Load spectrum compilation method for accelerated life bench test of main reduction gear in parallel-axis electric drive axle

Abstract

The invention discloses a load spectrum compilation method for an accelerated life bench test of a main reduction gear in a parallel-axis electric drive axle. The load spectrum compilation method comprises the following steps: 1, obtaining a road load spectrum of the parallel-axis electric drive axle in a test field; 2, establishing a parallel-axis electric drive axle kinetic model, and obtaining a rotating speed signal and a torque signal of a main reduction gear; 3, obtaining the distribution rule of the load of the main reduction gear through a rotating rain flow counting method; 4, establishing a rigid-flexible coupling model of the speed reducer, and obtaining a stress load spectrum of the main reduction gear in the whole life cycle of the main reduction gear; 5, the fatigue life and accumulated damage of the main reduction gear are obtained according to the damage equivalence principle; and 6, optimizing the accelerated life load spectrum by adopting a genetic algorithm. According to the method, the reliability bench test problem of the parallel-axis electric drive axle can be solved, and the problems that the working condition load of the parallel-axis electric drive axle is complex, the load distribution is irregular, the real vehicle test period is long and the cost is high are solved through the new load spectrum compilation method.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicles, and particularly to a method for compiling a program load spectrum for an accelerated life bench test of a main reduction gear in a parallel-axis electric drive axle. Background Art

[0002] Due to the many advantages of electric drive axles such as high integration, low cost, fast torque response, and high transmission efficiency, they have been widely used in new energy vehicles. However, during the driving process of new energy vehicles, the working conditions are complex and changeable. As one of the torque transmission structural components, the main reduction gear of the parallel-axis electric drive axle bears very complex working conditions. Especially under the action of complex random loads and impact loads, it is necessary to identify and analyze the structural load excitation characteristics of the main reduction gear of the parallel-axis electric drive axle and be able to accurately define them. At the same time, due to the working mechanism of the energy recovery system of new energy vehicles, the load form, load spectrum technical characteristics, and failure focus points borne by the main reduction gear are quite different from those of the traditional axle reducer gear. Therefore, the original accelerated life load spectrum for traditional reducer gears cannot be directly applied to the reducer gear of the parallel-axis electric drive axle, and the vehicle test consumes a large amount of manpower and material resources. It is necessary to recompile the accelerated life program load spectrum for the main reduction gear of the parallel-axis electric drive axle. Summary of the Invention

[0003] The present invention is to solve the problems of irregular load distribution of the main reduction gear in the parallel-axis electric drive axle and time-consuming and laborious vehicle tests in the above-mentioned prior art, and proposes a method for compiling a load spectrum for an accelerated life bench test of the main reduction gear in a parallel-axis electric drive axle, in order to realize the analysis of the load distribution law characteristics of the main reduction gear, and transfer the fatigue life test of the main reduction gear from the test field to the bench on the premise of ensuring the equivalent damage of the road test and the bench test, so as to facilitate the Clowsey design and evaluation of the main reduction gear of the parallel-axis electric drive axle.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] The method for compiling a load spectrum for an accelerated life bench test of a main reduction gear in a parallel-axis electric drive axle according to the present invention is characterized in that it is carried out according to the following steps:

[0006] Step 1, obtain the road load spectrum of the parallel-axis electric drive axle under different working conditions under the vehicle conditions of the test field, including: the rotational speed signal and torque signal of the parallel-axis electric drive axle when the vehicle starts, accelerates, moves at a constant speed, decelerates, coasts, and brakes under full load and no load; and perform consistency verification on the maximum, minimum, and range of the road load spectrum of the parallel-axis electric drive axle under each working condition. If all verifications pass, then execute Step 2; otherwise, return to Step 1 to re-obtain the road load spectrum;

[0007] Step 2: Establish a dynamic model of the parallel-axis electric drive axle, and input the road load spectra of the parallel-axis electric drive axle under different working conditions into the dynamic model to convert the main reduction gear of the parallel-axis electric drive axle, so as to obtain the rotational speed signal and torque signal of the main reduction gear of the parallel-axis electric drive axle under different working conditions;

[0008] Step 3: Use the rotational rainflow counting method to analyze the statistical laws of the rotational speed signal and torque signal of the main reduction gear, so as to determine the probability density function of the load of the main reduction gear according to the statistical laws;

[0009] Step 4: Based on the probability density function of the load of the main reduction gear, obtain the torque frequency matrix F1 of the main reduction gear, and according to F1, use the Monte Carlo method to randomly simulate and extrapolate the rotational speed signal and torque signal of the main reduction gear by N times to obtain the extrapolated torque frequency matrix , and then according to Obtain the torque load spectra of the main reduction gear under different working conditions, and amplify them to the torque load spectra at the target mileage, so as to perform rainflow superposition on the torque load spectra at the target mileage under different working conditions to obtain the load spectra within the full life cycle of the main reduction gear in the parallel-axis electric drive axle;

[0010] Step 5: Establish a finite element model of the main reduction gear in the parallel-axis electric drive axle, and based on the load spectra within the full life cycle of the main reduction gear, obtain the stress spectra of the critical points of the load spectra within the full life cycle of the main reduction gear in the parallel-axis electric drive axle, and divide the critical point stresses into x equal-spacing levels according to their numerical values;

[0011] Step 6: Based on the stress spectra of the critical points of the load spectra within the full life cycle of the main reduction gear, according to the S-N curve and Miner criterion of the material of the main reduction gear in the parallel-axis electric drive axle, obtain the damage, total damage and fatigue life of the main reduction gear at each level through the virtual iteration method;

[0012] Step 7: Take the total damage of the main reduction gear as the objective function, and the torque and rotational speed of the main reduction gear as the constraints, establish an equation relationship where the total damage under the accelerated load spectrum is equal to the total damage under the original load spectrum, and use the genetic algorithm to solve the equation relationship to obtain the optimal accelerated load spectrum of the main reduction gear in the parallel-axis electric drive axle.

[0013] The feature of the load spectrum compilation method for the accelerated life bench test of the main reduction gear in the parallel-axis electric drive axle described in the present invention also lies in that Step 7 is carried out according to the following steps:

[0014] Step 7-1: Based on the damage at each level, determine the minimum working condition torque of the accelerated load spectrum, and according to the actual operating conditions of the vehicle, divide the torque of the main reduction gear into positive torque and negative torque, divide the positive torque into m equal-spacing levels, and divide the negative torque into n equal-spacing levels;

[0015] Step 7-2: Determine the minimum running time T of positive torque at all levels according to the actual bench test conditions. + min and the maximum time T + max , Minimum running time T at all levels in negative torque - min and the maximum time T - max , and the speed range of the main reduction gear, and serve as the torque constraint and speed constraint of the main reduction gear accordingly;

[0016] Step 7-3, taking the total damage of the main reducer gear as the objective function, and solving it by using a genetic algorithm, so as to obtain the optimal acceleration load spectrum under the load condition parameters that meet the damage equivalence and the shortest running time.

[0017] An electronic device of the present invention includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the method, and the processor is configured to execute the program stored in the memory.

[0018] The present invention provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and the computer program executes the steps of the method when executed by a processor.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The present invention proposes a method for compiling a program load spectrum suitable for an accelerated life test of a main reduction gear of a parallel shaft electric drive axle. Due to the working mechanism of the energy recovery system of a new energy vehicle, the load form, load spectrum technical characteristics and failure focus points borne by the main reduction gear are quite different from those of traditional axle reducer gears. In the specific case of fatigue life of the parallel shaft electric drive axle involved in the present invention, the distribution law of the main reduction gear load can be statistically calculated using the rotating rain flow counting method, and the load spectrum of the main reduction gear in the parallel shaft electric drive axle during the full life cycle can be obtained using the rain flow superposition method. A probability density function calculation method for the load distribution law of the main reduction gear of a parallel shaft electric drive axle is provided, and then a load spectrum of a main reduction gear bench test of a parallel shaft electric drive axle can be compiled.

[0021] 2. The present invention uses a genetic algorithm to optimize the accelerated life load spectrum with the shortest operating time under the condition of equivalent damage, which can solve the reliability bench test problem of the main reduction gear of a parallel-axis electric drive axle. It transfers the reliability test of the main reduction gear of the electric drive axle from the vehicle test to the bench. By means of a new load spectrum compilation method, it solves the problems of complex load distribution and irregular amplitude distribution of the main reduction gear of the parallel-axis electric drive axle, and greatly shortens the test cycle. Description of the Drawings

[0022] Figure 1 It is the torque From-to distribution diagram of the main reduction gear of the parallel-axis electric drive axle under the urban road condition of the present invention;

[0023] Figure 2 It is the torque mean value distribution diagram of the main reduction gear of the parallel-axis electric drive axle under the extrapolated urban road condition of the present invention;

[0024] Figure 3 It is the comparison diagram of the load distribution of the main reduction gear of the parallel-axis electric drive axle before and after extrapolation under the urban road condition of the present invention;

[0025] Figure 4 It is the frequency diagram of the 64-level load spectrum within the full life cycle of the main reduction gear of the present invention, where the red line represents the frequency diagram of the original 64-level load spectrum, and the blue line is the frequency diagram of the extrapolated 64-level load spectrum;

[0026] Figure 5 It is the positive torque load spectrum of the present invention;

[0027] Figure 6 It is the negative torque load spectrum of the present invention;

[0028] Figure 7 It is the flow chart of the method of the present invention. Detailed Embodiment

[0029] In this embodiment, a relatively intuitive and clear load spectrum compilation method for the accelerated life bench test of the main reduction gear in a parallel-axis electric drive axle is to solve the reliability bench test problem of the parallel-axis electric drive axle. By means of a new load spectrum compilation method, it solves the problems of complex working condition loads, irregular load distribution, long real vehicle test cycle and high cost of the parallel-axis electric drive axle. Specifically, as Figure 7 shown in the flow chart of the method of the present invention, this method is carried out according to the following steps:

[0030] Step 1: Obtain the road load spectra of the parallel-axis electric drive axle under different working conditions under the whole vehicle conditions of the test site, including: the rotational speed signals and torque signals of the parallel-axis electric drive axle during vehicle start, acceleration, constant speed, deceleration, coasting, and braking when fully loaded and unloaded; and perform consistency checks on the maximum, minimum, and range of the road load spectra of the parallel-axis electric drive axle under each working condition. If all the checks pass, proceed to Step 2; otherwise, return to Step 1 to re-obtain the road load spectra.

[0031] According to the actual driving conditions of the vehicle and the vehicle industry standards Q / JQ 13143.1-2022 Test Method for Collecting Road Load Spectra of Whole Vehicles, Q / JQ 13303-2020 Test Method for Structural Reliability Driving Test of Passenger Vehicles in Xingang Test Site, and Q / JQ 13302.2-2023 Test Method for Reliability Driving Test of Power Transmission Systems of New Energy Passenger Vehicles in Xingang Test Site, divide the whole vehicle road load spectrum working conditions into 3 working conditions: high-speed road working condition, light-duty durability road working condition, and urban road working condition.

[0032] The high-speed road working condition includes the high-speed road maximum speed working condition and the variable speed working condition. The light-duty durability road working condition includes pothole road, cobblestone road, vibrating road, rib road, cement damaged road, rib road, same-phase wave road, curb impact road, speed bump, twisted road, rough asphalt / buildup road, cement concrete impact road, asphalt pothole road, European brick road, diamond brick road, washboard road, nylon rope road, railway road, regular long-wave road, Belgian road, manhole cover road, speed limit marking working condition. The urban road working condition is a random urban road working condition.

[0033] Obtain the rotational speed and torque load spectra of the parallel-axis electric drive axle of the whole vehicle under the high-speed road working condition, light-duty durability road working condition, and urban road working condition. The high-speed road working condition, light-duty durability road working condition, and urban road working condition include fully loaded and unloaded conditions. Collect 3 groups of data for each working condition, a total of 18 groups of data.

[0034] According to the working condition division of the 18 groups of collected data, perform consistency checks on the maximum, minimum, and range of the three groups of data under each working condition. Ratio = , and the magnification error of each group of data is concentrated within ±20%, indicating that the collected data is valid. If all the checks pass, proceed to Step 2; otherwise, return to Step 1 to re-obtain the road load spectra.

[0035] Step 2: Establish a dynamic model of the parallel-axis electric drive axle, and input the road load spectra of the parallel-axis electric drive axle under different working conditions into the dynamic model for the conversion of the main reduction gear of the parallel-axis electric drive axle, so as to obtain the rotational speed signal and torque signal of the main reduction gear of the parallel-axis electric drive axle under different working conditions.

[0036] Step 3: Use the rotational rainflow counting method to analyze the statistical laws of the rotational speed signal and torque signal of the main reduction gear, and thus determine the probability density function of the load of the main reduction gear according to the statistical laws;

[0037] According to the service life calculation method under variable load conditions in the load-carrying capacity calculation of spur gears and helical gears in GB / T 3480.6-2018, the torque load spectra obtained by decomposition under different working conditions are divided into 64 equal intervals according to numerical values. The 64-level torque mean distribution under different working conditions obtained by using the rotational rainflow counting method is as Figure 1 shown in the torque From-to distribution diagram of the main reduction gear of the parallel-axis electric drive axle under urban road conditions after rotational rainflow counting;

[0038] Determine the Gaussian kernel K as the kernel density function of non-parametric kernel density estimation according to the obtained load mean distribution above. Its non-parametric kernel density function is Equation (1):

[0039] (1)

[0040] In Equation (1), n is the torque sample size; h is the bandwidth of the kernel density function, which affects the smoothness of the estimation; K is the Gaussian kernel function, as shown in Equation (2); x i is the i-th sample point;

[0041] (2)

[0042] The bandwidth expression is shown in Equation (3):

[0043] (3)

[0044] In Equation (3), is the sample standard deviation, and its calculation formula is shown in Equation (4):

[0045] (4)

[0046] In Equation (4), is the number of cycles of the mean value, is the mean value of all the number of cycles.

[0047] Step 4: Based on the probability density function of the load of the main reduction gear, obtain the torque frequency matrix F1 of the main reduction gear. And according to F1, use the Monte Carlo method to randomly simulate and extrapolate the rotational speed signal and torque signal of the main reduction gear by N times to obtain the extrapolated torque frequency matrix and then according to obtain the torque load spectra of the main reduction gear under different working conditions, as Figure 2 shown in the torque From-to distribution diagram of the main reduction gear of the parallel-axis electric drive axle under urban road conditions after extrapolation, as Figure 3The figure shows the comparison diagram of the load distribution before and after extrapolation of the main reduction gear of the parallel-axis electric drive axle under urban road conditions. The red line represents the original 64-level load spectrum frequency diagram, and the blue line is the 64-level load spectrum frequency diagram after extrapolation. By comparing whether the load distribution forms before and after extrapolation are consistent, the accuracy of the load spectrum after extrapolation is verified, and the load spectrum after extrapolation is magnified to the target mileage: 80,000 km for highway conditions, 10,000 km for light-duty durability road conditions, and 10,000 km for urban road conditions. The rain flow superposition is performed on the load at the target mileage of different conditions to obtain the load spectrum within the full life cycle of the main reduction gear of the parallel-axis electric drive axle;

[0048] Step 5: Establish a finite element model of the main reduction gear in the parallel-axis electric drive axle, and based on the load spectrum within the full life cycle of the main reduction gear, obtain the stress spectrum of the critical points of the load spectrum within the full life cycle of the main reduction gear in the parallel-axis electric drive axle, and divide the stress at the critical points into x = 64 equal intervals according to the torque magnitude, as Figure 4 shown in the 64-level load spectrum frequency diagram within the full life cycle of the main reduction gear of the present invention, and each level corresponds to the number of cycles at that level;

[0049] Step 6: Based on the stress spectrum of the critical points of the load spectrum within the full life cycle of the main reduction gear, according to the S-N curve and Miner's criterion of the material of the main reduction gear in the parallel-axis electric drive axle, obtain the damage, total damage, and fatigue life of the main reduction gear at each level through the virtual iteration method;

[0050] According to the 64-level stress load spectrum and the S-N curve and Miner cumulative damage theory of the material of the main reduction gear, calculate the damage and fatigue life of the main reduction gear at each level, and the cumulative damage value , when is equal to or exceeds 1, the material will undergo fatigue failure; m is the number of load levels; is the actual number of cycles experienced at the jth stress level, is the number of cycles that the material can withstand until fatigue failure at the jth torque stress level.

[0051] The damage of the main reduction gear is calculated, and the fatigue life of the main reduction gear .

[0052] Step 7: Taking the total damage of the main reduction gear as the objective function and the torque and speed of the main reduction gear as the constraints, establish an equation relationship where the total damage under the accelerated load spectrum is equal to the total damage under the original load spectrum, and use the genetic algorithm to solve the equation relationship to obtain the optimal accelerated load spectrum of the main reduction gear in the parallel-axis electric drive axle;

[0053] Step 7-1: Based on the damage at each level, determine the minimum operating condition torque of the acceleration load spectrum. According to the actual operating conditions of the vehicle, divide the torque of the main reduction gear into positive torque and negative torque. Divide the positive torque into 8 equally spaced levels and divide the negative torque into n = 8 equally spaced levels;

[0054] Step 7-2: According to the actual bench test conditions, determine the minimum operating time T + min = 1 hour and the maximum time T + max = 150 hours for all levels of positive torque, the minimum operating time of 1 hour and the maximum time of 150 hours for all levels of negative torque, and the speed range of the main reduction gear, and use them as the torque constraint and speed constraint of the main reduction gear accordingly;

[0055] Step 7-3: Take the total damage of the main reduction gear as the objective function and use the genetic algorithm to solve it to obtain the optimal acceleration load spectrum under the load condition parameters that satisfy damage equivalence and the shortest operating time, as Figure 5 shown is the positive torque load spectrum compiled by the present invention, as Figure 6 shown is the negative torque load spectrum compiled by the present invention. When compiling the load spectrum, use the "low-high-low" loading method to compile the load spectrum;

[0056] Step 8: Through the rigid-flexible coupling finite element model of the parallel-axis electric drive axle, the material characteristic curves of the key components of the parallel-axis electric drive axle, the Miner linear cumulative damage theory, and the program load spectrum, obtain the fatigue life and damage of the key components of the parallel-axis electric drive, and verify the equivalence before and after the compilation of the program load spectrum.

[0057] In this embodiment, an electronic device includes a memory and a processor. The memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0058] In this embodiment, a computer-readable storage medium stores a computer program on the computer-readable storage medium. When the computer program is run by the processor, it executes the steps of the above method.

Claims

1. A method for compiling a load spectrum of an accelerated life bench test of a main reduction gear in a parallel-axis electric drive axle, characterized in that, The steps are as follows: Step 1: Obtain the road load spectra of the parallel-axis electric drive axle under different working conditions in the whole vehicle condition of the test site, including: the rotational speed signals and torque signals of the parallel-axis electric drive axle during vehicle start, acceleration, constant speed, deceleration, coasting, and braking under full load and no load; and perform consistency verification of the maximum, minimum, and range for the road load spectra of the parallel-axis electric drive axle under each working condition. If all verifications pass, proceed to Step 2; otherwise, return to Step 1 to re-obtain the road load spectra. Step 2: Establish a dynamic model of the parallel-axis electric drive axle, and input the road load spectra of the parallel-axis electric drive axle under different working conditions into the dynamic model to perform transformation of the main reduction gear of the parallel-axis electric drive axle, so as to obtain the rotational speed signals and torque signals of the main reduction gear of the parallel-axis electric drive axle under different working conditions. Step 3: Use the rotational rainflow counting method to analyze the statistical laws of the rotational speed signals and torque signals of the main reduction gear, so as to determine the probability density function of the load of the main reduction gear according to the statistical laws. Step 4: Based on the probability density function of the main reduction gear load, obtain the torque frequency matrix F1 of the main reduction gear. According to F1, use the Monte Carlo method to randomly simulate and extrapolate the rotational speed signal and torque signal of the main reduction gear by N times to obtain the extrapolated torque frequency matrix , and then according to obtain the torque load spectra of the main reduction gear under different working conditions, and amplify them to the torque load spectra at the target mileage, so as to perform rainflow superposition on the torque load spectra at the target mileage under different working conditions, and obtain the load spectra within the full life cycle of the main reduction gear in the parallel-axis electric drive axle; Step 5: Establish a finite element model of the main reduction gear in the parallel-axis electric drive axle, and based on the load spectra during the entire life cycle of the main reduction gear, obtain the stress spectra of the critical points of the load spectra during the entire life cycle of the main reduction gear in the parallel-axis electric drive axle, and divide the critical point stresses into x equally spaced levels according to their numerical magnitudes. Step 6: Based on the stress spectra of the critical points of the load spectra during the entire life cycle of the main reduction gear, according to the S-N curve and Miner criterion of the material of the main reduction gear in the parallel-axis electric drive axle, obtain the damage, total damage, and fatigue life of the main reduction gear at each level through the virtual iteration method. Step 7: Take the total damage of the main reduction gear as the objective function, and take the torque and rotational speed of the main reduction gear as constraints, establish an equation relationship where the total damage under the accelerated load spectrum is equal to the total damage under the original load spectrum, and use the genetic algorithm to solve the equation relationship to obtain the optimal accelerated load spectrum of the main reduction gear in the parallel-axis electric drive axle.

2. The method for compiling a load spectrum of an accelerated life bench test of a main reduction gear in a parallel-axis electric drive axle according to claim 1, characterized in that, Step 7 is carried out as follows: Step 7-1: Determine the minimum working condition torque of the accelerated load spectrum based on the damage at each level, and according to the actual operating conditions of the vehicle, divide the torque of the main reduction gear into positive torque and negative torque, divide the positive torque into m equally spaced levels, and divide the negative torque into n equally spaced levels. Step 7-2: Determine the minimum running time T and the maximum running time T of the positive torque at all levels according to the actual bench test conditions, the minimum running time T and the maximum running time T of the negative torque at all levels, and the rotational speed range of the main reduction gear, and use them as the torque constraint and rotational speed constraint of the main reduction gear accordingly. + min and the maximum time T + max of the minimum running time T - min and the maximum time T - max of the negative torque at all levels, as well as the rotational speed range of the main reduction gear, and use them as the torque constraint and rotational speed constraint of the main reduction gear accordingly. Step 7-3: Take the total damage of the main reduction gear as the objective function, and use the genetic algorithm to solve it to obtain the optimal accelerated load spectrum under the load condition parameters that satisfy damage equivalence and the shortest operating time.

3. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program for supporting the processor to execute the load spectrum preparation method for the accelerated life bench test described in Claim 1 or 2, and the processor is configured to execute the program stored in the memory.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it executes the steps of the load spectrum preparation method for the accelerated life bench test described in Claim 1 or 2.

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