Off-road chassis vehicle retrofit electronic control optimization method

Abstract

This invention discloses an electronic control optimization method for modifying off-road chassis vehicles, specifically relating to the field of electronic control optimization technology. By statistically analyzing the number of times the electronic differential lock switches on and off within a fixed sliding window and calculating the moving locking frequency, short-term yaw rate abnormal fluctuation information under high-frequency locking is obtained, and a short-term yaw rate abnormal fluctuation coefficient is calculated. Simultaneously, wheel slip rate adjustment information is collected to calculate the wheel slip rate adjustment coefficient. Combined with the obtained steering angle change information, an abnormal steering angle change coefficient is calculated. Based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, a vehicle stability system misjudgment interference model is constructed, and a vehicle stability system misjudgment interference index is output. This achieves real-time and accurate assessment of the degree of misjudgment interference to the vehicle stability system under high-frequency locking of the electronic differential lock, effectively reducing the risk of ESP system misjudgment caused by high-frequency locking.

Description

Technical Field

[0001] This invention relates to the field of electronic control optimization technology, and more specifically, to a method for optimizing the electronic control of off-road chassis vehicles. Background Technology

[0002] When off-road vehicles travel on extreme terrains (such as mud, gravel, and steep slopes), one wheel is prone to slipping or becoming suspended in the air. To improve off-road capability, electronic differential locks are widely used. These locks use a solenoid valve or motor to drive a clutch, rigidly connecting the slipping wheel to the non-slipping wheel, thus increasing traction. However, under complex operating conditions, electronic differential locks may frequently lock and release, leading to a series of technical problems.

[0003] First, the short-term dynamic signals caused by high-frequency locking (such as instantaneous wheel slippage, wheel speed changes, and yaw rate fluctuations) may be highly similar to vehicle loss-of-control signals, leading to misjudgments by the Electronic Stability Program (ESP). When the ESP system misjudges that the vehicle has entered a loss-of-control state, it will actively trigger forced braking to restore driving stability. However, in off-road environments, this intervention by ESP often conflicts with the traction optimization strategy of the electronic differential lock, resulting in traction interruption, affecting the ability to get out of trouble, and even causing power loss in critical scenarios, preventing the vehicle from moving forward. Furthermore, the braking intervention caused by frequent ESP misjudgments generates additional mechanical stress, subjecting the braking and transmission systems to additional impacts and increasing vehicle maintenance costs. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an electronic control optimization method for modifying off-road chassis vehicles to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for optimizing the electronic control system of an off-road chassis vehicle includes the following steps:

[0007] Step S1: Obtain the number of times the electronic differential lock is switched within a fixed sliding window, calculate the moving locking frequency of the electronic differential lock, and determine whether the electronic differential lock has entered the high-frequency locking state based on the moving locking frequency.

[0008] Step S2: Obtain short-term yaw rate abnormal fluctuation information when the electronic differential lock is in high-frequency locking state, and calculate the short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information.

[0009] Step S3: Obtain wheel slip rate adjustment information when the electronic differential lock is in high-frequency locking state, and calculate the wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information;

[0010] Step S4: Obtain steering angle change information when the electronic differential lock is in high-frequency locking state, and calculate the abnormal steering angle change coefficient based on the steering angle change information;

[0011] Step S5: Construct a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient; output the vehicle stability system misjudgment interference index; and evaluate the degree of misjudgment interference of the electronic differential lock in high-frequency locking state on the vehicle stability system.

[0012] 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 movement locking frequency of the electronic differential lock is calculated, as follows: ,in express The movement locking frequency of the electronic differential lock. Indicates the size of the sliding window. Indicates the first The number of times the electronic differential lock is switched on and off at any given time;

[0013] The electronic differential lock's movement locking frequency is compared with a preset movement locking frequency threshold to determine whether the electronic differential lock has entered a high-frequency locking state, as detailed below:

[0014] If the moving locking frequency of the electronic differential lock is greater than the moving locking frequency threshold, it indicates that the electronic differential lock has entered a high-frequency locking state; if the moving locking frequency of the electronic differential lock is less than or equal to the moving locking frequency threshold, it indicates that the electronic differential lock is in a normal locking state and no intervention is required.

[0015] In a preferred embodiment, by acquiring short-term abnormal yaw rate fluctuation information of the electronic differential lock in a high-frequency locking state, the severity of yaw rate fluctuation in the high-frequency locking state of the electronic differential lock is analyzed, and the short-term abnormal yaw rate fluctuation coefficient is calculated to measure the severity of yaw rate fluctuation in the high-frequency locking state of the electronic differential lock.

[0016] The logic for obtaining the abnormal fluctuation coefficient of short-term yaw rate is as follows:

[0017] With the electronic differential lock in high-frequency locking mode, the vehicle's yaw rate data is collected to obtain a yaw rate data sequence: ,in Indicates the first The angular velocity of the vehicle's rotation about the vertical axis at each sampling point. , It is a positive integer;

[0018] Calculate the standard deviation of the yaw rate: ,in Indicates the standard deviation of the yaw rate. This represents the average yaw rate. ; Calculate the short-term yaw rate abnormal fluctuation coefficient: ,in This represents the coefficient of abnormal fluctuation in short-term yaw rate. This represents a very small positive value and is used to avoid the denominator being equal to 0.

[0019] In a preferred embodiment, by acquiring the wheel slip rate adjustment information of the electronic differential lock in the high-frequency locking state, the dynamic impact of the electronic differential lock on the distribution of vehicle driving force in the high-frequency locking state is analyzed, and the wheel slip rate adjustment coefficient is calculated to measure the degree of dynamic impact of the electronic differential lock on the distribution of vehicle driving force in the high-frequency locking state.

[0020] The logic for obtaining the wheel slippage rate adjustment coefficient is as follows:

[0021] Obtaining wheel linear velocity from onboard sensors longitudinal speed of the vehicle body ; Calculate the slip rate of each wheel based on the longitudinal speed of the vehicle body: ,in Indicates the first The slippage rate of each wheel Indicates the first The linear velocity of each wheel; the adjustment amount for calculating the slippage rate before and after locking: ,in Indicates the first The adjustment amount for the slippage rate before and after locking each wheel. Indicates the first The slippage rate before the wheel is locked. Indicates the first The slippage rate of each wheel after locking; calculating the wheel imbalance coefficient: ,in This represents the wheel imbalance coefficient. Indicates the first Adjustment amount for slippage rate before and after locking each wheel , ,and , For positive integers; calculate the wheel slippage rate adjustment factor: ,in This represents the wheel slippage rate adjustment coefficient. This is to calculate the average adjustment amount for the slippage rate before and after locking all wheels.

[0022] In a preferred embodiment, by acquiring the steering angle change information of the electronic differential lock in a high-frequency locking state, the impact of the electronic differential lock in a 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 a high-frequency locking state on the vehicle's steering stability.

[0023] The logic for obtaining the abnormal steering angle change coefficient is as follows:

[0024] Obtain the instantaneous steering angle of the electronic differential lock when it is in high-frequency locking state. angular velocity of steering angular acceleration ;

[0025] The Morlet wavelet function was selected as the mother wavelet function, and continuous wavelet transform was used to extract high-frequency energy of the abnormal turning angle. ,in Represents the wavelet coefficients of the steering angle. Represents the mother wavelet function. Indicates the scale parameter. , It is a positive integer. Indicates the time shift parameter. This indicates high-frequency energy at abnormal steering angles;

[0026] Calculate the chaos coefficient of the steering angle: ,in Indicates the chaos coefficient of the steering angle. Indicates the first The instantaneous turning angle at any given moment. Indicates the first The instantaneous turning angle at any given moment. , It is a positive integer;

[0027] Calculate the abnormal steering angle variation coefficient: ,in Indicates the coefficient of abnormal steering angle change. The root mean square value of the steering angular acceleration: , These represent the high-frequency energy of the abnormal steering angle, the root mean square value of the steering angle acceleration, and the preset proportional coefficient of the steering angle chaos coefficient, respectively. All are greater than 0.

[0028] In a preferred embodiment, a vehicle stability system misjudgment interference model is constructed based on the short-time yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle change coefficient, and the vehicle stability system misjudgment interference index is output. The model is based on the following formula: In the formula These represent the preset proportional coefficients for the short-term yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle change coefficient, respectively. All are greater than 0.

[0029] 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 degree of misjudgment interference of the electronic differential lock in a high-frequency locking state on the vehicle stability system, as follows:

[0030] If the misjudgment interference index of the vehicle stability system is greater than the misjudgment interference index threshold of the vehicle stability system, a misjudgment warning signal will be generated; if the misjudgment interference index of the vehicle stability system is less than or equal to the misjudgment interference index threshold of the vehicle stability system, no misjudgment warning signal needs to be generated.

[0031] The technical effects and advantages of this invention are as follows:

[0032] 1. By counting the number of times the electronic differential lock is switched on and off within a fixed sliding window and calculating the moving locking frequency, short-term yaw rate abnormal fluctuation information under high-frequency locking is obtained, and the short-term yaw rate abnormal fluctuation coefficient is calculated. At the same time, wheel slip rate adjustment information is collected to calculate the wheel slip rate adjustment coefficient. Combined with the obtained steering angle change information, the abnormal steering angle change coefficient is calculated. Based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, a vehicle stability system misjudgment interference model is constructed, and the vehicle stability system misjudgment interference index is output. This enables real-time and accurate assessment of the degree of misjudgment interference to the vehicle stability system under high-frequency locking of the electronic differential lock. This can effectively reduce the risk of ESP system misjudgment caused by high-frequency locking, prevent unnecessary braking and traction interruption, optimize vehicle traction distribution, improve the off-road vehicle's ability to get out of trouble and passability in extreme terrain, reduce the wear of electronic components and mechanical parts and system maintenance costs, and ultimately ensure that the vehicle has higher dynamic stability and handling safety in complex road conditions. Attached Figure Description

[0033] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0034] Figure 1 This is a flowchart of a method according to an embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Example: Figure 1 This invention provides a method for optimizing the electronic control system of an off-road chassis vehicle, comprising the following steps:

[0037] Step S1: Obtain the number of times the electronic differential lock is switched within a fixed sliding window, calculate the moving locking frequency of the electronic differential lock, and determine whether the electronic differential lock has entered the high-frequency locking state based on the moving locking frequency.

[0038] Step S2: Obtain short-term yaw rate abnormal fluctuation information when the electronic differential lock is in high-frequency locking state, and calculate the short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information.

[0039] Step S3: Obtain wheel slip rate adjustment information when the electronic differential lock is in high-frequency locking state, and calculate the wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information;

[0040] Step S4: Obtain steering angle change information when the electronic differential lock is in high-frequency locking state, and calculate the abnormal steering angle change coefficient based on the steering angle change information;

[0041] Step S5: Construct a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient; output the vehicle stability system misjudgment interference index; and evaluate the degree of misjudgment interference of the electronic differential lock in the high-frequency locking state on the vehicle stability system.

[0042] The number of times the electronic differential lock opens and closes within a fixed sliding window is obtained, and the movement locking frequency of the electronic differential lock is calculated, as follows: ,in express The movement locking frequency of the electronic differential lock. Indicates the size of the sliding window. Indicates the first The number of times the electronic differential lock is switched on and off at any given time;

[0043] It should be noted that the above formulas are all dimensionless calculations. Commonly used methods for removing dimensions include Min-Max normalization and Z-Score standardization, which will not be elaborated here.

[0044] The electronic differential lock's movement locking frequency is compared with a preset movement locking frequency threshold to determine whether the electronic differential lock has entered a high-frequency locking state, as detailed below:

[0045] If the moving locking frequency of the electronic differential lock is greater than the moving locking frequency threshold, it indicates that the electronic differential lock has entered a high-frequency locking state; if the moving locking frequency of the electronic differential lock is less than or equal to the moving locking frequency threshold, it indicates that the electronic differential lock is in a normal locking state, and the system can continue to operate normally without intervention.

[0046] Step S2: Obtain short-term yaw rate abnormal fluctuation information when the electronic differential lock is in high-frequency locking state, and calculate the short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information.

[0047] In this invention, the short-term yaw rate abnormal fluctuation coefficient is used to measure the severity of yaw rate fluctuations and its interference with the vehicle stability system under high-frequency locking conditions of the electronic differential lock. A larger short-term yaw rate abnormal fluctuation coefficient indicates that the yaw rate changes drastically in a short period of time, suggesting that frequent locking / unlocking of the electronic differential lock leads to vehicle instability, which may cause the ESP to misjudge the vehicle as out of control and trigger forced braking. Conversely, a smaller short-term yaw rate abnormal fluctuation coefficient indicates that the yaw rate fluctuation is relatively stable, suggesting 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 of the electronic differential lock under high-frequency locking conditions based on the short-term yaw rate abnormal fluctuation coefficient helps to optimize the control strategy of the electronic differential lock, reduce ESP system misjudgment intervention, and improve the stability and passability of off-road vehicles in complex road conditions.

[0048] Therefore, by acquiring short-term abnormal yaw rate fluctuation information of the electronic differential lock in high-frequency locking state, the severity of yaw rate fluctuation in the high-frequency locking state of the electronic differential lock is analyzed, and the short-term abnormal yaw rate fluctuation coefficient is calculated to measure the severity of yaw rate fluctuation in the high-frequency locking state of the electronic differential lock.

[0049] The logic for obtaining the abnormal fluctuation coefficient of short-term yaw rate is as follows:

[0050] With the electronic differential lock in high-frequency locking mode, the vehicle's yaw rate data is collected to obtain a yaw rate data sequence: ,in Indicates the first The angular velocity of the vehicle's rotation about the vertical axis at each sampling point. , It is a positive integer;

[0051] It should be noted that the vehicle's yaw rate data includes the vehicle's rotational angular velocity about its vertical axis.

[0052] Calculate the standard deviation of the yaw rate: ,in Indicates the standard deviation of the yaw rate. This represents the average yaw rate. ; Calculate the short-term yaw rate abnormal fluctuation coefficient: ,in This represents the coefficient of abnormal fluctuation in short-term yaw rate. This represents a very small positive value, used to avoid the denominator being equal to 0;

[0053] It should be noted that the above formulas are all dimensionless calculations. Commonly used methods for removing dimensions include Min-Max normalization and Z-Score standardization, which will not be elaborated here.

[0054] Step S3: Obtain wheel slip rate adjustment information when the electronic differential lock is in high-frequency locking state, and calculate the wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information;

[0055] In this invention, the wheel slip rate adjustment coefficient is used to measure the dynamic impact of the electronic differential lock on the distribution of vehicle driving force under high-frequency locking conditions. A larger wheel slip rate adjustment coefficient indicates that there is still a large difference in the speed of the left and right wheels or an unbalanced distribution of driving force after the electronic differential lock is locked, which may cause the ESP to misjudge the vehicle as out of control and trigger braking intervention, thereby causing traction interruption and power loss. A smaller wheel slip rate adjustment coefficient indicates that the electronic differential lock has a better effect on suppressing wheel slip, the speed of the left and right wheels tends to be consistent, the driving force is evenly distributed, and the probability of ESP misjudgment is reduced, thereby ensuring the stability and traction of the vehicle under complex working conditions. Evaluating the degree of misjudgment interference of the electronic differential lock under high-frequency locking conditions based on the wheel slip rate adjustment coefficient helps to optimize the electronic differential lock control strategy, reduce unnecessary ESP intervention, and improve the vehicle's passability and handling safety in off-road environments.

[0056] Therefore, by acquiring the wheel slip rate adjustment information of the electronic differential lock in the high-frequency locking state, the dynamic impact of the electronic differential lock on the distribution of vehicle driving force in the high-frequency locking state is analyzed, and the wheel slip rate adjustment coefficient is calculated to measure the degree of dynamic impact of the electronic differential lock on the distribution of vehicle driving force in the high-frequency locking state.

[0057] The logic for obtaining the wheel slippage rate adjustment coefficient is as follows:

[0058] Obtaining wheel linear velocity from onboard sensors longitudinal speed of the vehicle body ; Calculate the slip rate of each wheel based on the longitudinal speed of the vehicle body: ,in Indicates the first The slippage rate of each wheel Indicates the first The linear velocity of each wheel; the adjustment amount for calculating the slippage rate before and after locking: ,in Indicates the first The adjustment amount for the slippage rate before and after locking each wheel. Indicates the first The slippage rate before the wheel is locked. Indicates the first The slippage rate of each wheel after locking; calculating the wheel imbalance coefficient: ,in This represents the wheel imbalance coefficient. Indicates the first Adjustment amount for slippage rate before and after locking each wheel , ,and , For positive integers; calculate the wheel slippage rate adjustment factor: ,in This represents the wheel slippage rate adjustment coefficient. To calculate the average adjustment amount for slippage rate before and after locking all wheels;

[0059] It should be noted that the above formulas are all dimensionless calculations. Commonly used methods for removing dimensions include Min-Max normalization and Z-Score standardization, which will not be elaborated here.

[0060] Step S4: Obtain steering angle change information when the electronic differential lock is in high-frequency locking state, and calculate the abnormal steering angle change coefficient based on the steering angle change information;

[0061] In this invention, the abnormal steering angle variation coefficient is used to measure the impact of the electronic differential lock in a high-frequency locking state on the vehicle's steering stability. A larger abnormal steering angle variation coefficient indicates that frequent locking of the electronic differential lock causes drastic fluctuations in the steering angle, making the vehicle's directional control unstable. This may induce the Electronic Stability Program (ESP) to misjudge the vehicle as 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 impact on the vehicle's steering angle, the ESP system has a lower risk of misjudgment, and the vehicle can maintain stable directional control. Assessing the degree of interference of the electronic differential lock in a high-frequency locking state on the ESP system based on the abnormal steering angle variation coefficient can effectively optimize the collaborative 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.

[0062] Therefore, by acquiring information on the change in steering angle when the electronic differential lock is in a high-frequency locking state, the impact of the electronic differential lock in a 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 a high-frequency locking state on the vehicle's steering stability.

[0063] The logic for obtaining the abnormal steering angle change coefficient is as follows:

[0064] Obtain the instantaneous steering angle of the electronic differential lock when it is in high-frequency locking state. angular velocity of steering angular acceleration ;

[0065] It should be noted that the steering angular velocity is calculated using a first-order difference: ,in This represents the instantaneous turning angle at time g. This represents the instantaneous turning angle at time g-1. Indicates the time interval; the steering angular acceleration is calculated using the second-order difference: ,in This represents the turning angular velocity at time g. This represents the turning angular velocity at time g-1;

[0066] The Morlet wavelet function was selected as the mother wavelet function, and continuous wavelet transform was used to extract high-frequency energy of the abnormal turning angle. ,in Represents the wavelet coefficients of the steering angle. Represents the mother wavelet function. Indicates the scale parameter. , It is a positive integer. Indicates the time shift parameter. This indicates high-frequency energy at abnormal steering angles;

[0067] It should be noted that high-frequency energy at a large abnormal steering angle indicates a drastic change in the abnormal steering angle, which may trigger a false alarm by the ESP.

[0068] Calculate the chaos coefficient of the steering angle: ,in Indicates the chaos coefficient of the steering angle. Indicates the first The instantaneous turning angle at any given moment. Indicates the first The instantaneous turning angle at any given moment. , It is a positive integer;

[0069] It should be noted that a larger chaos coefficient in the steering angle indicates that the change in steering angle exhibits chaotic characteristics, and the risk of ESP misjudgment is higher; a smaller chaos coefficient in the steering angle indicates that the system changes more stably, and the risk of ESP misjudgment is lower.

[0070] Calculate the abnormal steering angle variation coefficient: ,in Indicates the coefficient of abnormal steering angle change. The root mean square value of the steering angular acceleration: , These represent the high-frequency energy of the abnormal steering angle, the root mean square value of the steering angle acceleration, and the preset proportional coefficient of the steering angle chaos coefficient, respectively. All are greater than 0;

[0071] It should be noted that the above formulas are all dimensionless calculations. Commonly used methods for removing dimensions include Min-Max normalization and Z-Score standardization, which will not be elaborated here. The settings should be tailored to the specific circumstances. For example, an expert-empowered approach could be adopted, where experts in relevant fields are invited to determine the pre-defined proportions for each indicator through professional opinion surveys and comprehensive evaluations. It can be 0.4, 0.2, or 0.4;

[0072] Step S5: Construct a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient; output the vehicle stability system misjudgment interference index; and evaluate the degree of misjudgment interference of the electronic differential lock in the high-frequency locking state on the vehicle stability system.

[0073] A vehicle 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 the vehicle stability system misjudgment interference index is output. The model is based on the following formula: In the formula These represent the preset proportional coefficients for the short-term yaw rate abnormal fluctuation coefficient, the wheel slip rate adjustment coefficient, and the abnormal steering angle change coefficient, respectively. All are greater than 0;

[0074] It should be noted that the above formulas are all dimensionless calculations. Commonly used methods for removing dimensions include Min-Max normalization and Z-Score standardization, which will not be elaborated here. The settings should be tailored to the specific circumstances. For example, an expert-empowered approach could be adopted, where experts in relevant fields are invited to determine the pre-defined proportions for each indicator through professional opinion surveys and comprehensive evaluations. It can be 0.3, 0.4, or 0.3;

[0075] As can be seen from the above calculation expressions, 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 change coefficient, the larger the vehicle stability system misjudgment interference index, indicating that the vehicle stability system is subject to a higher degree of misjudgment interference. The high-frequency locking state of the electronic differential lock has a more significant impact on the dynamic stability of the vehicle, which may lead to ESP false triggering and affect the vehicle's 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 change coefficient, the smaller the vehicle stability system misjudgment interference index, indicating that the high-frequency locking of the electronic differential lock is within a reasonable range and does not significantly interfere with the ESP system.

[0076] The misjudgment interference index of the vehicle stability system is compared with the preset misjudgment interference index threshold of the vehicle stability system to evaluate the degree of misjudgment interference of the electronic differential lock in the high-frequency locking state on the vehicle stability system, as follows:

[0077] If the misjudgment interference index of the vehicle stability system is greater than the threshold of the vehicle stability system misjudgment interference index, it means that the electronic differential lock is in a high-frequency locking state, and the system generates strong interference, causing the vehicle stability system to easily misjudge the vehicle as out of control and generate a misjudgment warning signal; if the misjudgment interference index of the vehicle stability system is less than or equal to the threshold of the vehicle stability system misjudgment interference index, it means that the electronic differential lock has less interference to the vehicle stability system in a high-frequency locking state, and the system can effectively avoid misjudgment and respond correctly to the vehicle status, without generating a misjudgment warning signal.

[0078] This invention obtains short-term yaw rate abnormal fluctuation information and calculates the short-term yaw rate abnormal fluctuation coefficient by counting the number of times the electronic differential lock is switched on and off within a fixed sliding window and calculating the moving locking frequency within a fixed sliding window. At the same time, it collects wheel slip rate adjustment information to calculate the wheel slip rate adjustment coefficient. Then, it combines the obtained steering angle change information to calculate the abnormal steering angle change coefficient. Based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient, it constructs a vehicle stability system misjudgment interference model and outputs the vehicle stability system misjudgment interference index. This enables real-time and accurate assessment of the degree of misjudgment interference of the electronic differential lock on the vehicle stability system under high-frequency locking conditions. It 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 ability to get out of trouble and pass through in extreme terrain, reduce the wear and tear of electronic components and mechanical parts and system maintenance costs, and ultimately ensure that the vehicle has higher dynamic stability and handling safety in complex road conditions.

[0079] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0080] It should be understood that, in the various embodiments of this application, the order of the above-mentioned processes does not imply 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 this application.

[0081] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for optimizing the electronic control system of an off-road chassis vehicle, characterized in that: Includes the following steps: Step S1: Obtain the number of times the electronic differential lock is switched within a fixed sliding window, calculate the moving locking frequency of the electronic differential lock, and determine whether the electronic differential lock has entered the high-frequency locking state based on the moving locking frequency. Step S2: Obtain short-term yaw rate abnormal fluctuation information when the electronic differential lock is in high-frequency locking state, and calculate the short-term yaw rate abnormal fluctuation coefficient based on the short-term yaw rate abnormal fluctuation information. Step S3: Obtain wheel slip rate adjustment information when the electronic differential lock is in high-frequency locking state, and calculate the wheel slip rate adjustment coefficient based on the wheel slip rate adjustment information; Step S4: Obtain steering angle change information when the electronic differential lock is in high-frequency locking state, and calculate the abnormal steering angle change coefficient based on the steering angle change information; Step S5: Construct a vehicle stability system misjudgment interference model based on the short-term yaw rate abnormal fluctuation coefficient, wheel slip rate adjustment coefficient, and abnormal steering angle change coefficient; output the vehicle stability system misjudgment interference index; and evaluate the degree of misjudgment interference of the electronic differential lock in high-frequency locking state on the vehicle stability system.

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

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

4. The method for optimizing the electronic control system of an off-road chassis vehicle according to claim 1, characterized in that: By acquiring wheel slip rate adjustment information when the electronic differential lock is in high-frequency locking state, the dynamic impact of the electronic differential lock on the distribution of vehicle driving force in high-frequency locking state is analyzed, and the wheel slip rate adjustment coefficient is calculated to measure the degree of dynamic impact of the electronic differential lock on the distribution of vehicle driving force in high-frequency locking state. The logic for obtaining the wheel slippage rate adjustment coefficient is as follows: Obtaining wheel linear velocity from onboard sensors longitudinal speed of the vehicle body ; Calculate the slip rate of each wheel based on the longitudinal speed of the vehicle body: ,in Indicates the first The slippage rate of each wheel Indicates the first The linear velocity of each wheel; the adjustment amount for calculating the slippage rate before and after locking: ,in Indicates the first The adjustment amount for the slippage rate before and after locking each wheel. Indicates the first The slippage rate before the wheel is locked. Indicates the first The slippage rate of each wheel after locking; calculating the wheel imbalance coefficient: ,in This represents the wheel imbalance coefficient. Indicates the first Adjustment amount for slippage rate before and after locking each wheel , ,and , For positive integers; calculate the wheel slippage rate adjustment factor: ,in This represents the wheel slippage rate adjustment coefficient. This is to calculate the average adjustment amount for the slippage rate before and after locking all wheels.

5. The method for optimizing the electronic control system of an off-road chassis vehicle according to claim 1, characterized in that: By acquiring information on the change in steering angle when the electronic differential lock is in a high-frequency locking state, the impact of the electronic differential lock in a 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 a high-frequency locking state on the vehicle's steering stability. The logic for obtaining the abnormal steering angle change coefficient is as follows: Obtain the instantaneous steering angle of the electronic differential lock when it is in high-frequency locking state. angular velocity of steering angular acceleration ; The Morlet wavelet function was selected as the mother wavelet function, and continuous wavelet transform was used to extract high-frequency energy of the abnormal turning angle. ,in Represents the wavelet coefficients of the steering angle. Represents the mother wavelet function. Indicates the scale parameter. , It is a positive integer. Indicates the time shift parameter. This indicates high-frequency energy at abnormal steering angles; Calculate the chaos coefficient of the steering angle: ,in Indicates the chaos coefficient of the steering angle. Indicates the first The instantaneous turning angle at any given moment. Indicates the first The instantaneous turning angle at any given moment. , It is a positive integer; Calculate the abnormal steering angle variation coefficient: ,in Indicates the coefficient of abnormal steering angle change. The root mean square value of the steering angular acceleration: , These represent the high-frequency energy of the abnormal steering angle, the root mean square value of the steering angle acceleration, and the preset proportional coefficient of the steering angle chaos coefficient, respectively. All are greater than 0.

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

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

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