Electric control optimization method for modification of cross-country chassis vehicle

Abstract

The invention discloses an off-road chassis vehicle refitting electronic control optimization method, and particularly relates to the technical field of electronic control optimization. The number of times of opening and closing of an electronic differential lock is counted in a fixed sliding window, and the moving locking frequency is calculated; short-time yaw rate abnormal fluctuation information in the high-frequency locking state is obtained, a short-time yaw rate abnormal fluctuation coefficient is calculated, meanwhile, wheel slip rate adjustment information is collected to calculate a wheel slip rate adjustment coefficient, and then an abnormal steering angle change coefficient is calculated in combination with obtained steering angle change information; according to the short-time yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient and the abnormal steering angle change coefficient, a vehicle body stability system misjudgment interference model is constructed, and a vehicle body stability system misjudgment interference index is output; real-time and accurate evaluation of the misjudgment interference degree of the electronic differential lock in the high-frequency locking state on the vehicle body stabilization system is achieved, and the ESP system misjudgment risk caused by high-frequency locking is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic control optimization, and more particularly to an electronic control optimization method for refitting an off-road chassis vehicle. Background Art

[0002] Off-road vehicles are prone to single-sided wheel slippage or suspension when navigating extreme terrain (such as mud, gravel, and steep slopes). To improve off-road maneuverability, electronic differential locks are widely used. These locks utilize a solenoid valve or motor-driven clutch to rigidly connect the slipping wheel with the non-slipping wheel, improving traction. However, in complex operating conditions, the electronic differential lock can frequently engage and disengage, leading to a series of technical issues.

[0003] First, the short-term dynamic signals caused by frequent locking (such as instantaneous wheel slip, wheel speed changes, and yaw rate fluctuations) can be highly similar to signs of vehicle loss of control, leading to misjudgments by the Electronic Stability Program (ESP). Upon misjudging the vehicle's loss of control, the ESP system proactively triggers forced braking to restore driving stability. However, in off-road environments, this ESP intervention often conflicts with the electronic differential lock's traction optimization strategy, resulting in traction interruption, impairing escape capability, and even causing power loss in critical scenarios, rendering the vehicle unable to continue forward. Furthermore, frequent braking interventions caused by ESP misjudgments generate additional mechanical stress, placing additional strain on the braking and transmission systems and increasing vehicle maintenance costs. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an electronic control optimization method for off-road chassis vehicle modification to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for optimizing electronic control of an off-road chassis vehicle modification comprises the following steps: Step S1, obtaining the number of times the electronic differential lock is switched on and off within a fixed sliding window, and calculating the mobile locking frequency of the electronic differential lock, and determining whether the electronic differential lock has entered a high-frequency locking state based on the mobile locking frequency; Step S2, obtaining short-term yaw rate abnormal fluctuation information when the electronic differential lock is in a high-frequency locking state, and calculating a short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information; Step S3, obtaining wheel slip rate adjustment information when the electronic differential lock is in a high-frequency locking state, and calculating a wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information; Step S4, obtaining steering angle change information when the electronic differential lock is in a high-frequency locking state, and calculating an abnormal steering angle change coefficient based on the steering angle change information; Step S5: constructing a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle variation coefficient, outputting a vehicle stability system misjudgment interference index, and evaluating the degree of misjudgment interference to the vehicle stability system caused by the electronic differential lock being in a high-frequency locking state.

[0006] In a preferred embodiment, the number of times the electronic differential lock is switched on and off is obtained within a fixed sliding window, and the mobile locking frequency of the electronic differential lock is calculated, as follows: ,in express The moving locking frequency of the electronic differential lock at all times, represents the sliding window size, Indicates the The number of times the electronic differential lock is switched on and off at any given moment; The moving locking frequency of the electronic differential lock is compared with the preset moving locking frequency threshold to determine whether the electronic differential lock has entered the high-frequency locking state, as follows: If the movement locking frequency of the electronic differential lock is greater than the movement locking frequency threshold, it means that the electronic differential lock enters the high-frequency locking state; if the movement locking frequency of the electronic differential lock is less than or equal to the movement locking frequency threshold, it means that the electronic differential lock is in the normal locking state and no intervention is required.

[0007] In a preferred embodiment, by acquiring information about abnormal short-term yaw rate fluctuations when the electronic differential lock is in a high-frequency locking state, analyzing the severity of the yaw rate fluctuations in the high-frequency locking state of the electronic differential lock, and calculating a short-term abnormal yaw rate fluctuation coefficient, the severity of the yaw rate fluctuations in the high-frequency locking state of the electronic differential lock is measured; The logic for obtaining the short-term yaw rate abnormal fluctuation coefficient is as follows: When the electronic differential lock is in the high-frequency locking state, the vehicle's yaw rate data is collected to obtain the yaw rate data sequence: ,in Indicates the The angular velocity of the vehicle around the vertical axis at each sampling point, , is a positive integer; Calculate the yaw rate standard deviation: ,in represents the standard deviation of the yaw rate, represents the average yaw rate, ; Calculate the short-term yaw rate abnormal fluctuation coefficient: ,in represents the short-term yaw rate abnormal fluctuation coefficient, Represents a very small positive value, used to avoid the denominator being equal to 0.

[0008] In a preferred embodiment, wheel slip adjustment information is obtained when the electronic differential lock is in a high-frequency locking state, the dynamic impact of the electronic differential lock in the high-frequency locking state on the vehicle driving force distribution is analyzed, and a wheel slip adjustment coefficient is calculated to measure the degree of dynamic impact of the electronic differential lock in the high-frequency locking state on the vehicle driving force distribution; The logic for obtaining the wheel slip adjustment coefficient is as follows: Obtain wheel linear speed from vehicle-mounted sensors , vehicle longitudinal speed ; Calculate the slip rate of each wheel based on the longitudinal speed of the vehicle: ,in Indicates the The slip rate of each wheel, Indicates the The linear speed of each wheel; calculate the adjustment of the slip rate before and after locking: ,in Indicates the The adjustment amount of the slip rate before and after the wheels are locked, Indicates the The slip rate of each wheel before locking, Indicates the The slip rate of each wheel after locking; calculate the wheel imbalance coefficient: ,in represents the wheel imbalance coefficient, Indicates the Adjustment of the slip rate before and after each wheel is locked , ,and , Is a positive integer; calculate the wheel slip adjustment coefficient: ,in Indicates the wheel slip adjustment coefficient, It is the average value of the adjustment amount of the slip rate before and after all wheels are locked.

[0009] In a preferred embodiment, by acquiring steering angle change information when the electronic differential lock is in a high-frequency locking state, the influence of the electronic differential lock in the high-frequency locking state on the vehicle steering stability is analyzed, and the abnormal steering angle change coefficient is calculated to measure the influence of the electronic differential lock in the high-frequency locking state on the vehicle steering stability; The logic for obtaining the abnormal steering angle change coefficient is as follows: Get the instantaneous steering angle when the electronic differential lock is in high-frequency locking state , steering angular velocity , steering angular acceleration ; The Morlet wavelet function is selected as the mother wavelet function and continuous wavelet transform is used to extract the high-frequency energy of abnormal steering angles: ,in represents the steering angle wavelet coefficient, represents the mother wavelet function, represents the scale parameter, , is a positive integer, represents the time shift parameter, Indicates the unit of time, Indicates high-frequency energy of abnormal steering angle; Calculate the chaotic coefficient of steering angle: ,in represents the chaotic coefficient of the steering angle, Indicates the The instantaneous steering angle at time Indicates the The instantaneous steering angle at time , is a positive integer; Calculate the abnormal steering angle variation coefficient: ,in Indicates the abnormal steering angle variation coefficient, The root mean square value of the steering angular acceleration is: , They represent the high-frequency energy of abnormal steering angle, the root mean square value of steering angle acceleration, and the preset proportional coefficient of steering angle chaos coefficient, respectively, and Both are greater than 0.

[0010] In a preferred embodiment, a vehicle body stability system misjudgment interference model is constructed based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, and a vehicle body stability system misjudgment interference index is output. The model is based on the following formula , where They represent the preset proportional coefficients of the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, respectively, and Both are greater than 0.

[0011] In a preferred embodiment, the vehicle stability system misjudgment interference index is compared with a preset vehicle stability system misjudgment interference index threshold to evaluate the misjudgment interference degree of the vehicle stability system caused by the electronic differential lock in the high-frequency locking state, as follows: If the vehicle body stability system misjudgment interference index is greater than the vehicle body stability system misjudgment interference index threshold, a misjudgment warning signal is generated; if the vehicle body stability system misjudgment interference index is less than or equal to the vehicle body stability system misjudgment interference index threshold, no misjudgment warning signal needs to be generated.

[0012] Technical effects and advantages of the present invention: 1. By counting the number of electronic differential lock (EDL) activations and deactivations within a fixed sliding window and calculating the frequency of mobile locking, the system captures short-term yaw rate fluctuation information and calculates the short-term yaw rate fluctuation coefficient during high-frequency locking. Wheel slip adjustment information is also collected to calculate the wheel slip adjustment coefficient, which is then combined with the acquired steering angle variation information to calculate the abnormal steering angle variation coefficient. A body stability system misjudgment interference model is constructed based on the short-term yaw rate fluctuation coefficient, wheel slip adjustment coefficient, and abnormal steering angle variation coefficient, and a body stability system misjudgment interference index is output. This system provides real-time and accurate assessment of the degree of misjudgment interference with the body stability system during high-frequency EDL locking. This effectively reduces the risk of ESP system misjudgment caused by high-frequency locking, preventing unnecessary braking and traction loss. It also optimizes traction distribution, improving the vehicle's ability to escape and maneuver in extreme terrain. It also reduces wear on electronic and mechanical components and reduces system maintenance costs, ultimately ensuring enhanced dynamic stability and handling safety in complex road conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 Flowchart of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0015] Example: Figure 1 The present invention provides an electronic control optimization method for off-road chassis vehicle modification, comprising the following steps: Step S1, obtaining the number of times the electronic differential lock is switched on and off within a fixed sliding window, and calculating the mobile locking frequency of the electronic differential lock, and determining whether the electronic differential lock has entered a high-frequency locking state based on the mobile locking frequency; Step S2, obtaining short-term yaw rate abnormal fluctuation information when the electronic differential lock is in a high-frequency locking state, and calculating a short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information; Step S3, obtaining wheel slip rate adjustment information when the electronic differential lock is in a high-frequency locking state, and calculating a wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information; Step S4, obtaining steering angle change information when the electronic differential lock is in a high-frequency locking state, and calculating an abnormal steering angle change coefficient based on the steering angle change information; Step S5: constructing a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle variation coefficient, outputting a vehicle stability system misjudgment interference index to assess the degree of misjudgment interference to the vehicle stability system when the electronic differential lock is in a high-frequency locking state; The number of times the electronic differential lock is switched on and off within a fixed sliding window is obtained, and the mobile locking frequency of the electronic differential lock is calculated as follows: ,in express The moving locking frequency of the electronic differential lock at all times, represents the sliding window size, Indicates the The number of times the electronic differential lock is switched on and off at any given moment; It should be noted that the above formulas are all dimensionless and numerical calculations. Common dimensionless methods include Min-Max normalization and Z-Score normalization, which will not be described here. The moving locking frequency of the electronic differential lock is compared with the preset moving locking frequency threshold to determine whether the electronic differential lock has entered the high-frequency locking state, as follows: If the movement locking frequency of the electronic differential lock is greater than the movement locking frequency threshold, it means that the electronic differential lock enters the high-frequency locking state; if the movement locking frequency of the electronic differential lock is less than or equal to the movement locking frequency threshold, it means that the electronic differential lock is in the normal locking state and the system can continue to operate normally without intervention.

[0016] Step S2, obtaining short-term yaw rate abnormal fluctuation information when the electronic differential lock is in a high-frequency locking state, and calculating a short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information; The short-term yaw rate abnormal fluctuation coefficient in the present invention is used to measure the severity of yaw rate fluctuations in the high-frequency locking state of the electronic differential lock and the degree of interference with the vehicle stability system. A larger short-term yaw rate abnormal fluctuation coefficient indicates that the yaw rate changes drastically in a short period of time, indicating that frequent locking / releasing of the electronic differential lock causes vehicle posture instability, which may cause the ESP to misjudge the vehicle as out of control and trigger forced braking. A smaller short-term yaw rate abnormal fluctuation coefficient indicates that the yaw rate fluctuation is relatively stable, indicating that the intervention of the electronic differential lock has a smaller impact on vehicle stability and is less likely to cause ESP misjudgment. Assessing the degree of misjudgment interference with the vehicle stability system in the high-frequency locking state of the electronic differential lock based on the short-term yaw rate abnormal fluctuation coefficient helps optimize the control strategy of the electronic differential lock, reduce misjudgment intervention of the ESP system, and improve the stability and passability of off-road vehicles in complex road conditions. Therefore, by acquiring information about abnormal short-term yaw rate fluctuations when the electronic differential lock is in a high-frequency locking state, the severity of the yaw rate fluctuations in this state is analyzed, and the abnormal short-term yaw rate fluctuation coefficient is calculated to measure the severity of the yaw rate fluctuations in this state. The logic for obtaining the short-term yaw rate abnormal fluctuation coefficient is as follows: When the electronic differential lock is in the high-frequency locking state, the vehicle's yaw rate data is collected to obtain the yaw rate data sequence: ,in Indicates the The angular velocity of the vehicle around the vertical axis at each sampling point, , is a positive integer; It should be noted that the vehicle's yaw rate data includes the vehicle's rotational angular velocity around the vertical axis; Calculate the yaw rate standard deviation: ,in represents the standard deviation of the yaw rate, represents the average yaw rate, ; Calculate the short-term yaw rate abnormal fluctuation coefficient: ,in represents the short-term yaw rate abnormal fluctuation coefficient, Represents the smallest positive value, used to avoid the denominator being equal to 0; It should be noted that the above formulas are all dimensionless and numerical calculations. Common dimensionless methods include Min-Max normalization and Z-Score normalization, which will not be described here. Step S3, obtaining wheel slip rate adjustment information when the electronic differential lock is in a high-frequency locking state, and calculating a wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information; The wheel slip adjustment coefficient in the present invention is used to measure the dynamic influence of the electronic differential lock on the vehicle driving force distribution in the high-frequency locking state. A larger wheel slip adjustment coefficient indicates that there is still a large left-right wheel speed difference or unbalanced driving force distribution after the electronic differential lock is locked, which may cause ESP to misjudge that the vehicle is out of control and trigger brake intervention, thereby causing traction interruption and power loss; a smaller wheel slip adjustment coefficient indicates that the electronic differential lock has a better inhibitory effect on wheel slip, the left and right wheel speeds tend to be consistent, the driving force is evenly distributed, and the probability of ESP misjudgment is reduced, thereby ensuring the stability and escape ability of the vehicle in complex working conditions. Evaluating the degree of misjudgment interference of the electronic differential lock in the high-frequency locking state on the vehicle stability system based on the wheel slip adjustment coefficient is helpful to optimize the electronic differential lock control strategy, reduce unnecessary ESP intervention, and improve the vehicle's passability and control safety in off-road environments; Therefore, by obtaining wheel slip adjustment information when the electronic differential lock is in a high-frequency locking state, the dynamic impact of the electronic differential lock in this high-frequency locking state on the vehicle's driving force distribution is analyzed, and the wheel slip adjustment coefficient is calculated to measure the degree of dynamic impact of the electronic differential lock in this high-frequency locking state on the vehicle's driving force distribution; The logic for obtaining the wheel slip adjustment coefficient is as follows: Obtain wheel linear speed from vehicle-mounted sensors , vehicle longitudinal speed ; Calculate the slip rate of each wheel based on the longitudinal speed of the vehicle: ,in Indicates the The slip rate of each wheel, Indicates the The linear speed of each wheel; calculate the adjustment of the slip rate before and after locking: ,in Indicates the The adjustment amount of the slip rate before and after the wheels are locked, Indicates the The slip rate of each wheel before locking, Indicates the The slip rate of each wheel after locking; calculate the wheel imbalance coefficient: ,in represents the wheel imbalance coefficient, Indicates the Adjustment of the slip rate before and after each wheel is locked , ,and , Is a positive integer; calculate the wheel slip adjustment coefficient: ,in Indicates the wheel slip adjustment coefficient, To calculate the average of the slip rate adjustments before and after all wheels are locked; It should be noted that the above formulas are all dimensionless and numerical calculations. Common dimensionless methods include Min-Max normalization and Z-Score normalization, which will not be described here. Step S4, obtaining steering angle change information when the electronic differential lock is in a high-frequency locking state, and calculating an abnormal steering angle change coefficient based on the steering angle change information; In the present invention, the abnormal steering angle variation coefficient is used to measure the influence of the electronic differential lock in a high-frequency locking state on the vehicle steering stability. A larger abnormal steering angle variation coefficient indicates that the frequent locking of the electronic differential lock causes the steering angle to fluctuate violently, making the vehicle direction control unstable, which may induce the body stability system (ESP) to misjudge that the vehicle is out of control, thereby triggering unnecessary braking intervention and affecting driving smoothness; a smaller abnormal steering angle variation coefficient indicates that the electronic differential lock has a smaller dynamic influence on the vehicle steering angle, the ESP system has a lower risk of misjudgment, and the vehicle can maintain stable directional control. Evaluating the degree of misjudgment interference of the electronic differential lock in a high-frequency locking state on the body stability system based on the abnormal steering angle variation coefficient can effectively optimize the coordinated control strategy of the electronic differential lock and the ESP system, reduce unnecessary braking intervention, and improve the handling stability and passability of off-road vehicles.

[0017] Therefore, by acquiring the steering angle change information when the electronic differential lock is in a high-frequency locking state, the impact of the electronic differential lock in this high-frequency locking state on the vehicle's steering stability is analyzed, and the abnormal steering angle change coefficient is calculated to measure the degree of impact of the electronic differential lock in this high-frequency locking state on the vehicle's steering stability; The logic for obtaining the abnormal steering angle change coefficient is as follows: Get the instantaneous steering angle when the electronic differential lock is in high-frequency locking state , steering angular velocity , steering angular acceleration ; It should be noted that the steering angular velocity is calculated by the first-order difference: ,in represents the instantaneous steering angle at the g-th moment, represents the instantaneous steering angle at the g-1th moment, represents the time interval; the steering angular acceleration is calculated by the second-order difference: ,in represents the steering angular velocity at the g-th moment, represents the steering angular velocity at the g-1th moment; The Morlet wavelet function is selected as the mother wavelet function and continuous wavelet transform is used to extract the high-frequency energy of abnormal steering angles: ,in represents the steering angle wavelet coefficient, represents the mother wavelet function, represents the scale parameter, , is a positive integer, represents the time shift parameter, Indicates the unit of time, Indicates high-frequency energy of abnormal steering angle; It should be noted that a large high-frequency energy of abnormal steering angle indicates a drastic change in abnormal steering angle, which may induce ESP misjudgment; Calculate the chaotic coefficient of steering angle: ,in represents the chaotic coefficient of the steering angle, Indicates the The instantaneous steering angle at time Indicates the The instantaneous steering angle at time , is a positive integer; It should be noted that a larger steering angle chaos coefficient indicates that the steering angle change presents chaotic characteristics, and the risk of ESP misjudgment is higher; a smaller steering angle chaos coefficient indicates that the system change is more stable, and the risk of ESP misjudgment is lower; Calculate the abnormal steering angle variation coefficient: ,in Indicates the abnormal steering angle variation coefficient, The root mean square value of the steering angular acceleration is: , They represent the high-frequency energy of abnormal steering angle, the root mean square value of steering angle acceleration, and the preset proportional coefficient of steering angle chaos coefficient, respectively, and All greater than 0; It should be noted that the above formulas are all dimensionless and numerical calculations. Common dimensionless methods include Min-Max normalization and Z-Score normalization, which will not be described here. Set it according to the actual situation. For example, adopt the expert empowerment method, that is, invite experts in related fields to determine the preset proportion coefficients of various indicators through professional opinion surveys and comprehensive evaluations, for example, It can be 0.4, 0.2, 0.4; Step S5: constructing a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle variation coefficient, outputting a vehicle stability system misjudgment interference index to assess the degree of misjudgment interference to the vehicle stability system when the electronic differential lock is in a high-frequency locking state; According to the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, a vehicle body stability system misjudgment interference model is constructed, and the vehicle body stability system misjudgment interference index is output. The model is based on the following formula , where They represent the preset proportional coefficients of the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, respectively, and All greater than 0; It should be noted that the above formulas are all dimensionless and numerical calculations. Common dimensionless methods include Min-Max normalization and Z-Score normalization, which will not be described here. Set it according to the actual situation. For example, adopt the expert empowerment method, that is, invite experts in related fields to determine the preset proportion coefficients of various indicators through professional opinion surveys and comprehensive evaluations, for example, It can be 0.3, 0.4, 0.3; The above calculation expression shows that the larger the short-term yaw rate abnormal fluctuation coefficient, the larger the wheel slip rate adjustment coefficient, and the larger the abnormal steering angle variation coefficient, the larger the body stability system misjudgment interference index, indicating that the body stability system is subject to a higher degree of misjudgment interference and the high-frequency locking state of the electronic differential lock has a more significant impact on the vehicle's dynamic stability, potentially leading to ESP false triggering and affecting vehicle handling safety. Conversely, the smaller the short-term yaw rate abnormal fluctuation coefficient, the smaller the wheel slip rate adjustment coefficient, and the smaller the abnormal steering angle variation coefficient, the smaller the body stability system misjudgment interference index, indicating that the high-frequency locking state of the electronic differential lock is within a reasonable range and does not significantly interfere with the ESP system. The vehicle stability system misjudgment interference index is compared with the preset vehicle stability system misjudgment interference index threshold to evaluate the degree of misjudgment interference to the vehicle stability system when the electronic differential lock is in a high-frequency locking state, as follows: If the body stability system misjudgment interference index is greater than the body stability system misjudgment interference index threshold, it means that the electronic differential lock is in a high-frequency locking state, and the system has generated strong interference, causing the body stability system to easily misjudgment the vehicle as out of control and generate a misjudgment warning signal. If the body stability system misjudgment interference index is less than or equal to the body stability system misjudgment interference index threshold, it means that the electronic differential lock has little interference with the body stability system in the high-frequency locking state, and the system can effectively avoid misjudgment and correctly respond to the vehicle status, without generating a misjudgment warning signal. The present invention counts the number of times the electronic differential lock is switched on and off within a fixed sliding window and calculates the mobile locking frequency, obtains short-term yaw rate abnormal fluctuation information under a high-frequency locking state and calculates the short-term yaw rate abnormal fluctuation coefficient, simultaneously collects wheel slip adjustment information to calculate the wheel slip adjustment coefficient, and then calculates the abnormal steering angle variation coefficient in combination with the obtained steering angle variation information. A vehicle body stability system misjudgment interference model is constructed based on the short-term yaw rate abnormal fluctuation coefficient, the wheel slip adjustment coefficient, and the abnormal steering angle variation coefficient, and a vehicle body stability system misjudgment interference index is output, thereby achieving real-time and accurate assessment of the degree of misjudgment interference of the electronic differential lock on the vehicle stability system under a high-frequency locking state. This can effectively reduce the risk of ESP system misjudgment caused by high-frequency locking, prevent unnecessary braking and traction interruption, optimize the vehicle's traction distribution, improve the off-road vehicle's escape ability and passability in extreme terrain, and reduce the wear of electronic components and mechanical parts and system maintenance costs, ultimately ensuring that the vehicle has higher dynamic stability and control safety under complex road conditions. The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0018] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0019] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for optimizing electronic control for off-road chassis vehicle modification, characterized by: The steps include: Step S1, obtaining the number of times the electronic differential lock is switched on and off within a fixed sliding window, and calculating the mobile locking frequency of the electronic differential lock, and determining whether the electronic differential lock has entered a high-frequency locking state based on the mobile locking frequency; Step S2, obtaining short-term yaw rate abnormal fluctuation information when the electronic differential lock is in a high-frequency locking state, and calculating a short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information; Step S3, obtaining wheel slip rate adjustment information when the electronic differential lock is in a high-frequency locking state, and calculating a wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information; Step S4, obtaining steering angle change information when the electronic differential lock is in a high-frequency locking state, and calculating an abnormal steering angle change coefficient based on the steering angle change information; Step S5: constructing a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle variation coefficient, outputting a vehicle stability system misjudgment interference index, and evaluating the degree of misjudgment interference to the vehicle stability system caused by the electronic differential lock being in a high-frequency locking state.

2. The method for optimizing electronic control of an off-road chassis vehicle modification according to claim 1, characterized in that: The number of times the electronic differential lock is switched on and off within a fixed sliding window is obtained, and the mobile locking frequency of the electronic differential lock is calculated as follows: ,in express The moving locking frequency of the electronic differential lock at all times, represents the sliding window size, Indicates the The number of times the electronic differential lock is switched on and off at any given moment; The moving locking frequency of the electronic differential lock is compared with the preset moving locking frequency threshold to determine whether the electronic differential lock has entered the high-frequency locking state, as follows: If the movement locking frequency of the electronic differential lock is greater than the movement locking frequency threshold, it means that the electronic differential lock enters the high-frequency locking state; if the movement locking frequency of the electronic differential lock is less than or equal to the movement locking frequency threshold, it means that the electronic differential lock is in the normal locking state and no intervention is required.

3. The electronic control optimization method for off-road chassis vehicle modification according to claim 1, characterized in that: By acquiring information about abnormal short-term yaw rate fluctuations when the electronic differential lock is in a high-frequency locking state, the severity of the yaw rate fluctuations in this state is analyzed, and the abnormal short-term yaw rate fluctuation coefficient is calculated to measure the severity of the yaw rate fluctuations in this state. The logic for obtaining the short-term yaw rate abnormal fluctuation coefficient is as follows: When the electronic differential lock is in the high-frequency locking state, the vehicle's yaw rate data is collected to obtain the yaw rate data sequence: ,in Indicates the The angular velocity of the vehicle around the vertical axis at each sampling point, , is a positive integer; Calculate the yaw rate standard deviation: ,in represents the standard deviation of the yaw rate, represents the average yaw rate, ; Calculate the short-term yaw rate abnormal fluctuation coefficient: ,in represents the short-term yaw rate abnormal fluctuation coefficient, Represents a very small positive value, used to avoid the denominator being equal to 0.

4. The method for optimizing electronic control of an off-road chassis vehicle modification according to claim 1, characterized in that: By acquiring wheel slip adjustment information when the electronic differential lock is in a high-frequency locking state, the dynamic impact of the electronic differential lock in this high-frequency locking state on the vehicle's driving force distribution is analyzed, and the wheel slip adjustment coefficient is calculated to measure the degree of dynamic impact of the electronic differential lock in this high-frequency locking state on the vehicle's driving force distribution; The logic for obtaining the wheel slip adjustment coefficient is as follows: Obtain wheel linear speed from vehicle-mounted sensors , vehicle longitudinal speed ; Calculate the slip rate of each wheel based on the longitudinal speed of the vehicle: ,in Indicates the The slip rate of each wheel, Indicates the The linear speed of each wheel; calculate the adjustment of the slip rate before and after locking: ,in Indicates the The adjustment amount of the slip rate before and after the wheels are locked, Indicates the The slip rate of each wheel before locking, Indicates the The slip rate of each wheel after locking; calculate the wheel imbalance coefficient: ,in represents the wheel imbalance coefficient, Indicates the Adjustment of the slip rate before and after each wheel is locked , ,and , Is a positive integer; calculate the wheel slip adjustment coefficient: ,in Indicates the wheel slip adjustment coefficient, It is the average value of the adjustment amount of the slip rate before and after all wheels are locked.

5. The electronic control optimization method for off-road chassis vehicle modification according to claim 1, characterized in that: By acquiring steering angle change information when the electronic differential lock is in a high-frequency locking state, the impact of the electronic differential lock in this high-frequency locking state on the vehicle's steering stability is analyzed, and the abnormal steering angle change coefficient is calculated to measure the degree of impact of the electronic differential lock in this high-frequency locking state on the vehicle's steering stability; The logic for obtaining the abnormal steering angle change coefficient is as follows: Get the instantaneous steering angle when the electronic differential lock is in high-frequency locking state , steering angular velocity , steering angular acceleration ; The Morlet wavelet function is selected as the mother wavelet function and continuous wavelet transform is used to extract the high-frequency energy of abnormal steering angles: ,in represents the steering angle wavelet coefficient, represents the mother wavelet function, represents the scale parameter, , is a positive integer, represents the time shift parameter, Indicates the unit of time, Indicates high-frequency energy of abnormal steering angle; Calculate the chaotic coefficient of steering angle: ,in represents the chaotic coefficient of the steering angle, Indicates the The instantaneous steering angle at time Indicates the The instantaneous steering angle at time , is a positive integer; Calculate the abnormal steering angle variation coefficient: ,in Indicates the abnormal steering angle variation coefficient, The root mean square value of the steering angular acceleration is: , They represent the high-frequency energy of abnormal steering angle, the root mean square value of steering angle acceleration, and the preset proportional coefficient of steering angle chaos coefficient, respectively, and Both are greater than 0.

6. The method for optimizing electronic control of an off-road chassis vehicle modification according to claim 1, characterized in that: According to the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, a vehicle body stability system misjudgment interference model is constructed, and the vehicle body stability system misjudgment interference index is output. The model is based on the following formula , where They represent the preset proportional coefficients of the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, respectively, and Both are greater than 0.

7. The method for optimizing electronic control of an off-road chassis vehicle modification according to claim 6, characterized in that: The vehicle stability system misjudgment interference index is compared with the preset vehicle stability system misjudgment interference index threshold to evaluate the degree of misjudgment interference to the vehicle stability system when the electronic differential lock is in a high-frequency locking state, as follows: If the vehicle body stability system misjudgment interference index is greater than the vehicle body stability system misjudgment interference index threshold, a misjudgment warning signal is generated; if the vehicle body stability system misjudgment interference index is less than or equal to the vehicle body stability system misjudgment interference index threshold, no misjudgment warning signal needs to be generated.

Images