervention. Summary of the Invention

[0003] The purpose of this invention is to address the problems existing in the prior art by providing a method for improving the safety of distributed drive electric vehicles through soft interference. When the vehicle approaches danger, the method uses soft interference torque on the steering wheel and adjustments to the torque weights of the front and rear wheels to suppress driver errors and oversteering input. When the vehicle is in a danger zone, the soft interference is disengaged and the strength of the additional yaw moment is increased, thereby improving vehicle handling stability and safety without hindering necessary driver intervention. The specific solution of this invention is as follows: In addition to the existing power assist torque, self-centering torque, and basic damping in the EPS of distributed drive electric vehicles, a soft interference torque is added. This torque is used to alert the driver whether they are in the correct steering direction when the vehicle's condition is becoming dangerous. When the driver makes an incorrect steering input, the soft interference torque will be triggered, providing a direct and perceptible warning to the driver about the steering wheel error and limiting the driver's incorrect operation within a controllable range, thereby improving safety. Simultaneously, leveraging the advantages of distributed drive electric vehicles, under certain conditions, the in-wheel motors actively generate understeer to suppress the driver's oversteering input to the steering wheel.

[0004] Soft interference is triggered when the corresponding triggering conditions are met. The corresponding triggering conditions consist of two layers: the first layer consists of many vehicle parameters, and the second layer consists of the driver's real-time operating status. Meeting the first condition indicates that the vehicle is in a dangerous state, while meeting the second condition indicates that the driver is operating the wrong direction. When only the first layer of conditions is met, it indicates that the vehicle is in a dangerous state, but the driver's steering is correct and reducing the danger. No soft interference torque is generated, the EPS provides normal power assistance, and the wheel hub motor adjusts the front wheel load rate weight and the rear wheel load rate weight to generate active understeer to suppress excessive input when the driver is operating correctly. When two conditions are met simultaneously, it indicates that the vehicle is in a dangerous state and the driver is operating the wrong direction, which is increasing the danger. EPS soft interference torque is generated to remind the driver of the operation error in a visually perceptible way. At the same time, the hub motor increases the driving force of the front wheels and decreases the driving force of the rear wheels to form an understeer trend in coordination with the steering wheel soft interference torque, thereby suppressing the driver's oversteer input. After performing the above operations, the vehicle returns to a safe state, the soft interference disengages, and the EPS resumes normal power assistance. When the vehicle enters a dangerous state after performing the above operations, the soft interference disengages, the EPS resumes normal power assistance, no longer hindering the driver from emergency rescue, and at the same time sends information to the torque distribution control module to enhance the strength of the generated yaw moment, working together with the driver to maintain stability.

[0005] Includes the following steps: (1) Obtain initial parameters, including data from the vehicle's electronic power steering system, vehicle status parameters, and road surface parameters; (2) Determine whether the soft interference triggering condition is met; (3) When the soft interference triggering condition is not met, the electronic power steering system provides normal assistance; (4) When the soft interference triggering condition is met, soft interference is generated. The soft interference includes soft interference torque and active understeering. The soft interference limits the driver's oversteering input and corrects the driver's wrong operation. (5) After the above steps, if the vehicle enters a dangerous state, the soft interference will be disengaged, the electronic power steering system will resume normal power assistance, and at the same time, information will be sent to the torque distribution control module to enhance the strength of the yaw moment generated, and stabilize the vehicle together with the driver, and return to step (1). If the vehicle returns to a safe state, the soft intervention is disengaged, the electronic power steering system resumes normal power assistance, and the process returns to step (1).

[0006] Furthermore, the formula for the soft interference torque is as follows:

[0007] In the formula, M The torque that the electric power steering system ultimately exerts on the steering wheel; M N The sum of torques in an electric power steering system without soft interference torque, including power assist torque, return torque, and basic damping torque; M res This is the newly added soft interference torque.

[0008] Furthermore, the conditions at the first level are as follows: Constructing a multi-dimensional state space based on vehicle state parameters:

[0009]

[0010] in, , In the formula, µ The road surface adhesion coefficient; g It is the acceleration due to gravity; K 1 、K 2 and K 3 represents the weighting coefficient; v x The longitudinal speed of the vehicle; This refers to the vehicle's lateral acceleration. β It is the centroid sideslip angle; c This refers to the yaw rate; Constructing multidimensional hazard characterization factors based on a multidimensional state space SI :

[0011] In the formula, w 1 、w 2 、w 3 and w 4 represents the weighting coefficient. The multidimensional risk characterization factors SI This serves as a parameter to determine whether the first-level conditions are met.

[0012] The multidimensional risk characterization factors SI The judgment rule is: when When the time is specified, it indicates that the vehicle is in a safe state and the electronic power steering system is providing normal assistance. when When the vehicle is approaching a dangerous state, the first-level condition judgment takes effect, the electronic power steering system provides normal assistance, and the wheel hub motor adjusts the front wheel load rate weight and the rear wheel load rate weight to generate active understeering to suppress the oversteering input when the driver operates correctly. when When this occurs, it indicates that the vehicle is in a dangerous state, and the electronic power steering system will only provide normal assistance.

[0013] Furthermore, the second layer of conditions is as follows:

[0014] In the formula, The angular velocity of the steering wheel; For yaw rate error, When the function A value of 0 indicates that the driver is in the correct correction state and the soft interference torque is not triggered; when this function... A value of 1 indicates that the driver is in an escalating danger state, triggering the soft interference torque.

[0015] Furthermore, the model for the soft interference torque is as follows:

[0016] In the formula, - k adp For adaptive damping gain; M res This is the final generated soft interference torque; M max The maximum torque that allows the driver to turn the steering wheel without difficulty is the controllable limit to the driver's erroneous actions.

[0017] The first layer of conditions considers many parameters related to the vehicle, the second layer of conditions considers driver behavior information, and the adaptive gain considers environmental information and EPS characteristics.

[0018] Furthermore, adaptive gain k adp The design is as follows:

[0019] In the formula, G base Base proportional gain; µ The road surface adhesion coefficient; α( phase The weight mapping function reflects the degree of danger of the vehicle's state; the second-level conditions are directly embedded into the soft interference moment model to reduce complexity.

[0020] Furthermore, adaptive gain parameters f ( µ The expression form of ) is:

[0021] K µ The maximum road surface compensation coefficient is set between 1.5 and 2.0. Considering the impact of road conditions on the electric power steering system, when the road surface is very slippery, the steering wheel feel will become lighter (due to reduced tire return torque), making it easier for the driver to oversteer. Therefore, a road surface factor is introduced. f ( µ ), µ The smaller, f ( µ The larger the number of ) Based on multidimensional risk characterization factors SI Construct the weight mapping function:

[0022] In the formula, when hour, .

[0023] By employing an S-curve based on the cosine function for a smooth transition, the continuity of the gain coefficient on the first derivative is ensured, eliminating the abruptness of damping intervention from a physical level and achieving seamless human-computer interaction.

[0024] Furthermore, the method for adjusting the front wheel load rate weight and rear wheel load rate weight in the four-wheel torque optimization distribution is to reduce the front wheel coefficient distribution weight and increase the rear wheel coefficient distribution weight. The four-wheel torque distribution optimization objective function used in this method is as follows:

[0025] The standard quadratic programming form is as follows:

[0026] in, J The objective function for optimizing torque distribution across the four wheels; x is the longitudinal force matrix of the four wheels; µ The road surface adhesion coefficient; F xi The longitudinal force is applied to the four wheels. F zi The vertical load force on the four wheels. The H matrix is:

[0027] In the formula, B represents the matrix coefficients; W v These are the weighting coefficients; W i for r i ,Right now r fl , r fr , r rl and r rr ,in r fl and r fr For the front wheel coefficient, r rl and r rr Rear wheel coefficient, in

[0028] In the formula, r f0 and r r0 These are the original baseline weights; K s1 and K s2 As a weighting factor; Dr. This represents the weight reduction amount.

[0029] After the above operations are performed (i.e., after the soft intervention takes effect), if the vehicle returns to a safe state, the soft intervention disengages, and the electric power steering system resumes normal assistance. If the vehicle enters a dangerous state, the soft intervention disengages, and the electric power steering system resumes normal assistance, no longer hindering the driver's emergency rescue efforts. Simultaneously, information is sent to the torque distribution control module, introducing a hazard enhancement factor. s This enhances the strength of the yaw moment generated, working together with the driver to maintain stability.

[0030] Furthermore,

[0031] In the formula, F x_total As the overall driving force; DM z To add yaw moment; s As a hazard-enhancing factor, it refers to the factors that increase the risk of a vehicle becoming more dangerous, whether the vehicle is in a safe state or approaching a dangerous state. s =1, in

[0032] In the formula, K σ These are the weighting coefficients.

[0033] Compared with the prior art, the present invention has the following beneficial effects: 1. Existing technologies apply damping indiscriminately when a vehicle becomes unstable. While this avoids excessively rapid or large steering, it may cause cognitive aggression in the driver, affecting their correct correct intervention. This invention uses a first and second layer of conditions to determine the cause of instability, applying a soft intervention torque only when the driver makes an error, thus avoiding human-machine aggression.

[0034] 2. Existing technologies continue to intervene when danger escalates, and the intervention intensifies as danger increases, which hinders the driver's emergency rescue operations. This invention actively withdraws intervention when the vehicle enters a dangerous situation, reducing interference with the driver. At the same time, it enhances the direct yaw moment control of the distributed drive electric vehicle for active stabilization, realizing a switch from human-machine collaboration to automatic dominance. This not only does not hinder the driver's rescue efforts but also provides stronger stability control capabilities.

[0035] 3. Existing technologies do not fully utilize the corrective capabilities of active understeer. This invention abandons the traditional method of compensating through braking or steering via the vehicle's electronic stability system. Instead, it actively utilizes the advantages of understeer, combining it with the advantage of individually adjustable torque for each of the four wheels in a distributed drive electric vehicle. This, along with the soft interference torque of the steering wheel, more effectively suppresses the driver's tendency to oversteer.

[0036] 4. Existing technologies lack consideration for human characteristics and do not limit the amplitude of interference. This invention reduces driver error through soft interference, and the interference effect will not excessively increase driver discomfort and fatigue, thus improving operating comfort. Attached Figure Description

[0037] Figure 1 This is a diagram illustrating the control steps of the present invention; Figure 2 This is the control logic diagram of the present invention; Figure 3 This is the control flowchart of the present invention; Figure 4 The multidimensional hazard characterization factor of this invention SI Change diagram; Figure 5 This is the soft interference moment diagram of the present invention; Figure 6 This is a comparison diagram of the yaw rate of the present invention; Figure 7 This is a comparison diagram of the lateral acceleration of the present invention. Detailed Implementation

[0038] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. The illustrative embodiments and descriptions herein are used to explain the present invention, but are not intended to limit the present invention.

[0039] Example Combination Figure 1 As shown, this example provides a method for improving the safety of distributed drive electric vehicles through soft interference, as detailed below: S1. Constructing a Soft Interference Torque Term: In addition to the existing assist torque, self-centering torque, and basic damping terms in the EPS of a distributed drive electric vehicle, a new soft interference torque term is added. This term serves to alert the driver whether they are in the correct directional control when the vehicle's condition becomes dangerous. When the driver makes an incorrect directional adjustment, the soft interference torque is triggered, providing a direct and perceptible warning and limiting the driver's erroneous actions within a controllable range. Simultaneously, leveraging the advantages of distributed drive electric vehicles, the hub motors actively generate understeer to suppress the driver's oversteer input when certain conditions are met.

[0040] The formula for constructing the soft interference torque is as follows:

[0041] In the formula, M The torque that the electric power steering system ultimately exerts on the steering wheel; M N The sum of torques in the electric power steering system without soft interference torque, including power assist torque, return torque, and basic damping torque; M res This is the newly added soft interference torque.

[0042] S2, Design the first-level condition for triggering the soft interference torque: Construct a multi-dimensional state space. Constructing a multi-dimensional state space based on vehicle state parameters:

[0043]

[0044] in, , In the formula, µ The road surface adhesion coefficient; g It is the acceleration due to gravity; K 1 、K 2 and K 3 represents the weighting coefficient; v x The longitudinal speed of the vehicle; This refers to the vehicle's lateral acceleration. β It is the centroid sideslip angle; c This refers to the yaw rate; Constructing multidimensional hazard characterization factors based on a multidimensional state space SI :

[0045] In the formula, w 1 、w 2 、w 3 and w 4 represents the weighting coefficient. The multidimensional risk characterization factors SI As a parameter to determine whether the first-level conditions are met; The decision rules are set as the first-level conditions for soft interference. When the corresponding conditions are met, the first-level condition decision takes effect.

[0046] The judgment rules are as follows: when When the time is specified, it indicates that the vehicle is in a safe state and the electronic power steering system is providing normal assistance. when When the vehicle is approaching a dangerous state, the first-level condition judgment takes effect, the electronic power steering system provides normal assistance, and the wheel hub motor adjusts the front wheel load rate weight and the rear wheel load rate weight to generate active understeering to suppress the oversteering input when the driver operates correctly. when When this occurs, it indicates that the vehicle is in a dangerous state, and the electronic power steering system will only provide normal assistance.

[0047] S3. Design the second layer of conditions for triggering the soft interference torque: When this condition is met, it means that the driver is in a state of heightened danger, and the soft interference torque is triggered; when this condition is not met, it means that the driver is in a state of corrective action, and the soft interference torque is not triggered.

[0048] The second layer of conditions is as follows:

[0049] In the formula, The angular velocity of the steering wheel; For yaw rate error, When the function A value of 0 indicates that the driver is in the correct correction state and the soft interference torque is not triggered; when this function... A value of 1 indicates that the driver is in an escalating danger state, triggering the soft interference torque.

[0050] S4. Construct a soft interference moment model:

[0051] In the formula, - k adp For adaptive damping gain;M res This is the final generated soft interference torque; M max The maximum torque that allows the driver to turn the steering wheel without difficulty is the controllable limit to the driver's erroneous actions.

[0052] S5. Constructing a soft interference moment model with numerous parameters: Adaptive gain k adp The design is as follows:

[0053] In the formula, G base Base proportional gain; µ The road surface adhesion coefficient; α ( phase () is a weight mapping function that reflects the degree of danger of the vehicle's condition; Adaptive gain parameters f ( µ The expression form of ) is:

[0054] K µ The maximum road surface compensation coefficient is set between 1.5 and 2.0. Considering the impact of road conditions on the electric power steering system, when the road surface is very slippery, the steering wheel feel will become lighter (due to reduced tire return torque), making it easier for the driver to oversteer. Therefore, a road surface factor is introduced. f ( µ ), µ The smaller, f ( µ The larger the number of ) To effectively avoid frequent "hand-jamming" fluctuations in the controller near constraint boundaries, a multidimensional hazard characterization factor-based approach was constructed. SI The weighting mapping function of the index: Based on multidimensional risk characterization factors SI Construct the weight mapping function:

[0055] In the formula, when hour, , A smooth transition is achieved by using an S-curve based on the cosine function, ensuring the continuity of the gain coefficient on the first derivative. This eliminates the abruptness of damping intervention at the physical level and achieves seamless human-computer interaction. To avoid abrupt intervention and withdrawal of soft interference torque when transitioning to areas outside the danger zone, a similar weight mapping function can also be used for a smooth transition.

[0056] S6. Coordination between Design and Torque Distribution Layer: When both the first and second layer conditions are met simultaneously, the vehicle state tends towards danger, and the driver's directional input is incorrect, increasing the risk of danger. EPS soft interference torque is generated to visually alert the driver to the operational error. Simultaneously, the front and rear wheel load factor weights in the four-wheel torque optimization distribution are adjusted, increasing the front wheel driving force and decreasing the rear wheel driving force. This creates an active understeer trend in coordination with the steering wheel soft interference torque, thereby suppressing the driver's oversteer input. The specific implementation method is as follows: The method for adjusting the front wheel load rate weight and rear wheel load rate weight in the four-wheel torque optimization distribution is to decrease the front wheel coefficient distribution weight and increase the rear wheel coefficient distribution weight. The four-wheel torque distribution optimization objective function used in this method is as follows:

[0057] The standard quadratic programming form is as follows:

[0058] J The objective function for optimizing torque distribution across the four wheels; x is the longitudinal force matrix of the four wheels; µ The road surface adhesion coefficient; F xi The longitudinal force is applied to the four wheels. F zi The vertical load force on the four wheels. The H matrix is:

[0059] In the formula, B represents the matrix coefficients; W v These are the weighting coefficients; W i for r i ,Right now r fl , r fr , r rl and r rr ,in r fl and r fr For the front wheel coefficient, r rl and r rr Rear wheel coefficient, in

[0060] In the formula, r f0 and r r0 These are the original baseline weights; K s1 and K s2 As a weighting factor; Dr. This represents the weight reduction amount.

[0061] This embodiment provides a simple method for adjusting the driving force of the front and rear wheels, with the front wheel coefficient... r fl = r fr =1; r rl = r rr =10.

[0062] After performing the above operations, the vehicle returns to a safe state, the soft intervention disengages, and the EPS resumes normal power assist. If the vehicle enters a dangerous state, the soft intervention disengages, the EPS resumes normal power assist, no longer hindering the driver's emergency response, and simultaneously sends information to the torque distribution control module, introducing a hazard amplification factor. s This enhances the strength that generates yaw moment, working together with the driver to maintain stability. Specifically,

[0063] In the formula, F x_total As the overall driving force; DM z To add yaw moment; s As a hazard-enhancing factor, it refers to the factors that increase the risk of a vehicle becoming more dangerous, whether the vehicle is in a safe state or approaching a dangerous state. s =1, in

[0064] In the formula, K σ These are the weighting coefficients.

[0065] This embodiment provides a hazard enhancement factor. s The implementation method is as follows: when the vehicle is in a danger zone, s It is 1.5; when the vehicle is in other areas, s The value is 1.

[0066] v = Bx, where x is the longitudinal force matrix of the four wheels, and:

[0067] In the formula, the front wheel takes into account the turning angle. d Effect on torque arm; dw Wheelbase; F xfl This refers to the longitudinal force on the left front wheel; F xfr This refers to the longitudinal force on the right front wheel; F xrl The longitudinal force is on the left rear wheel; F xrr This is the longitudinal force on the right rear wheel.

[0068] The control logic of this embodiment is as follows: Figure 2 As shown, it specifically includes the following: The triggering conditions consist of two layers. Meeting the first layer indicates that the vehicle's condition is approaching danger. If the second layer is not met, it indicates that the vehicle's condition is approaching danger, but the driver's steering is correcting and reducing the danger. No soft interference torque is generated, the EPS provides normal assistance, and the wheel hub motors adjust the front and rear wheel load weights to generate active understeer to suppress excessive input when the driver is operating correctly. If the second layer is met, it indicates that the driver's steering is incorrect. The EPS generates soft interference torque, reminding the driver that the vehicle's dangerous condition is worsening and that the driver should counter-steer to correct the vehicle's condition. At the same time, the front and rear wheel weights in the four-wheel torque optimization distribution are adjusted to increase the front wheel driving force and decrease the rear wheel driving force, generating active understeer to suppress excessive input when the driver is operating correctly. When the first condition is not met, it indicates that the vehicle is in a dangerous or safe state. When in a safe state, the EPS provides normal assistance without soft interference. When in a dangerous state, it means that the vehicle was not successfully prevented from becoming dangerous. At this time, the soft interference is disengaged, the EPS resumes normal assistance, and no longer hinders the driver from taking emergency measures. At the same time, it sends information to the torque distribution control module to enhance the strength of the yaw moment and work with the driver to maintain stability.

[0069] like Figure 3 As shown, the control flow of this embodiment is as follows: (1) Estimate and observe the layers to obtain much of the necessary information; (2) Conditional judgment layer: based on multidimensional risk characterization factors SI The two layers of logical decision-making—whether the driver's direction of operation is correct—determine when soft intervention should intervene and when it should withdraw. (3) Command execution layer: executes the result of the condition judgment layer; (4) Interaction layer: vehicle interaction.

[0070] The method in this embodiment was verified using Simulink-CarSim co-simulation. The simulation was conducted using a co-simulation platform combining MATLAB R2022b / Simulink and CarSim 2024.1. The scenario was set as a double lane change operation with a longitudinal vehicle speed of 80 km / h and a road surface adhesion coefficient of [missing information]. µ = 0.85. Vehicle parameters are shown in the table below:

[0071] Some graphics obtained through Simulink-CarSim co-simulation are shown below. Figure 4 , Figure 5 , Figure 6 as well as Figure 7 As shown. Among them Figure 4 for SI A graph showing the changes in the index; Figure 5 This is a graph showing the variation of the soft interference torque. Figure 6 Comparison curves of ideal yaw rate with no control applied in the danger zone and with enhanced additional yaw moment control applied in the danger zone; Figure 7 The figure above shows the lateral acceleration curves when no control is applied when the situation is approaching danger and when understeering control is actively applied when the situation is approaching danger; this figure confirms the effectiveness of the method in this patent.

[0072] Depend on Figure 4 and Figure 6 It can be seen that the vehicle undergoes two large-angle steering and straightening processes. Figure 6 When the vehicle's yaw rate is at its peak, the vehicle is in the danger zone; the area near the peak is closer to the danger zone. This is consistent with... Figure 4 The vehicle status corresponds perfectly.

[0073] Figure 4 There were four dangerous phases, but Figure 5 The soft interference torque was generated only twice, because on both occasions the driver was in the correct correction state and the soft interference torque was zero. This confirms the accuracy of the control logic in this application.

[0074] Figure 6 The black line represents the yaw rate curve without control applied in the danger zone, and the red line represents the yaw rate curve with enhanced additional yaw moment control applied in the danger zone. It can be seen that the yaw rate with enhanced additional yaw moment control applied in the danger zone reaches its peak earlier and is lower. This confirms that the peak yaw rate of the vehicle of the present invention is lower and the vehicle stability is higher.

[0075] Figure 7 The black line represents the lateral acceleration when no control is applied when the vehicle is approaching danger, while the red line represents the lateral acceleration when understeering control is actively applied when the vehicle is approaching danger. As can be seen, the lateral acceleration when control is applied is lower, and the vehicle stability is better, which reflects the effectiveness of the control.

Claims

1. A method for improving the safety of distributed drive electric vehicles through soft interference, characterized in that, Includes the following steps: (1) Obtain initial parameters, including data from the vehicle's electronic power steering system, vehicle parameters, and road surface parameters; (2) Determine whether the soft interference triggering condition is met; (3) When the soft interference triggering condition is not met, the electronic power steering system provides normal assistance; (4) When the soft interference triggering condition is met, soft interference is generated. The soft interference includes soft interference torque and active understeering. The soft interference limits the driver's oversteering input and corrects the driver's wrong operation. (5) After the above steps, if the vehicle enters a dangerous state, the soft interference will be disengaged, the electronic power steering system will resume normal power assistance, and at the same time, information will be sent to the torque distribution control module to enhance the strength of the yaw moment generated, and stabilize the vehicle together with the driver, and return to step (1). If the vehicle returns to a safe state, the soft intervention is disengaged, the electronic power steering system resumes normal power assistance, and the process returns to step (1).

2. The method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 1, characterized in that, The soft interference triggering conditions include a first-level condition and a second-level condition.

3. The method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 2, characterized in that, The conditions for the first layer are as follows. Constructing a multi-dimensional state space based on vehicle state parameters: in, , In the formula, µ The road surface adhesion coefficient; g It is the acceleration due to gravity; K 1 、K 2 and K 3 represents the weighting coefficient; v x The longitudinal speed of the vehicle; This refers to the vehicle's lateral acceleration. β It is the centroid sideslip angle; γ This refers to the yaw rate; Constructing multidimensional hazard characterization factors based on a multidimensional state space SI : In the formula, w 1 、w 2 、w 3 and w 4 represents the weighting coefficient. The multidimensional risk characterization factors SI This serves as a parameter to determine whether the first-level conditions are met.

4. The method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 3, characterized in that, The multidimensional risk characterization factors SI The judgment rule is: when When the time is specified, it indicates that the vehicle is in a safe state and the electronic power steering system is providing normal assistance. when When the vehicle is approaching a dangerous state, the first condition takes effect, the electronic power steering system provides normal assistance, and the hub motor adjusts the front wheel load rate weight and the rear wheel load rate weight to generate active understeering to suppress the oversteering input when the driver operates correctly. when When this occurs, it indicates that the vehicle is in a dangerous state, and the electronic power steering system will only provide normal assistance.

5. A method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 4, characterized in that, The method for generating active understeer by adjusting the front wheel load factor weight and the rear wheel load factor weight is to reduce the front wheel coefficient allocation weight and increase the rear wheel coefficient allocation weight. The four-wheel torque distribution optimization objective function used in this method is as follows: The standard quadratic programming form is as follows: in, J The objective function for optimizing torque distribution across the four wheels; x is the longitudinal force matrix of the four wheels; µ The road surface adhesion coefficient; F xi For the four wheels longitudinally; F zi The vertical load force on the four wheels. The H matrix is: In the formula, B represents the matrix coefficients; W v These are the weighting coefficients; W i for ρ i ,Right now ρ fl , ρ fr , ρ rl and ρ rr ,in ρ fl and ρ fr For the front wheel coefficient, ρ rl and ρ rr Rear wheel coefficient; After performing the above operations, if the vehicle returns to a safe state, the soft intervention disengages, and the electric power steering system resumes normal assistance. If the vehicle enters a dangerous state, the soft intervention disengages, the electric power steering system resumes normal assistance, no longer hindering the driver's emergency rescue efforts, and simultaneously sends information to the torque distribution control module, introducing a hazard enhancement factor. σ This enhances the strength of the yaw moment generated, working together with the driver to maintain stability.

6. A method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 5, characterized in that, In the formula, F x_total As the overall driving force; ΔM z To add yaw moment; σ As a hazard-enhancing factor, it refers to the factors that increase the risk of a vehicle becoming more dangerous, whether the vehicle is in a safe state or approaching a dangerous state. σ The value is 1.

7. A method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 2, characterized in that, The second layer of conditions is as follows: In the formula, The angular velocity of the steering wheel; For yaw rate error, When the function A value of 0 indicates that the driver is in the correct correction state and the soft interference torque is not triggered; when this function... A value of 1 indicates that the driver is in an escalating danger state, triggering the soft interference torque.

8. A method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 1, characterized in that, The formula for constructing the soft interference torque is as follows: In the formula, M The torque that the electric power steering system ultimately exerts on the steering wheel; M N The sum of torques in the electric power steering system without soft interference torque, including power assist torque, return torque, and basic damping torque; M res This is the newly added soft interference torque.

9. A method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 1, characterized in that, The model for the soft interference torque is as follows: In the formula, - k adp For adaptive damping gain; M res This is the final generated soft interference torque; M max The maximum torque that allows the driver to turn the steering wheel without difficulty is the controllable limit to the driver's erroneous actions.

10. A method for improving the safety of a distributed drive electric vehicle through soft interference according to claim 9, characterized in that, The adaptive damping gain is In the formula, G base Base proportional gain; µ The road surface adhesion coefficient; α ( phase () is a weight mapping function that reflects the degree of danger of the vehicle's condition; in, K µ The maximum road surface compensation coefficient is set between 1.5 and 2.

0. Considering the impact of road conditions on the electric power steering system, when the road surface is very slippery, the steering wheel will feel lighter, making it easier for the driver to oversteer. Therefore, a road surface factor is introduced. f ( µ ), µ The smaller, f ( µ The larger the number of ) Based on multidimensional risk characterization factors SI Construct the weight mapping function: In the formula, when hour, .

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