Crawler center steering performance evaluation method based on real vehicle data

Abstract

The invention belongs to the technical field of real vehicle test data processing of electromechanical composite transmission systems of special vehicles, and particularly relates to a tracked vehicle center steering performance evaluation method based on real vehicle data. Comprising the steps of real vehicle test data conversion processing, central steering global index position determination and frequency statistics, central steering stable rotating speed point determination and central steering index time calculation. According to the method, the center steering performance of the tracked vehicle can be accurately evaluated based on accurate analysis of real vehicle data of the electromechanical composite transmission system of the special vehicle. According to the method, test data is deeply processed, key features of center steering are recognized, the sliding window technology and standard deviation judgment are combined, conversion from fluctuation to a stable state is effectively captured, and steering performance indexes are accurately determined. According to the method, the accuracy of center steering evaluation is improved, and a scientific basis is provided for performance optimization of the special vehicle.

Description

Technical Field

[0001] The present invention belongs to the technical field of real vehicle test data processing of special vehicle electromechanical composite transmission system, and specifically relates to a tracked vehicle center steering performance evaluation method based on real vehicle data, which is suitable for data processing and index performance evaluation of special vehicle electromechanical composite system. Background Art

[0002] In today's complex military and engineering environments, the operational performance of special vehicles, especially the maneuverability and flexibility of tracked vehicles, is particularly important. Given that these vehicles need to perform tasks under changing and harsh conditions, superior center steering capabilities are indispensable to ensure that they can adjust and respond quickly and effectively in various strategic environments. However, traditional evaluation methods have various limitations in experimental environment, data collection and data analysis, resulting in deficiencies in the accuracy and real-time nature of the evaluation results. Therefore, how to evaluate the center steering performance of tracked vehicles with higher accuracy and efficiency has become an urgent need.

[0003] With the advancement of technology, the popularity of mechatronic transmission systems in special vehicles has provided opportunities for this. These systems can greatly improve the dynamic performance of vehicles by efficiently converting mechanical energy into electrical energy, especially when performing complex maneuvers such as center turns. However, to fully realize the potential of these systems, they need to be supported by sophisticated data analysis under actual operating conditions.

[0004] The rapid development of big data technology and modern signal processing methods has provided an innovative path for the scientific evaluation of special vehicle performance. Through the precise collection and analysis of real vehicle data, it is possible to study the performance of vehicles under different driving and operating conditions. Specifically, in-depth exploration of the relationship between driver control behavior and vehicle response will reveal the dynamic characteristics and performance change characteristics of tracked vehicles during center turns, thereby providing valuable information for the optimization of vehicle design and control strategies.

[0005] In this context, the present invention proposes a center steering performance evaluation method based on real vehicle data, which breaks through the limitations of traditional means. By introducing technologies such as sliding window traversal and signal feature capture, the center steering behavior characteristics of the vehicle under real operating conditions are effectively extracted. By accurately mapping the signal change position and the vehicle dynamic position point, this method significantly improves the accuracy of center steering feature recognition and provides a scientific basis for the objective evaluation of vehicle performance indicators. The implementation of this technology can not only improve the mobility and resilience assessment level of military vehicles, but also provide guidance for the performance optimization of special vehicles in other complex application fields. Summary of the invention

[0006] 1. Technical issues to be resolved

[0007] The technical problem to be solved by the present invention is: in the actual vehicle test environment of the electro-mechanical composite transmission system of special vehicles, how to effectively extract and analyze the characteristics of the central steering performance from a vast amount of data. This task involves key issues such as identifying the data change characteristics during the central steering phase, determining the occurrence time and frequency of central steering, and precisely correlating the position information of central steering with the dynamic performance of the vehicle.

[0008] The present invention proposes a method for evaluating the central steering performance of tracked vehicles based on actual vehicle data. By applying the sliding window technology combined with the signal characterization analysis strategy, it focuses on solving the problems of inaccurate identification of the central steering position, complexity of performance index calculation, and low data processing efficiency in traditional methods, thus providing a solution that achieves a balance between accuracy and efficiency.

[0009] This method realizes the accurate and rapid evaluation of the central steering performance of the vehicle by deeply analyzing the central steering data of the tracked vehicle during actual operation. The sliding window traversal technology is used to monitor the signal changes in real time and identify the significant characteristics of the data during the central steering process, accurately locating the starting point and ending point of central steering. Combining data mapping and performance time calculation, this method can detail the central steering performance of the vehicle under different working conditions and provide important performance indicators such as the number of central steerings and the average steering time.

[0010] Through this technical solution, the present invention not only improves the accuracy and efficiency of central steering performance evaluation, but also provides a scientific basis for the performance optimization of special vehicles. It can effectively help designers discover potential problems in central steering characteristics, providing solid data support for optimizing vehicle control strategies and improving performance. This method lays a foundation for the performance evaluation of special vehicles under complex working conditions and promotes the further development of related technical fields.

[0011] (2) Technical solution

[0012] To solve the above technical problems, the present invention provides a method for evaluating the central steering performance of tracked vehicles based on actual vehicle data, and the method includes the following steps:

[0013] Step 1: Conversion and processing of actual vehicle test data;

[0014] Step 2: Determination of the global index position of central steering and statistics of the number of times;

[0015] Step 3: Determination of the stable rotation speed point of central steering;

[0016] Step 4: Calculation of the central steering index time.

[0017] Among them, in the above Step 1, the conversion and processing of actual vehicle test data are carried out;

[0018] Collect the operation data of the electro-mechanical composite drive system under different working conditions during the real vehicle test; the original data formats collected from the real vehicle are usually diverse and inconsistent, so format conversion is required to ensure that all data has a consistent format, including timestamp synchronization, multi-source data fusion, and data regeneration, to obtain the left and right drive motor speed curves.

[0019] Among them, in the step 1, collect the operation data of the electro-mechanical composite drive system under different working conditions during the real vehicle test; the data includes: the left drive motor speed signal EMT_SpdL, the right drive motor speed signal EMT_SpdR, and the gear position signal EMT_Gear.

[0020] Among them, in the step 2, determine the global index position of the center turn and count the number of times.

[0021] Analyze the differences in the drive motor speed performance between the center turn and the turn, analyze the recognition features of the center turn curve, and obtain the center turn judgment conditions; for the left and right drive motor speed curves obtained in step 1, adopt the method of combining a sliding window with logical judgment and cyclic traversal search. First, find the points where the speed signs of the left and right drive motors are opposite and the speed difference is relatively small, remember the position index of this point, and use the sliding window cyclic traversal method to search forward along the time axis to find the point where the sliding window is all zero, and find the position of the last zero point, so as to find the global index position point of the center turn, and increment the corresponding center turn count by one.

[0022] Among them, in the step 2, through a loop, extract a window of a specific size from the left drive motor speed EMT_SpdL and the right drive motor speed EMT_SpdR signals; ensure that the window does not exceed the signal range, and obtain the window values of the left drive motor speed EMT_SpdL and the right drive motor speed EMT_SpdR by cyclic traversal. Judge whether there are elements with different signs in the window values, check whether the absolute values of all elements in the window values are greater than 50, calculate the absolute value difference of the window, if all the differences are less than 150, and if all the above conditions are met, continue with an additional search operation. Starting from the current index position, search forward along the time axis for up to 100 points. During the search, find a window containing zero in EMT_SpdL; for each possible window, the length of the window is fixed at 100 and it moves one grid forward each time, check whether the window contains zero elements; if a zero point is found, record the last position of the zero point and jump out of the search loop; after finding the zero point, the position variable will be updated to the position of the zero point, and the inner loop will be exited to stop further search;

[0023] If the zero point search returns a valid position, search for the characteristics of the signal backward from the zero point position; start from the position before the zero point, record this starting position, and increment the count of the number of turns.

[0024] Among them, in the said step 2, the logic of the method for determining the global index position of the center turn and counting the number of times is summarized as follows: extract a window that meets specific conditions from the signal. If this window meets the requirements of different signal signs, large absolute values, and small differences, further search whether there is a zero point among the positions before this window, and record the position of this zero point; if no zero point meeting the conditions is found, it will remain in the empty state.

[0025] Among them, in the said step 3, determine the stable rotation speed point of the center turn;

[0026] Starting from the position point given in step 2, use the method of combining the standard deviation of the sliding window with threshold judgment to cyclically traverse downward along the time axis. Combining the verification results of engineering experience, the standard deviation threshold is given as 10, so as to find the transition point where the rotation speed point of the drive motor changes from steep fluctuation to steady fluctuation, and judge whether this rotation speed point meets the rotation speed requirements of the center turn index. If it does not meet the requirements, it will not be included in the calculation of the center turn index time;

[0027] Starting from the position of the transition point from steep fluctuation to steady fluctuation, use the method of combining the sliding window with threshold judgment to cyclically traverse to find the fluctuation points with smaller fluctuation amplitudes of the left and right drive motor rotation speeds. Each found sliding window is stored, and the average value of all stored data that meet the conditions is calculated as the input for the calculation of the center turn index.

[0028] Among them, in the said step 3, set a standard deviation threshold equal to 10, and extract a window of 100 consecutive elements through a loop, and calculate the standard deviation of this window; if the standard deviation exceeds the threshold, it means that the signal fluctuates greatly, and then enter the next stage; continue to extract a new window backward until the standard deviation is lower than the threshold; at this time, if the maximum absolute value in the accumulated stored rotation speed signal extracted by the rotation speed is less than 3800, terminate the search and jump out of the current loop;

[0029] When the standard deviation of the window is lower than the threshold, check the increase and decrease changes of the signal; that is, calculate the signal difference. If both positive increase and negative decrease are included in the difference, that is, the signal has undulating changes, or there is 0 in the difference, indicating that the signal is stable, then further judgment is made;

[0030] If the difference between the maximum difference and the minimum difference of the signal is less than 300, it is considered that the current window meets the conditions, record this window and its position; then, increase the step size by 50 and continue to process the next window; if it does not meet the conditions, increase the step size by 1 and recheck;

[0031] If the signal no longer meets the condition of symbol change, that is, there is no obvious fluctuation or change, or the standard deviation of the window during the search process never meets the threshold, then jump out of the current loop; finally, record the last position of the current window and end this round of search.

[0032] Among them, in step 3, the method for determining the center turning stable speed point is based on the starting point of the zero position, and further search for a window that meets specific fluctuation characteristics in the signal; by judging the standard deviation and symbol change, find the fluctuation area of the signal and record its position; this process involves the dynamic adjustment of the signal window, gradually extracting the characteristic signal segments, and adjusting the step size with the change of the signal for further search.

[0033] Among them, in step 4, calculate the center turning index time;

[0034] For the driving motor speed result of step 3, starting from the transition point position from steep fluctuation to steady fluctuation in step 3 to the end position point of the search end, search for the corresponding position point value of the gear, and use different calculation formulas for different gears to calculate the center turning index time;

[0035] In step 4, first calculate the average value of the absolute values of all elements in the stored speed signal window of step 3; this value represents the average fluctuation amplitude of the speed signal of this window;

[0036] Use the position index recorded in step 3 to extract the corresponding values from the EMT_Gear array; store these values in a specific array, representing the steering state corresponding to the found window position, that is, the value of EMT_Gear;

[0037] Judge the steering state of the signal according to the values stored in the specific array, that is, the value of EMT_Gear at a specific position point, and calculate the steering time according to different states, first gear or second gear;

[0038] If all the values stored in the specific array are 1, then use the formula to calculate the steering time:

[0039]

[0040] In the formula, i c is the side transmission, ib1 is the first gear transmission ratio, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the crawler center distance, δ is the slip ratio, ava_Spd is the average speed of the left and right driving motors at the stable point, r z is the radius of the driving wheel;

[0041] If all the values stored in a specific array are 2, another set of formulas is used to calculate the steering time:

[0042]

[0043] where i c is the side transmission, ib2 is the gear ratio of the second gear, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the track center distance, δ is the slip ratio, ava_Spd is the average rotational speed of the left and right drive motors at the stable point, r z is the radius of the driving wheel;

[0044] If the values stored in a specific array are both 1 and 2, that is, there is a mixed situation, the steering time is set to be empty, indicating that it cannot be calculated;

[0045] The calculated steering time is stored in the steering time array, recording the center steering time obtained each time;

[0046] The calculation method of the center steering index time determines the steering state of the signal by calculating the average absolute value of the window signal and the steering state value EMT_Gear extracted from the signal position, and calculates the corresponding steering time according to different steering states; if the steering states of the signals are inconsistent, that is, in a mixed state, the steering time is not calculated and an empty value is returned; the calculation results are recorded in the center steering time array.

[0047] (III) Advantageous Effects

[0048] Compared with the prior art, the technical solution of the present invention provides a method for evaluating the center steering performance based on the actual vehicle test data of a special vehicle's electro-mechanical composite transmission system, aiming to accurately evaluate the performance of its center steering by deeply analyzing and processing the test data of a tracked vehicle during actual operation. This method solves the problems of insufficient accuracy, complex data processing, and inadequate analysis of steering behavior in traditional evaluation means, and provides a data-driven evaluation framework that can effectively capture the key behavioral characteristics of the vehicle during center steering.

[0049] This method is achieved through four main steps: conversion and processing of actual vehicle test data, determination and frequency statistics of the global index position of center steering, identification of stable rotational speed points, and calculation of the center steering index time. In specific applications, the sliding window technique is used to analyze and identify the fluctuation characteristics of the vehicle steering signal. Combining the standard deviation determination and threshold strategy can accurately locate the conversion point and stable fluctuation region of center steering, thereby accurately calculating the steering performance index. These technical means not only enhance the accuracy of performance evaluation but also can effectively conduct quantitative analysis on the steering characteristics in driving behavior.

[0050] Through this evaluation method, the present invention can extract key central steering characteristics from the actual test data of the vehicle, accurately analyze and identify the dynamic changes during the central steering process, thereby providing a scientific basis for the design optimization, control strategy adjustment, and performance improvement of special vehicles. At the same time, the implementation of this method helps to improve the vehicle's handling, stability, and safety, ensuring excellent performance of special vehicles in complex tactical and operating environments.

[0051] The beneficial effect of the present invention is that through precise data analysis, it can effectively capture the characteristic changes of tracked vehicles during the central steering process, quantify their steering stability, and provide strong data support for the performance evaluation, optimization, and technical improvement of special vehicles. This method has broad application prospects and is not only applicable to the monitoring of the driving behavior of special vehicles but also can provide data-driven decision-making basis for the overall improvement of vehicle performance. Brief Description of the Drawings

[0052] Figure 1 It is a test data diagram of the central steering (including gear position and rotational speeds of left and right drive motors) of the present invention.

[0053] Figure 2 It is a logic diagram of the method for determining the global index position and counting the number of times of central steering of the present invention.

[0054] Figure 3 It is a logic diagram of the method for determining the stable rotational speed point of central steering of the present invention.

[0055] Figure 4 It is a flow chart of the technical solution of the present invention. Detailed Description of the Preferred Embodiments

[0056] To make the objectives, contents, and advantages of the present invention clearer, the following further describes in detail the specific embodiments of the present invention in conjunction with the drawings and embodiments.

[0057] To solve the above technical problems, the present invention provides a method for evaluating the central steering performance of a tracked vehicle based on real vehicle data, and the method includes the following steps:

[0058] Step 1: Conversion and processing of real vehicle test data;

[0059] Step 2: Determination of the global index position of central steering and counting of the number of times;

[0060] Step 3: Determination of the stable rotational speed point of central steering;

[0061] Step 4: Calculation of the central steering index time.

[0062] Among them, in the above Step 1, conversion and processing of real vehicle test data are performed;

[0063] Collect the operation data of the electromechanical composite drive system under different working conditions during the real vehicle test; the original data formats collected from real vehicles are usually diverse and inconsistent, so format conversion is required to ensure that all data has a consistent format, including timestamp synchronization, multi-source data fusion, and data regeneration, to obtain the rotational speed curves of the left and right drive motors.

[0064] Among them, in step 1, collect the operation data of the electromechanical composite drive system under different working conditions during the real vehicle test; the data includes: the rotational speed signal EMT_SpdL of the left drive motor, the rotational speed signal EMT_SpdR of the right drive motor, and the gear signal EMT_Gear.

[0065] Among them, in step 2, determine the global index position of central steering and count the number of times;

[0066] Analyze the differences in the rotational speed performance of the drive motors between central steering and normal steering, analyze the identification characteristics of the central steering curve, and obtain the central steering judgment conditions; for the rotational speed curves of the left and right drive motors obtained in step 1, use a sliding window combined with logical judgment and the method of circular traversal search. First, find the points where the rotational speed signs of the left and right drive motors are opposite and the speed difference is relatively small, remember the position index of this point, and use the method of circular traversal along the time axis forward with a sliding window to find the point where the sliding window is all zero, and find the position of the last zero point, so as to find the global index position point of central steering, and increment the corresponding number of central steering times by one.

[0067] Among them, in step 2, through a loop, extract a window of a specific size from the signals of the rotational speed of the left drive motor EMT_SpdL and the rotational speed of the right drive motor EMT_SpdR; ensure that the window does not exceed the range of the signal, and through the method of circular traversal, obtain the window values of the rotational speed of the left drive motor EMT_SpdL and the rotational speed of the right drive motor EMT_SpdR, judge whether there are elements with different signs in the window values, check whether the absolute values of all elements in the window values are greater than 50, calculate the absolute value difference of the window, if all the differences are less than 150, and if all the above conditions are met, continue with an additional search operation. Starting from the current index position, search forward along the time axis for up to 100 points. During the search process, find a window containing zero in EMT_SpdL; for each possible window, the length of the window is fixed at 100 and it moves forward one grid each time, check whether the window contains a zero element; if a zero point is found, record the last position of this zero point and jump out of the search loop; after finding the zero point, the position variable will be updated to the position of this zero point, and jump out of the inner loop to stop further search;

[0068] If the zero point search returns a valid position, search for the characteristics of the signal backward from the zero point position; start from the position before the zero point, record this starting position, and increment the count of the number of turns.

[0069] Among them, in the said step 2, the logic of the method for determining the global index position of the center turn and counting the number of times is summarized as follows: extract a window that meets specific conditions from the signal. If this window meets the requirements of different signal symbols, large absolute values, and small differences, further search whether there is a zero point among the positions before this window, and record the position of this zero point; if no zero point meeting the conditions is found, it will remain in an empty state.

[0070] Among them, in the said step 3, determine the stable rotation speed point of the center turn;

[0071] Starting from the position point given in step 2, use the method of combining the standard deviation of the sliding window with threshold judgment to loop through downward along the time axis. Combining the verification results of engineering experience, the standard deviation threshold is given as 10, so as to find the transition point where the rotation speed point of the drive motor changes from steep fluctuation to steady fluctuation, and judge whether this rotation speed point meets the rotation speed requirements of the center turn index. If it does not meet the requirements, it will not be included in the calculation of the center turn index time;

[0072] Starting from the position of the transition point from steep fluctuation to steady fluctuation, use the method of combining the sliding window with threshold judgment to loop through to find the fluctuation points with smaller fluctuation amplitudes of the left and right drive motor rotation speeds. Each found sliding window is stored, and the average value of all stored data that meet the conditions is calculated as the input for the calculation of the center turn index.

[0073] Among them, in the said step 3, set a standard deviation threshold equal to 10, and extract a window of 100 consecutive elements through a loop, and calculate the standard deviation of this window; if the standard deviation exceeds the threshold, it means that the signal fluctuates greatly, and then enter the next stage; continue to extract a new window backward until the standard deviation is lower than the threshold; at this time, if the maximum absolute value in the accumulated stored rotation speed signal extracted by the rotation speed is less than 3800, terminate the search and jump out of the current loop;

[0074] When the standard deviation of the window is lower than the threshold, check the increase and decrease changes of the signal; that is, calculate the signal difference. If both positive increase and negative decrease are included in the difference, that is, the signal has ups and downs, or there is 0 in the difference, indicating that the signal is stable, then further judgment is made;

[0075] If the gap between the maximum difference and the minimum difference of the signal is less than 300, it is considered that the current window meets the conditions, record this window and its position; then, increase the step size by 50 and continue to process the next window; if it does not meet the conditions, increase the step size by 1 and check again;

[0076] If the signal no longer meets the condition of sign change, that is, there is no obvious fluctuation or change, or the standard deviation of the window during the search process never meets the threshold, then jump out of the current loop; finally, record the last position of the current window and end this round of search.

[0077] Among them, in step 3, the method for determining the center turning stable speed point is based on the zero position starting point, and further search for windows that meet specific fluctuation characteristics in the signal; through the judgment of the standard deviation and sign change, find the fluctuation area of the signal and record its position; this process involves the dynamic adjustment of the signal window, gradually extracting the characteristic signal segments, and adjusting the step size with the change of the signal for further search.

[0078] Among them, in step 4, calculate the center turning index time;

[0079] For the drive motor speed result of step 3, starting from the transition point position from steep fluctuation to steady fluctuation to the end position point in step 3, search for the corresponding position point values of the gear, and adopt different calculation formulas for different gears to calculate the center turning index time;

[0080] In step 4, first calculate the average value of the absolute values of all elements in the stored speed signal window of step 3; this value represents the average fluctuation amplitude of the speed signal in this window;

[0081] Using the position index recorded in step 3, extract the corresponding values from the EMT_Gear array; store these values in a specific array, representing the steering state corresponding to the found window position, that is, the value of EMT_Gear;

[0082] Judge the steering state of the signal according to the values stored in the specific array, that is, the value of EMT_Gear at a specific position point, and calculate the steering time according to different states, first gear or second gear;

[0083] If all the values stored in the specific array are 1, then use the formula to calculate the steering time:

[0084]

[0085] In the formula, i c is the side transmission, ib1 is the first gear transmission ratio, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the crawler center distance, δ is the slip and skid rate, ava_Spd is the average speed of the left and right drive motor stable points, r z is the driving wheel radius;

[0086] If all the values stored in a specific array are 2, another set of formulas is used to calculate the steering time:

[0087]

[0088] Where i c is the side drive, ib2 is the gear ratio of the second gear, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the track center distance, δ is the slip ratio, ava_Spd is the average rotational speed of the stable points of the left and right drive motors, r z is the radius of the driving wheel;

[0089] If the values stored in a specific array are both 1 and 2, that is, there is a mixed situation, the steering time is set to be empty, indicating that it cannot be calculated;

[0090] The calculated steering time is stored in the steering time array, recording the center steering time obtained each time;

[0091] The calculation method of the center steering index time determines the steering state of the signal by calculating the average absolute value of the window signal and the steering state value EMT_Gear extracted from the signal position, and calculates the corresponding steering time according to different steering states; if the steering states of the signals are inconsistent, that is, in a mixed state, the steering time is not calculated and an empty value is returned; the calculation result is recorded in the center steering time array.

[0092] Embodiment 1

[0093] The present invention aims to solve the problem of effectively extracting and analyzing the characteristics of the center steering performance from a large amount of complex data during the actual vehicle test of the existing electromechanical composite transmission system for special vehicles. This task involves key issues such as identifying the data change characteristics in the center steering stage, determining the occurrence time and frequency of the center steering, and accurately correlating the position information of the center steering with the dynamic performance of the vehicle. The present invention provides a method for evaluating the center steering performance of a tracked vehicle based on actual vehicle data, and the method includes the following:

[0094] (1) Conversion and processing of actual vehicle test data

[0095] 1) Data acquisition

[0096] First, the operation data of the electromechanical composite transmission system under different working conditions are collected during the actual vehicle test. The data includes: the rotational speed signal EMT_SpdL of the left drive motor, the rotational speed signal EMT_SpdR of the right drive motor, and the gear position signal EMT_Gear.

[0097] These data are collected through various sensors and data acquisition systems, and the data is transmitted through standard communication protocols (such as CAN or FlexRay buses).

[0098] 2) Data format conversion

[0099] The original data formats collected from actual vehicles are usually diverse and inconsistent. Therefore, format conversion is required to ensure that all data has a consistent format. The main data processing methods are as follows:

[0100] Timestamp synchronization: Since the sampling frequencies of each sensor are different, it is first necessary to align the timestamps of all data to ensure the time synchronization of data from different sensors.

[0101] (2) Method for determining the global index position of center steering and counting the number of times

[0102] Through a loop, extract a window of a specific size from the left drive motor speed EMT_SpdL and the right drive motor speed EMT_SpdR signals. Ensure that the window does not exceed the signal range, and then obtain the window values of the left drive motor speed EMT_SpdL and the right drive motor speed EMT_SpdR by traversing the loop. Determine whether there are elements with different signs in the window values, check whether the absolute values of all elements in the window values are greater than 50, calculate the absolute value difference of the window, and if all differences are less than 150, and if all the above conditions are met, continue with an additional search operation. Starting from the current index position, search forward along the time axis for up to 100 points. During the search, find a window containing zero in EMT_SpdL. For each possible window (the length of this window is fixed at 100 and it moves one grid forward each time), check whether the window contains a zero element. If a zero point is found, record the last position of this zero point and jump out of the search loop. After finding the zero point, the position variable will be updated to the position of this zero point, and the inner loop will be exited to stop further searching.

[0103] If the zero point search returns a valid position, search for the characteristics of the signal backward from the zero point position. Start from the position before the zero point and record this starting position, and increment the count of the number of steering times.

[0104] Generally speaking, the logic of the method for determining the global index position of center steering and counting the number of times can be summarized as follows: Extract a window that meets specific conditions from the signal. If this window meets the requirements of different signal signs, large absolute values, and small differences, then further search whether there is a zero point among the positions before this window, and record the position of this zero point. If no zero point meeting the conditions is found, it will remain in an empty state.

[0105] (3) Method for determining the stable rotation speed point of center steering

[0106] Starting from the starting position recorded in (2), a new search phase is entered. A standard deviation threshold is set equal to 10, and a window of 100 consecutive elements is extracted through a loop, and the standard deviation of this window is calculated. If the standard deviation exceeds the threshold, indicating that the signal fluctuates greatly, then the next phase is entered. New windows (size 100) will continue to be extracted backward until the standard deviation is below the threshold. At this time, if the maximum absolute value in the accumulated stored rotational speed signal extracted by rotational speed is less than 3800, the search will be terminated and the current loop will be exited.

[0107] When the standard deviation of the window is below the threshold, the program will check the increase and decrease changes of the signal. Specifically, it will calculate the signal difference. If both positive increase and negative decrease are included in the difference (i.e., the signal has undulating changes), or there is 0 in the difference (indicating that the signal is stable), then further judgment will be made.

[0108] If the gap between the maximum difference and the minimum difference of the signal is less than 300, it is considered that the current window meets the conditions, and the window and its position can be recorded. Then, the step size is increased by 50, and the next window is continued to be processed. If the conditions are not met, the step size is increased by 1 and rechecked.

[0109] If the signal no longer meets the condition of sign change (i.e., there is no obvious fluctuation or change), or the standard deviation of the window during the search process never meets the threshold, the program will jump out of the current loop. Finally, the last position of the current window is recorded, and this round of search is ended.

[0110] Generally speaking, the method for determining the center turning stable rotational speed point is based on the starting point of the zero position, and further searches for windows that meet specific fluctuation characteristics in the signal. Through the judgment of the standard deviation and sign change, the fluctuation area of the signal is found and its position is recorded. This process involves the dynamic adjustment of the signal window, gradually extracting the characteristic signal segments, and adjusting the step size with the change of the signal for further search.

[0111] (4) Method for calculating the center turning index time

[0112] First, calculate the average value of the absolute values of all elements in the rotational speed signal window stored in (3). This value represents the average fluctuation amplitude of the rotational speed signal of this window.

[0113] Using the position index recorded in (3), extract the corresponding values from the EMT_Gear array. Store these values in a specific array, representing the turning state (i.e., the value of EMT_Gear) corresponding to the found window position.

[0114] Judge the steering state of the signal according to the value stored in a specific array, that is, the value of EMT_Gear at a specific position point, and calculate the steering time according to different states (first gear or second gear).

[0115] If all the values stored in the specific array are 1, use the formula to calculate the steering time:

[0116]

[0117] In the formula, i c is the side transmission, ib1 is the first-gear speed ratio, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the crawler center distance, δ is the slip ratio, ava_Spd is the average rotational speed of the left and right drive motors at the stable point, r z is the radius of the driving wheel.

[0118] If all the values stored in the specific array are 2, use another set of formulas to calculate the steering time:

[0119]

[0120] In the formula, i c is the side transmission, ib2 is the second-gear speed ratio, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the crawler center distance, δ is the slip ratio, ava_Spd is the average rotational speed of the left and right drive motors at the stable point, r z is the radius of the driving wheel.

[0121] If the values stored in the specific array are both 1 and 2 (i.e., there is a mixed situation), the steering time is set to empty, indicating that it cannot be calculated.

[0122] The calculated steering time is stored in the steering time array, and the center steering time obtained each time is recorded.

[0123] The calculation method of the center steering index time judges the steering state of the signal by calculating the average absolute value of the window signal and the steering state value (EMT_Gear) extracted from the signal position, and calculates the corresponding steering time according to different steering states. If the steering states of the signals are inconsistent (i.e., mixed states), the steering time is not calculated (return empty). The calculation results will be recorded in the center steering time array.

[0124] In summary, the present invention belongs to the technical field of processing experimental data of the electro-mechanical composite transmission system of special vehicles, and specifically relates to a method for evaluating the central steering performance of tracked vehicles based on in-vehicle data. This method faces the experimental data collected from the in-vehicle electro-mechanical composite transmission system of special vehicles, analyzes the mapping relationship between the data and driving behavior, processes the central steering test data, analyzes the differences in signal representation between central steering and normal steering, finds and identifies the characteristics of central steering, uses the sliding window method to search for and determine the global index position points of central steering, combines the standard deviation of the sliding window with threshold judgment to determine the conversion position points from the rising trend to a stable curve with little fluctuation, and finds the stable fluctuation speed points by using the stable fluctuation characteristics of the rotational speed, so as to calculate the central steering index time through gear judgment and average stable rotational speed. This method solves the problem of how to accurately analyze and capture the change characteristics of central steering at the data performance level based on the experimental data collected from the in-vehicle electro-mechanical composite transmission system of special vehicles, identify the global position index of central steering, find the turning point from its steep fluctuation to steady-state fluctuation, and thus evaluate the central steering performance index by combining theoretical calculations. This method can extract key central steering information from in-vehicle data, providing a scientific basis for optimizing and improving the performance of special vehicles.

[0125] This method is divided into in-vehicle test data conversion and processing, central steering global index position determination and frequency statistics method, central steering stable speed point determination method, and central steering index time calculation method. The beneficial effects of the present invention are that through the accurate analysis based on the in-vehicle data of the electro-mechanical composite transmission system of special vehicles, the central steering performance of tracked vehicles can be accurately evaluated. By deeply processing the experimental data, this method identifies the key characteristics of central steering, combines the sliding window technology and standard deviation judgment, effectively captures the transition from the fluctuating state to the stable state, and accurately determines the steering performance index. This method not only improves the accuracy of central steering evaluation, but also provides a scientific basis for optimizing the performance of special vehicles. Through the accurate analysis of in-vehicle data, the central steering stability can be quantified, the control strategy can be optimized, thereby improving the vehicle's handling, stability and safety. This method has wide application value in the monitoring of driving behavior, performance evaluation and technical improvement of special vehicles.

[0126] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the technical principle of the present invention, several improvements and deformations can be made, and these improvements and deformations should also be regarded as the protection scope of the present invention.

Claims

1. A method for evaluating the central steering performance of a tracked vehicle based on real vehicle data, characterized in that The method includes the following steps: Step 1: Convert and process the real vehicle test data; Step 2: Determine the global index position of central steering and count the number of times; Step 3: Determine the stable rotational speed point of central steering; Step 4: Calculate the central steering index time.

2. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 1, wherein In Step 1, convert and process the real vehicle test data; Collect the operation data of the electromechanical composite drive system under different working conditions during the real vehicle test; the original data formats collected in the real vehicle are usually diverse and inconsistent, so format conversion is required to ensure that all data has a consistent format, including timestamp synchronization, multi-source data fusion, and data regeneration, to obtain the rotational speed curves of the left and right drive motors.

3. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 2, wherein In Step 1, collect the operation data of the electromechanical composite drive system under different working conditions during the real vehicle test; the data includes: the rotational speed signal of the left drive motor EMT_SpdL, the rotational speed signal of the right drive motor EMT_SpdR, and the gear position signal EMT_Gear.

4. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 3, wherein In Step 2, determine the global index position of central steering and count the number of times; Analyze the differences in the rotational speed performance of the drive motors between central steering and steering, analyze the recognition features of the central steering curve, and obtain the central steering judgment conditions; for the rotational speed curves of the left and right drive motors obtained in Step 1, use a sliding window combined with logical judgment and a loop traversal search method. First, find the points where the rotational speed signs of the left and right drive motors are opposite and the speed difference is relatively small, remember the position index of this point, and use the sliding window loop traversal method to search forward along the time axis to find the point where the sliding window is all zero, and find the position of the last zero point, so as to find the global index position point of central steering, and increment the corresponding central steering count by one.

5. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 4, wherein In Step 2, through a loop, extract a window of a specific size from the left drive motor rotational speed EMT_SpdL and the right drive motor rotational speed EMT_SpdR signals; ensure that the window does not exceed the signal range, and through loop traversal, obtain the window values of the left drive motor rotational speed EMT_SpdL and the right drive motor rotational speed EMT_SpdR, judge whether there are elements with different signs in the window values, check whether the absolute values of all elements in the window values are greater than 50, calculate the absolute value difference of the window, if all differences are less than 150, and if all the above conditions are met, continue with an additional search operation. Starting from the current index position, search forward along the time axis for up to 100 points, and find a window containing zero in EMT_SpdL during the search; for each possible window, the length of the window is fixed at 100 and it moves one grid forward each time, check whether the window contains a zero element; if a zero point is found, record the last position of this zero point and jump out of the search loop; after finding the zero point, the position variable will be updated to the position of this zero point, and jump out of the inner loop to stop further search; If the zero point search returns a valid position, search for the signal features backward from the zero point position; start from the position before the zero point and record this starting position, and increment the count of the steering times.

6. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 5, wherein In step 2, the logic of the method for determining the central steering global index position and counting the number of times is summarized as follows: Extract a window that meets specific conditions from the signal. If the window meets the requirements of different signal symbols, a relatively large absolute value, and a relatively small difference, further check whether there is a zero point among the positions before this window, and record the position of this zero point; if no zero point that meets the conditions is found, it will remain in an empty state.

7. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 5, characterized in that, In step 3, determine the central steering stable speed point; Starting from the position point given in step 2, use the method of combining the standard deviation of the sliding window with threshold judgment to cyclically traverse downward along the time axis. Combining the verification results of engineering experience, the standard deviation threshold is given as 10, so as to find the transition point where the driving motor speed point changes from steep fluctuation to steady-state fluctuation, and judge whether this speed point meets the speed requirements of the central steering index. If it does not meet the requirements, it will not be included in the calculation of the central steering index time; Starting from the position of the transition point where it changes from steep fluctuation to steady-state fluctuation, use the method of combining the sliding window with threshold judgment to cyclically traverse to find the fluctuation points with relatively small fluctuation amplitudes of the left and right driving motor speeds. Store each found sliding window, and calculate the average value of all stored data that meet the conditions as the input for the calculation of the central steering index.

8. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 7, wherein In step 3, set a standard deviation threshold equal to 10, and extract a window of 100 consecutive elements through a loop, and calculate the standard deviation of this window; if the standard deviation exceeds the threshold, it means that the signal fluctuates greatly, and then enter the next stage; continue to extract a new window backward until the standard deviation is lower than the threshold; at this time, if the maximum absolute value in the cumulative stored speed signal extracted by the speed is less than 3800, terminate the search and jump out of the current loop; When the standard deviation of the window is lower than the threshold, check the increase and decrease of the signal; that is, calculate the signal difference. If the difference contains both positive increase and negative decrease, that is, the signal has fluctuations, or there is 0 in the difference, indicating that the signal is stable, then further judgment is made; If the difference between the maximum difference and the minimum difference of the signal is less than 300, it is considered that the current window meets the conditions, record this window and its position; then, increase the step size by 50 and continue to process the next window; if it does not meet the conditions, increase the step size by 1 and check again; If the signal no longer meets the condition of symbol change, that is, there is no obvious fluctuation or change, or the standard deviation of the window never meets the threshold during the search process, then jump out of the current loop; finally, record the last position of the current window and end this round of search.

9. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 8, wherein, In step 3, the method for determining the central steering stable speed point is based on the starting point of the zero point position, and further search for a window that meets specific fluctuation characteristics in the signal; through the judgment of the standard deviation and symbol change, find the fluctuation area of the signal and record its position; This process involves the dynamic adjustment of the signal window, gradually extracting the signal segments with characteristics, and adjusting the step size for further search as the signal changes.

10. The method for evaluating the central steering performance of a tracked vehicle based on real vehicle data according to claim 8, characterized in that, In step 4, calculate the central steering index time; For the driving motor speed result in step 3, starting from the transition point position where it changes from steep fluctuation to steady-state fluctuation in step 3 to the end position point of the search, find the corresponding position point value of the gear, and adopt different calculation formulas for different gears to calculate the center steering index time; In step 4, first calculate the average value of the absolute values of all elements in the speed signal window stored in step 3; This value represents the average fluctuation amplitude of the speed signal in this window; Use the position index recorded in step 3 to extract the corresponding values from the EMT_Gear array; store these values in a specific array, representing the steering state corresponding to the found window position, that is, the value of EMT_Gear; Judge the steering state of the signal according to the values stored in the specific array, that is, the value of EMT_Gear at the specific position point, and calculate the steering time according to different states, first gear or second gear; If all the values stored in the specific array are 1, use the formula to calculate the steering time: Where, i c is the side drive, ib1 is the gear ratio of the first gear, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the track center distance, δ is the slip ratio, ava_Spd is the average rotational speed of the left and right drive motors at the stable point, r z is the radius of the driving wheel; If all the values stored in the specific array are 2, use another set of formulas to calculate the steering time: Where, i c is the side drive, ib2 is the gear ratio of the second gear, i j is the reduction ratio, k o is the coupling mechanism parameter, B is the track center distance, δ is the slip ratio, ava_Spd is the average rotational speed of the left and right drive motors at the stable point, r z is the radius of the driving wheel; If the values stored in the specific array are both 1 and 2, that is, there is a mixed situation, the steering time is set to be empty, indicating that it cannot be calculated; The calculated steering time is stored in the steering time array, and record the center steering time obtained each time; The calculation method of the center steering index time judges the steering state of the signal by calculating the average absolute value of the window signal and the steering state value EMT_Gear extracted from the signal position, and calculates the corresponding steering time according to different steering states; If the steering states of the signals are inconsistent, that is, in a mixed state, do not calculate the steering time and return empty; The calculation results are recorded in the center steering time array.

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