Multi-axle special vehicle road simulation bench acceleration test method

Abstract

The invention discloses a multi-axis special vehicle road simulation bench acceleration test method. The method is realized through a multi-axis special vehicle road simulation bench acceleration test system comprising a road simulation test bench, a road simulation iteration and control system, an acquisition test system, an auxiliary test device and a test vehicle. The test method comprises the following steps: carrying out a road load spectrum acquisition test to obtain load spectrum data when a test vehicle runs on a test field working condition road; carrying out load spectrum analysis and processing on the obtained load spectrum data to obtain a target load spectrum meeting damage equivalent requirements; carrying out a road simulation iteration test based on the target load spectrum, and obtaining a rack driving signal meeting an error requirement; and a bench acceleration test is carried out based on the bench driving signal, test data processing and result evaluation are completed, and reproduction and acceleration of the road driving working condition of the multi-axis special vehicle are realized. The method solves the test adaptability problem of the multi-axle special vehicle, realizes working condition reproduction and acceleration, shortens the period and saves the cost.

Description

Technical Field

[0001] This invention relates to the field of automotive testing technology, and more specifically, to a method for accelerating multi-axle special vehicles using a road simulation bench. Background Technology

[0002] Road simulation bench testing is a testing method that replicates the road vibration conditions of vehicles using electro-hydraulic servo loading equipment. It is a core method for studying the fatigue durability performance of vehicle components, assemblies, and the entire vehicle. Compared to road testing at a test track, bench testing has advantages such as being unaffected by the environment, having a shorter cycle time, lower cost, better safety and controllability, and better repeatability, and has been widely used in the research and development of small passenger cars and commercial vehicles. However, multi-axle special vehicles (such as multi-axle heavy transport vehicles and special operation vehicles) have characteristics such as a large number of axles (usually ≥4 axles), heavy load (fully loaded mass can reach tens of tons), uneven load distribution, and complex driving conditions (including off-road, mountain roads, and other harsh road conditions). Existing road simulation bench testing methods for passenger cars and commercial vehicles cannot adapt to their characteristics—for example, load spectrum processing does not consider multi-axle load coupling, iterative control cannot meet the accuracy requirements under heavy loads, and test acceleration does not take into account damage equivalence, resulting in the inability to effectively conduct performance verification of multi-axle special vehicles. Therefore, there is an urgent need for a road simulation bench testing method for multi-axle special vehicles that is highly adaptable, accurate, and accelerable. Summary of the Invention

[0003] This invention aims to provide a method for accelerated testing of multi-axle special vehicles using a road simulation bench, enabling equivalent bench testing and accelerated reproduction of road conditions under heavy loads, multiple axles, large wheelbase, and large tires. This provides technical support for the performance verification of multi-axle special vehicles, while shortening the testing cycle and saving resource costs.

[0004] To achieve the aforementioned technical objectives, this invention discloses an accelerated testing method for multi-axle special vehicles using a road simulation bench. This method is implemented through a multi-axle special vehicle road simulation bench accelerated testing system. The testing system includes a road simulation test bench, a road simulation iteration and control system, a data acquisition and testing system, auxiliary testing devices, and a test vehicle. The testing method includes the following steps:

[0005] S1: Conduct road load spectrum acquisition tests to obtain load spectrum data of the test vehicle when it is driving on the test site road under working conditions;

[0006] S2: Perform load spectrum analysis and processing on the load spectrum data obtained in step S1 to obtain the target load spectrum that meets the damage equivalence requirements.

[0007] S3: Conduct road simulation iterative tests based on the target load spectrum of step S2 to obtain bench drive signals that meet the error requirements;

[0008] S4: Based on the bench drive signal in step S3, conduct bench acceleration tests, complete test data processing and result evaluation, and realize the reproduction and acceleration of the road driving conditions of multi-axle special vehicles.

[0009] Furthermore, the present invention provides a method for accelerating multi-axle special vehicle road simulation bench testing, wherein step S1 includes test preparation and load spectrum acquisition test; the test preparation requires completing the technical condition check of the test vehicle, test scheme design, determining the mandatory test parameter as the wheel axle head acceleration as the iterative target measurement point, and completing the measurement point layout and test equipment installation and debugging; in the load spectrum acquisition test, the test vehicle travels along the test field working condition road at the maximum safe driving speed, and continuously collects data from each measurement point, wherein the test field working condition road is selected from at least one of uneven road, highway, mountain road, and off-road road.

[0010] Furthermore, in the present invention, a method for accelerated testing of multi-axle special vehicles on a road simulation bench is provided, wherein in step S1, the sampling frequency of the load spectrum acquisition is not less than 500Hz, and the number of samples acquired is at least 3; the load state of the test vehicle is set to the full-load state under motor transportation to ensure that the acquired data conforms to the actual operating conditions.

[0011] Furthermore, the present invention provides a method for accelerating multi-axle special vehicle road simulation bench tests, wherein step S2 includes load spectrum preprocessing, load spectrum analysis, and load spectrum editing; the load spectrum preprocessing sequentially performs data preparation, load spectrum truncation, data resampling, filtering, outlier removal, centering, and trend term removal; the load spectrum analysis includes at least one of time domain analysis, frequency domain analysis, statistical analysis, and damage analysis to perform load spectrum analysis on wheel axle head acceleration.

[0012] Furthermore, in the present invention, a method for accelerated testing of multi-axle special vehicles on a road simulation bench is provided. In step S2, the load spectrum editing adopts a damage equivalence-based editing method to identify and delete cyclic segments with low damage contribution. The retained cyclic segments are smoothed using a half-sine signal. After editing, the damage retention ratio of the load spectrum is 90%-95%, and the data duration does not exceed 60s. If the duration exceeds the limit, segmentation is performed. Before and after editing, the power spectral density, damage distribution, and failure mode of the load spectrum must be basically consistent, and the load spectra of all channels are edited synchronously to maintain phase consistency.

[0013] Further, for a multi-axis special vehicle road simulation bench acceleration test method of the present invention, an iterative test preparation step needs to be performed before step S3. The iterative test preparation step includes: leveling the foundation of the road simulation equipment to a preset position, arranging actuators according to the wheelbase and track of the test vehicle and positioning them in place, installing the tire tray and the upper vehicle device, positioning the test vehicle at the center of the tray, connecting the test system and checking, arranging limit and protection devices, installing a temperature control device for the suspension shock absorber, and completing system parameter configuration, performance debugging, limit effectiveness testing, and full-system joint debugging and pre-testing.

[0014] Further, for a multi-axis special vehicle road simulation bench acceleration test method of the present invention, after performing the iterative test preparation step in step S3, a system identification step is performed. The system identification step includes: using a white-pink noise signal as an excitation signal through the road simulation iterative test control system software, driving the bench to vibrate and excite the wheels of the test vehicle, collecting the response signals of the target measurement points and solving the frequency response function; when the coherence function values within the analysis frequency range are all greater than 0.8, it is determined that the system identification result is qualified; if the result is unqualified, adjust the excitation parameters or equipment status and re-identify.

[0015] Further, for a multi-axis special vehicle road simulation bench acceleration test method of the present invention, in step S3, the execution process of the target iterative test is as follows: import the target load spectrum obtained in step S2 using the system identification result and map it to the iterative channels, and carry out repeated iterative optimization; adaptively adjust the error control parameters according to the convergence situation during the iteration process. When the root mean square error or damage equivalent error of the time-domain signals of each channel does not exceed 10%, stop the iteration and save the corresponding bench drive signal; repeat the above operations to complete the iteration of all test conditions.

[0016] Further, for a multi-axis special vehicle road simulation bench acceleration test method of the present invention, where

[0017] Step S4 includes drive signal editing, bench acceleration test, and result analysis and evaluation; the drive signal editing is based on user-associated damage or reliability mileage allocation. According to the multi-axis special vehicle test track test specification, the bench drive signals of each condition are serially combined in the order of alternating strong and weak test conditions to form a complete test cycle; the bench acceleration test needs to configure a cyclic operation program and repeat the test cycle according to the set number of cycles until the specified total number of cycles is reached and then stop the test.

[0018] Further, for a multi-axis special vehicle road simulation bench acceleration test method of the present invention, where

[0019] In step S4, for particularly low-frequency road conditions such as twisted roads, the iterative method is not used, and the road surface elevation is directly used as the test bench drive signal; the result analysis and evaluation include: processing and analyzing the data collected during the test, writing a test report, and comprehensively evaluating the reliability and fatigue durability of the test vehicle based on the test records.

[0020] The beneficial effects of this invention are as follows:

[0021] 1. Targeting the heavy load and multiple axle count characteristics of multi-axle special vehicles, this study addresses the compatibility issues of existing methods through customized bench layout and multi-channel synchronous processing of load spectra, providing technical support for the performance verification of multi-axle heavy special vehicles.

[0022] 2. Achieve high-precision bench reproduction of road driving conditions, minimizing deviations between test results and actual road tests;

[0023] 3. By deleting low-damage load segments and combining strong and weak working condition cycles, the test cycle is shortened by more than 60% compared with traditional bench tests and by more than 80% compared with road tests, significantly saving time and resource costs;

[0024] 4. It can cover a variety of complex road conditions such as uneven roads, off-road roads, and twisting roads, and supports multi-axle special vehicle tests with different numbers of axles and different loads, with a wide range of application scenarios. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating the accelerated testing method for multi-axle special vehicles using a road simulation bench according to the present invention.

[0026] Figure 2 This is a schematic diagram of the frame structure of the multi-axle special vehicle road simulation test bench accelerated testing system of the present invention;

[0027] Figure 3 This is a schematic diagram of the iterative test process in the accelerated road simulation bench test method for multi-axle special vehicles of the present invention. Detailed Implementation

[0028] The following is a detailed explanation and description of the accelerated testing method for multi-axle special vehicles on a road simulation bench according to the present invention, with reference to the accompanying drawings.

[0029] like Figure 1 As shown in the figure, this invention discloses an accelerated testing method for multi-axle special vehicles using a road simulation bench, which is implemented through a dedicated testing system, as detailed below:

[0030] like Figure 2 As shown, the multi-axle special vehicle road simulation test bench accelerated testing system includes a road simulation test bench, a road simulation iteration and control system, a data acquisition and testing system, auxiliary test devices, and a test vehicle. The functions of each part are as follows:

[0031] Road simulation test bench: including road simulation actuators (arranged according to the wheelbase / wheelbase of multi-axle vehicles, responding to iterative and accelerated test commands), equipment foundation leveling device (providing stable support, realizing automatic leveling and vibration isolation), and vehicle mounting device (assisting in vehicle positioning and fixing);

[0032] Road simulation iterative control system: used to analyze target load spectrum, conduct iterative test control, generate bench drive signals, and support TWR (time domain waveform reproduction) iterative algorithm;

[0033] The data acquisition and testing system includes an acceleration sensor (mandatory wheel axle head measuring point), a displacement sensor, a strain sensor, a temperature sensor, and integrated data acquisition equipment to acquire multi-parameter signals during the test process.

[0034] Auxiliary testing equipment includes a hydraulic oil supply system (to power the actuator), a cooling circulating water system (to control the oil temperature), and a shock absorber temperature control device (to simulate the actual temperature conditions of the shock absorber).

[0035] Test vehicle: A multi-axle special vehicle test vehicle, which must be fully loaded under motor transport conditions to match actual working conditions.

[0036] like Figure 1 As shown, the test method of the present invention includes the following steps:

[0037] S1: Conduct road load spectrum acquisition tests to obtain load spectrum data of the test vehicle when it is driving on the test site road under working conditions;

[0038] S2: Perform load spectrum analysis and processing on the load spectrum data obtained in step S1 to obtain the target load spectrum that meets the damage equivalence requirements.

[0039] S3: Conduct road simulation iterative tests based on the target load spectrum of step S2 to obtain bench drive signals that meet the error requirements;

[0040] S4: Based on the bench drive signal in step S3, conduct bench acceleration tests, complete test data processing and result evaluation, and realize the reproduction and acceleration of the road driving conditions of multi-axle special vehicles.

[0041] In this example, road load spectrum acquisition tests were conducted to ensure that the acquired load spectrum data fully reflects the actual driving conditions of the vehicle. Load spectrum analysis was performed on the acquired load spectrum data to lay a reasonable target load spectrum foundation for accelerated testing. Based on the target load spectrum, road simulation iterative tests were conducted to obtain accurate bench drive signals, effectively solving the problem of poor adaptability of traditional testing methods to multi-axle special vehicles with large axle numbers, heavy loads, and uneven load distribution. This achieved high-precision bench equivalent reproduction of the vehicle's road driving vibration conditions. Based on the bench drive signals, accelerated bench tests were conducted and completed. The data processing and result evaluation not only stably reproduces the actual road driving conditions of multi-axle special vehicles and accurately assesses vehicle reliability and fatigue durability, but also significantly shortens the test cycle due to load spectrum editing and compression and cyclic test optimization. This avoids the drawbacks of road tests being greatly affected by environmental factors and costly. At the same time, the safety, controllability, and high repeatability of bench tests further improve the credibility and consistency of test results. Overall, it provides a highly adaptable, accurate, and efficient test technology solution for the performance verification of multi-axle special vehicles, achieving effective savings in resource costs while ensuring test quality.

[0042] In one embodiment of the present invention, step S1 includes test preparation and load spectrum acquisition test. The test preparation requires checking the technical condition of the test vehicle, designing the test plan, determining the wheel axle head acceleration as the iterative target measurement point as the mandatory test parameter, and completing the measurement point layout and test equipment installation and debugging. In the load spectrum acquisition test, the test vehicle travels along the test track road at its maximum safe driving speed, continuously collecting data from each measurement point. The test track road is selected from at least one of uneven roads, highways, mountain roads, and off-road roads. The sampling frequency for load spectrum acquisition is not less than 500Hz, and the number of samples collected is at least 3. The load state of the test vehicle is set to a fully loaded state under motorized transportation conditions to ensure that the collected data closely matches actual operating conditions.

[0043] In this embodiment, the technical condition check requires inspecting the tire pressure, suspension stiffness, and braking system of the test vehicle to ensure consistency with actual usage conditions. The test plan design requires determining the test track road conditions (e.g., a combination of uneven road, off-road road, and highway), with the vehicle fully loaded (meeting motor transport requirements), and the vehicle speed set according to the maximum safe speed for each road condition (e.g., 20 km / h for uneven road, 15 km / h for off-road road, and 60 km / h for highway). Six wheel axle heads are mandatory measurement points (with accelerometers installed), with additional frame strain measurement points and body displacement measurement points. Accelerometers are secured with bolts or strain gauges are attached to ensure secure installation. The data acquisition equipment is connected, and the sampling frequency is adjusted to 500 Hz. The load spectrum acquisition test vehicle travels sequentially along the test track road at the set speed, continuously collecting signals from each measurement point, collecting a total of three samples (meeting the requirement of ≥3 samples), with each sample acquisition lasting 120 seconds to ensure complete data coverage of the road conditions.

[0044] In one embodiment of the present invention, step S2 includes load spectrum preprocessing, load spectrum analysis, and load spectrum editing. The load spectrum preprocessing sequentially performs data preparation, load spectrum truncation, data resampling, filtering, outlier removal, centering, and trend term removal. The load spectrum analysis includes at least one of time-domain analysis, frequency-domain analysis, statistical analysis, and damage analysis for load spectrum analysis of wheel axle head acceleration. Load spectrum editing uses a damage equivalence-based editing method to identify and delete cyclic segments with low damage contribution, and uses a half-sine signal for smooth transition of the retained cyclic segments. After editing, the damage retention ratio of the load spectrum is 90%-95%, and the data duration does not exceed 60s. If the duration exceeds the limit, segmentation is performed. Before and after editing, the power spectral density, damage distribution, and failure mode of the load spectrum must be basically consistent, and all channel load spectra must be edited synchronously to maintain phase consistency.

[0045] In practical applications, load spectrum preprocessing sequentially processes the raw data of the three samples: importing the collected data and removing invalid data segments (such as the vehicle start / stop phase); extracting stable driving data segments corresponding to each road condition (such as 30s on uneven roads, 40s on off-road roads, and 30s on highways); unifying the sampling frequency to 500Hz (adjusting if fluctuations exist); using a low-pass filter (cutoff frequency 100Hz) to remove high-frequency noise; deleting outlier data exceeding ±3σ (σ is the standard deviation); adjusting the data mean to 0; and using the least squares method to remove linear trends in the data. Load spectrum analysis focuses only on the wheel axle head acceleration (target load spectrum): calculating peak, valley, and root mean square values ​​during time-domain analysis; obtaining the power spectral density through FFT transformation during frequency-domain analysis to identify the main vibration frequencies (5-15Hz for uneven roads, 3-10Hz for off-road roads); and using Miner's linear cumulative damage theory to calculate the cumulative damage value of each sample during damage analysis, selecting the sample with the damage closest to the mean as the base data. The damage equivalence editing method is used when editing the load spectrum. This includes identifying the damage contribution and screening out cyclic segments with a damage contribution ratio of <5% (such as smooth driving sections in highway conditions); deleting the above low-damage segments, leaving a data duration of 55s (≤60s, no segmentation required); connecting the first and last data of the deleted segments with a half-sine signal to avoid abrupt changes; after editing, the damage retention ratio is 92% (meeting the 90%-95% requirement), the power spectral density deviates from the original spectrum by <8%, and the damage distribution is consistent.

[0046] In this embodiment, the load spectrum preprocessing process effectively removes invalid information (such as unstable data during vehicle start-up or parking), high-frequency interference noise, abnormal fluctuation data, and linear trend deviations from the original load spectrum data. Simultaneously, it unifies the data sampling frequency, ensuring that the preprocessed data accurately reflects the true load state of multi-axle special vehicles during actual road driving. Analysis of wheel axle head acceleration (a mandatory target measurement point for road simulation iteration) focuses on the core load parameters of multi-axle special vehicles' road vibration, accurately acquiring the load time-domain characteristics, frequency domain distribution, statistical regularity, and cumulative damage characteristics of this key measurement point. This provides clear damage judgment criteria and core parameter references for subsequent load spectrum editing, ensuring the analysis process is not redundant and directly addresses key experimental needs, avoiding resource waste or missing key points due to scattered analysis of non-core parameters. Furthermore, the load spectrum editing method based on damage equivalence can significantly eliminate invalid test cycles while retaining 90%-95% of the core damage information, significantly shortening the total time of subsequent bench tests and achieving accelerated testing. It also avoids sudden changes in load signals through a half-sine signal transition, preventing bench tests from failing. During the loading process, additional impact damage may be caused to the test vehicle components or test bench equipment. After editing, the load spectrum data duration is strictly controlled to not exceed 60 seconds (if exceeded, it is processed in segments) to adapt to the signal processing time requirements of the test bench system, avoiding delays or decreased stability in test bench control due to excessively long signals, and improving the response efficiency of test bench control. Simultaneously, the power spectral density, damage distribution, and failure modes of the load spectrum before and after editing are ensured to be basically consistent, guaranteeing that the edited target load spectrum remains equivalent to the original road load spectrum in terms of vibration characteristics and damage effects, avoiding changes in test conditions due to editing. Distortion is eliminated to ensure that subsequent bench tests can accurately reproduce the actual road driving conditions of multi-axle special vehicles. In addition, the load spectra of all channels are edited synchronously to maintain phase consistency. In view of the characteristics of multi-axle special vehicles with a large number of axles and uneven load distribution, this can effectively avoid multi-axis coupled vibration distortion caused by phase deviation of multi-channel load signals, further improving the accuracy and adaptability of the target load spectrum. This ensures the accuracy, effectiveness and efficiency of accelerated road simulation bench tests for multi-axle special vehicles, shortens the test cycle and saves resource costs, while ensuring that the test results can reliably reflect the actual performance of the vehicle.

[0047] In one embodiment of the present invention, step S3 includes an iterative experiment preparation step, a system identification step, and a target iterative experiment.

[0048] Before executing step S3, the iterative test preparation steps must be performed first. The iterative test preparation steps include: leveling the foundation of the road simulation equipment to the preset position, arranging and positioning the actuators according to the wheelbase and track width of the test vehicle, installing the tire tray and the vehicle mounting device, positioning the test vehicle at the center of the tray, connecting and checking the test system, arranging the limit and protection devices, installing the suspension damper temperature control device, and completing the system parameter configuration, performance debugging, limit effectiveness testing, and full system integration and pre-test.

[0049] The system identification steps include: using white powder noise signal as excitation signal through the road simulation iterative test control system software, driving the test bench to vibrate the test vehicle wheels, collecting the response signal of the target measurement point and solving the frequency response function; when the recoherence function value in the analysis frequency range is greater than 0.8, the system identification result is deemed qualified; if the result is unqualified, the excitation parameters or equipment status are adjusted and the identification is repeated.

[0050] The execution process of the target iterative test is as follows: the target load spectrum obtained in step S2 is imported using the system identification results and mapped to the iterative channel, and repeated iterative optimization is carried out; during the iteration process, the error control parameters are adaptively adjusted according to the convergence situation. When the root mean square error of the time domain signal or the damage equivalent error of each channel does not exceed 10%, the iteration is stopped and the corresponding bench drive signal is saved; the above operation is repeated to complete the iteration of all test conditions.

[0051] In practical applications, such as Figure 3As shown, during the road simulation iterative test, preparation for the iterative test was first carried out. The equipment foundation was leveled, and six actuators were arranged according to the wheelbase and axle width of the test vehicle. Tire trays and vehicle mounting devices were installed. Then, the test vehicle was driven onto the test platform, aligning the wheel centers with the tray centers, and the vehicle body was fixed using limit devices. Next, the data acquisition and testing system and the iterative control system were connected, and the shock absorber temperature control device was installed. The actuator preset center position was adjusted, and the effectiveness of the limit was tested. Finally, a 30-second pre-test was conducted to confirm that the equipment was normal. During system identification, RSTWR software was used to determine the test condition name, the sampling frequency of 500Hz, the global frequency range of 0.5-200Hz, the iterative control channels of the six actuator displacement channels, and the target iterative channels of the six wheel axle head acceleration channels. White powder noise excitation signals were output, wheel axle head acceleration response signals were acquired, and the frequency response function was solved. The recoherence function values ​​within the frequency range were all 0.85-0.92, indicating that the identification results were qualified. When performing the target iterative test, the target load spectrum edited in S2-S3 is imported into the control system and mapped to the acceleration channels of the six wheel axle heads; the iteration is started, the initial error is set, and the proportional gain, integral time, and number of iterations are adjusted; the iteration is stopped after the iteration accuracy meets the requirements, the bench drive signals of the six actuators are saved, and the iteration of this working condition is completed; the above operation is repeated to complete the iteration of other working conditions (such as a separate off-road road or a separate uneven road) and obtain the corresponding drive signals (i.e., the excitation signals of the final output of the iteration).

[0052] In this embodiment, the initial iterative test preparation steps involve leveling the road simulation equipment foundation to a preset position, providing a stable and level support foundation for the entire bench test system and preventing additional vibration interference during the test due to uneven foundation. The actuators are arranged and positioned according to the wheelbase and track width of the test vehicle, precisely adapting to the structural characteristics of multi-axle special vehicles with numerous axles and unique wheelbase and track widths, ensuring that the actuator loading position matches the actual stress position of the vehicle. Installing the tire tray and mounting device enables stable load-bearing and positioning of the test vehicle, preventing displacement during vibration testing. Positioning the test vehicle at the center of the tray ensures uniform stress on each axle, avoiding the impact of eccentric loading on the accuracy of test data. Finally, the test system is connected. The system checks and completes parameter configuration and performance debugging, enabling early detection of test equipment connection faults and parameter setting deviations, ensuring the normal operation of data acquisition and system control; the installation of limit and protective devices provides safety protection for vehicles and equipment during testing, preventing vehicles from falling off or equipment from being damaged due to excessive vibration; the installation of suspension damper temperature control devices simulates the damper temperature environment of multi-axle special vehicles during actual driving, ensuring consistency between test conditions and actual use conditions; and the full system integration and pre-testing further verifies the collaborative working capability of the entire test system, identifies and resolves system compatibility issues in advance, and lays a stable, reliable, and realistic foundation for the smooth conduct of subsequent system identification and target iteration tests. In the system identification step, the white powder noise signal is used as the excitation signal through the road simulation iterative test control system software. Due to the wide frequency coverage of the white powder noise signal, it can fully excite the vibration characteristics of the test vehicle and the test bench system, thereby obtaining a system response that is more consistent with actual road vibration. By collecting the response signals of the target measurement points and solving the frequency response function, a mathematical relationship between the test bench excitation and the vehicle response can be established, providing an accurate system model for subsequent target iterations. Using a recoherence function value greater than 0.8 within the analysis frequency range as the pass criterion for the system identification results ensures that the established frequency response function has high reliability and reduces the risk of deviations in subsequent iterative tests due to inaccurate system models. When the results are not qualified, the operation of adjusting the excitation parameters or equipment status for re-identification further ensures the reliability of the system identification results and provides accurate basic data support for the target iterative test.The target iterative test imports the target load spectrum obtained in step S2 using the system identification results and maps it to the iterative channels. This ensures that the iteration direction is consistent with the target load spectrum, achieving accurate reproduction of the actual road load of multi-axle special vehicles. Repeated iterative optimization and adaptive adjustment of error control parameters based on convergence results effectively improve the iteration convergence speed and accuracy, avoiding iteration stagnation or excessive errors due to fixed parameters. Using a root mean square error or damage equivalent error of no more than 10% in the time domain signal of each channel as the criterion for stopping iteration strictly controls the deviation between the frame drive signal and the target load spectrum, ensuring that the drive signal can accurately reproduce the target load spectrum. The vibration characteristics and damage effects are measured; the corresponding bench drive signals are saved and the operation is repeated to complete the iteration of all test conditions, which can cover different road conditions that multi-axle special vehicles may face, ensuring that there are accurate bench drive signals under each condition. Ultimately, step S3 can provide accurate and reliable drive signals for subsequent bench acceleration tests, effectively solving the problems of poor adaptability and low simulation accuracy of traditional test methods for multi-axle special vehicles, ensuring the equivalence and accuracy of road simulation tests, and improving the safety and repeatability of the test through sufficient preparation and strict process control, making it more suitable for performance verification of multi-axle special vehicles.

[0053] In one embodiment of the present invention, step S4 includes drive signal editing, bench acceleration testing, and result analysis and evaluation. The drive signal editing is based on user-associated damage or reliability mileage allocation, and according to the multi-axle special vehicle track testing specifications, the bench drive signals for each working condition are serially combined in an alternating sequence of strong and weak test conditions to form a complete test cycle. The bench acceleration test requires a cyclic operation program, repeating the test cycle according to a set number of cycles until the specified total number of cycles is reached, at which point the test stops. In step S4, for particularly low-frequency road conditions such as tortuous roads, an iterative method is not used; the road surface elevation is directly used as the bench drive signal. The result analysis and evaluation includes: processing and analyzing the data collected during the test, writing a test report, and comprehensively evaluating the reliability and fatigue durability performance of the test vehicle based on the test records.

[0054] In practical applications, during bench acceleration testing, the drive signal editing is based on user reliability mileage requirements, allocating the number of cycles for each operating condition according to the track testing specifications: for example, 300 cycles for uneven road, 500 cycles for off-road, and 200 cycles for highway. The drive signals for each operating condition are connected in series in the order of off-road (strong) → highway (weak) → uneven road (strong) → highway (weak) to form a test cycle. When the bench acceleration test is started, the cycle operation program is configured, and the total number of cycles is set to 1000 to cover all operating conditions. During the test, the actuator displacement, wheel axle acceleration, and frame strain are monitored in real time. For the tortuous road, no iteration is performed; the road surface elevation data (obtained through test track measurements) is directly imported as the drive signal, with 100 cycles, and integrated into the total cycle program. The bench is started and runs continuously for a period of time, during which the oil temperature is controlled by the cooling water system and the shock absorber temperature control device is used to maintain the temperature. If there are no abnormal alarms during the test, the data acquisition is confirmed to be complete. During the results analysis and evaluation, the collected acceleration and strain data were analyzed in the time domain / frequency domain to calculate the cumulative damage value after the test; the test vehicle was disassembled to inspect key components such as suspension springs and frame welds, and no failure phenomena such as cracks or deformation were found; if the test results were qualified, the fatigue durability performance of the multi-axle special vehicle was determined to meet the reliability mileage requirements, and finally a test report was written.

[0055] In this embodiment, in step S4, the drive signal editing is based on user-associated damage or reliability mileage allocation and is performed according to the multi-axle special vehicle track test specifications. This ensures that the edited drive signal is highly consistent with the user's actual usage needs and vehicle design verification objectives. This allows the damage accumulation effect and reliability assessment standards of subsequent bench tests to accurately match the actual service scenarios of the vehicle, avoiding a disconnect between testing and actual needs. Furthermore, by serializing the drive signals of each working condition bench in an alternating sequence of strong and weak test conditions to form a complete test cycle, the one-sidedness of the test scenario caused by continuous loading of a single working condition is avoided, while also simulating the complex road conditions that occur during the actual driving of multi-axle special vehicles. The test covers real-world conditions, encompassing vehicle stress characteristics under varying load intensities, thus enhancing the comprehensiveness and representativeness of the test. The bench acceleration test, through a configured cyclic program, repeats the test cycle a set number of times until the specified total number is reached. Based on the prior editing of the load spectrum to eliminate invalid cycles, the total test time can be significantly reduced while ensuring test equivalence. Compared to the drawbacks of traditional road tests, which are greatly affected by environment and weather and have long cycles, as well as the low efficiency of single-condition bench tests, this significantly improves test efficiency and saves manpower and resource costs. Simultaneously, the program-controlled cyclic mode ensures the consistency of parameters for each loading, avoiding human error and enhancing test repeatability. Stability is ensured, meeting the stringent accuracy requirements of multi-axle special vehicles. For particularly low-frequency road conditions like tortuous roads, an iterative approach is avoided; instead, road surface elevation is directly used as the test bench drive signal. This fully considers the shortcomings of iterative control in low-frequency road conditions, such as response delay and phase deviation. By directly using actual road surface elevation data, the low-frequency vibration patterns and load transfer characteristics of tortuous roads can be accurately reproduced, avoiding additional errors introduced by the iterative process. This ensures that critical conditions testing the chassis stiffness and suspension torsional resistance of multi-axle special vehicles are accurately simulated, filling the gap in the adaptability of traditional iterative methods to complex low-frequency road conditions. Result analysis and evaluation are conducted using acceleration data collected during the test. The system processes and analyzes data such as strain, and combines test records to comprehensively evaluate vehicle reliability and fatigue durability. It can be supported by objective data, eliminate subjective judgment bias, and clearly present the vehicle's performance shortcomings or compliance status under simulated road conditions. This provides clear engineering basis for the design optimization, component improvement, or performance verification of multi-axle special vehicles, ensuring that the bench accelerated test can not only be completed efficiently, but also form test conclusions with practical value. Ultimately, it achieves the goal of accurately reproducing working conditions, efficiently shortening the cycle, comprehensively assessing performance, and scientifically evaluating results in multi-axle special vehicle road simulation bench tests, which is fully adapted to the characteristics of multi-axle special vehicles with many axles, heavy loads, and complex driving conditions.

[0056] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and simple improvements made on the substantive content of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for accelerated testing of multi-axle special vehicles using a road simulation bench, characterized in that: Accelerated testing is achieved using a multi-axle special vehicle road simulation bench system. This system includes a road simulation test bench, a road simulation iteration and control system, a data acquisition and testing system, auxiliary testing devices, and a test vehicle. The testing method includes the following steps: S1: Conduct road load spectrum acquisition tests to obtain load spectrum data of the test vehicle when it is driving on the test site road under working conditions; S2: Perform load spectrum analysis and processing on the load spectrum data obtained in step S1 to obtain the target load spectrum that meets the damage equivalence requirements. S3: Conduct road simulation iterative tests based on the target load spectrum of step S2 to obtain bench drive signals that meet the error requirements; S4: Based on the bench drive signal in step S3, conduct bench acceleration tests, complete test data processing and result evaluation, and realize the reproduction and acceleration of the road driving conditions of multi-axle special vehicles.

2. The method for accelerated testing of multi-axle special vehicles on a road simulation bench according to claim 1, characterized in that: Step S1 includes test preparation and load spectrum acquisition test; the test preparation requires checking the technical condition of the test vehicle, designing the test plan, determining the wheel axle head acceleration as the iterative target measurement point as the mandatory test parameter, and completing the measurement point layout and test equipment installation and debugging; in the load spectrum acquisition test, the test vehicle travels along the test site road at the maximum safe driving speed and continuously collects data from each measurement point. The test site road is selected from at least one of the following: uneven road, highway, mountain road, and off-road road.

3. The accelerated testing method for multi-axle special vehicles using a road simulation bench according to claim 2, characterized in that: In step S1, the sampling frequency of the load spectrum acquisition is not less than 500Hz, and the number of samples acquired is at least 3; the load state of the test vehicle is set to the full load state under motor transportation to ensure that the acquired data conforms to the actual working conditions.

4. The method for accelerated testing of multi-axle special vehicles on a road simulation bench according to claim 1, characterized in that: Step S2 includes load spectrum preprocessing, load spectrum analysis, and load spectrum editing; the load spectrum preprocessing sequentially performs data preparation, load spectrum truncation, data resampling, filtering, outlier removal, centering, and trend term removal; the load spectrum analysis includes at least one of time domain analysis, frequency domain analysis, statistical analysis, and damage analysis to perform load spectrum analysis on the wheel axle head acceleration.

5. The method for accelerated testing of multi-axle special vehicles on a road simulation bench according to claim 4, characterized in that: In step S2, the load spectrum editing uses a damage equivalence-based editing method to identify and delete cyclic segments with low damage contribution. The retained cyclic segments are smoothed using a half-sine signal. After editing, the damage retention ratio of the load spectrum is 90%-95%, and the data duration does not exceed 60s. If the duration exceeds the limit, segmentation is performed. Before and after editing, the power spectral density, damage distribution, and failure mode of the load spectrum must be basically consistent, and the load spectra of all channels are edited synchronously to maintain phase consistency.

6. The method for accelerated testing of multi-axle special vehicles on a road simulation bench according to claim 1, characterized in that: Before executing step S3, an iterative test preparation step must be performed first. The iterative test preparation step includes: leveling the foundation of the road simulation equipment to the preset position, arranging and positioning the actuators according to the wheelbase and track width of the test vehicle, installing the tire tray and the vehicle mounting device, positioning the test vehicle at the center of the tray, connecting and checking the test system, arranging the limit and protection devices, installing the suspension damper temperature control device, and completing the system parameter configuration, performance debugging, limit effectiveness testing, and full system integration and pre-test.

7. The accelerated testing method for multi-axle special vehicles on a road simulation bench according to claim 6, characterized in that: After performing the iterative test preparation step in step S3, the system identification step is performed. The system identification step includes: using white powder noise signal as excitation signal through the road simulation iterative test control system software to drive the test bench to vibrate the test vehicle wheels, collecting the response signal of the target measuring point and solving the frequency response function; when the recoherence function value in the analysis frequency range is greater than 0.8, the system identification result is judged to be qualified; if the result is unqualified, the excitation parameters or equipment status are adjusted and re-identified.

8. The accelerated testing method for multi-axle special vehicles on a road simulation bench according to claim 7, characterized in that: In step S3, the execution process of the target iterative test is as follows: the target load spectrum obtained in step S2 is imported using the system identification results and mapped to the iterative channel, and repeated iterative optimization is carried out; during the iteration process, the error control parameters are adaptively adjusted according to the convergence situation; when the root mean square error of the time domain signal or the damage equivalent error of each channel does not exceed 10%, the iteration is stopped and the corresponding bench drive signal is saved; the above operation is repeated to complete the iteration of all test conditions.

9. The accelerated testing method for multi-axle special vehicles using a road simulation bench according to claim 1, characterized in that: Step S4 includes drive signal editing, bench acceleration testing, and result analysis and evaluation. The drive signal editing is based on user-associated damage or reliability mileage allocation and, in accordance with the multi-axle special vehicle track testing specifications, connects and combines the bench drive signals of each working condition in a series of alternating strong and weak test conditions to form a complete test cycle. The bench acceleration test requires a cyclic operation program to repeat the test cycle according to the set number of cycles until the specified total number of cycles is reached and then the test stops.

10. The method for accelerated testing of multi-axle special vehicles on a road simulation bench according to claim 9, characterized in that: In step S4, for particularly low-frequency road conditions such as twisted roads, the iterative method is not used, and the road surface elevation is directly used as the test bench drive signal. The results analysis and evaluation include: processing and analyzing the data collected during the test, compiling the test report, and comprehensively evaluating the reliability and fatigue durability of the test vehicle based on the test records.

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