Method for accurately acquiring impact load of supporting bearing of automobile driving assembly

Abstract

The invention relates to the field of automobile driving assembly load identification, in particular to a method for accurately obtaining the impact load of a supporting bearing of an automobile driving assembly. According to the method, a driving assembly dynamic model is established, the incidence relation between a detection signal and a torque signal is reconstructed, the actual half-shaft real-time torque is obtained, and the whole vehicle half-shaft real-time torque and the driving end rotating speed serve as input of the driving assembly dynamic model; accurate important load boundary data are provided for comprehensively evaluating the static safety coefficient and the fatigue life of the support bearing, the accuracy of bearing model selection and checking during product development is ensured, and the product quality robustness is improved.

Description

Technical Field

[0001] The present invention relates to the field of automobile drive assembly load identification, and in particular to a method for accurately obtaining the impact load of a support bearing of an automobile drive assembly. Background Art

[0002] As a key component of the automotive drivetrain, support bearings play an irreplaceable role in transmitting power and supporting rotating parts. Underestimating the support bearing's load boundary can lead to premature failure due to excessive loads during actual use, compromising drivetrain performance and even causing safety accidents. Accurately capturing impact load data on automotive drivetrain support bearings is crucial for ensuring accurate load boundary identification, playing a crucial role in the design of automotive drivetrains.

[0003] However, it is very difficult to accurately obtain the impact load of the vehicle drive assembly support bearing for the following reasons:

[0004] ① Complex working conditions: The working environment of the vehicle drive assembly is extremely complex. When dealing with various road and driving conditions, frequent acceleration, deceleration and energy recovery will cause the output torque of the drive motor or the generator motor to fluctuate significantly, directly acting on the support bearing, causing its load to fluctuate rapidly, making it extremely difficult to capture its load;

[0005] ②Sensor limitations: Directly measuring bearing loads requires installing sensors inside or near the bearings. However, the compact design of automotive drivetrains limits the installation space for sensors, making installation difficult and potentially impacting bearing performance.

[0006] ③ The dynamic response of the system places high demands on hardware: Due to the short duration and high amplitude of the impact load, the sensor and acquisition system are required to have a high sampling rate and fast response capabilities, which increases the difficulty of measurement;

[0007] ④Multi-factor coupling: The impact load on the bearing is the result of the coupling of multiple factors such as the torque output of the drive end (engine or drive motor), road excitation, and transmission system vibration. The relationship between these factors is complex, and it is difficult to accurately separate and quantify their respective contributions to the bearing impact load, which increases the difficulty of determining the impact load magnitude;

[0008] ⑤ Cost and reliability: High-precision sensors and systems are expensive and need to work stably for a long time in harsh environments, which increases technical difficulty and cost pressure.

[0009] Typically, the performance of automotive drivetrain support bearings is evaluated based on the impact load data of the drive motor support bearings and the reducer support bearings. However, there is currently no reliable method for obtaining impact load data for reducer support bearings. Furthermore, impact load data for drive motor support bearings is estimated based solely on design experience, calculated by calculating the weight exerted on the supporting rotor at multiples to dozens of times the force, which is not very accurate. Therefore, existing technology cannot comprehensively and accurately evaluate the performance of automotive drivetrain support bearings.

[0010] Therefore, how to accurately obtain the impact load of the support bearing of the automobile drive assembly has always been a problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0011] The purpose of the present invention is to address the corresponding deficiencies in the existing technology and provide a method for accurately obtaining the impact load of the support bearing of an automobile drive assembly. By establishing a dynamic model of the drive assembly and reconstructing the correlation between the detection signal and the torque signal, a more realistic real-time torque of the half-shaft is obtained, and the real-time torque of the half-shaft of the entire vehicle and the driving end speed are used as inputs to the dynamic model of the drive assembly, thereby obtaining the actual impact load data of the support bearing of the automobile drive assembly, providing accurate important load boundary data for a comprehensive evaluation of the static safety factor and fatigue life of the support bearing, ensuring the accuracy of bearing selection and verification during product development, and improving the robustness of product quality.

[0012] The purpose of the present invention is to adopt the following scheme to achieve:

[0013] A method for accurately obtaining the impact load of a support bearing of an automobile drive assembly comprises the following steps:

[0014] 1) Determine the test content for identifying impact loads and establish a drive assembly dynamics simulation model;

[0015] 2) Install wireless telemetry sensors on both axles of the test vehicle to obtain real-time torque during driving. Calibration experiments are then performed to obtain data used to correct the output of the wireless telemetry sensors during driving.

[0016] 3) Based on the test content for identifying impact loads, multiple full-vehicle impact tests are conducted on the test vehicle to obtain real-time torque data on both half-axles of the test vehicle and record the speed data of the drive assembly input end of the test vehicle during the entire driving process;

[0017] 4) The real-time torque data of the two half-axles of the test vehicle and the speed data of the drive assembly input end are input into the drive assembly dynamics simulation model for dynamic simulation to obtain the impact load data of the vehicle drive assembly support bearing.

[0018] Preferably, in step 2), the specific steps of obtaining data for correcting the output results of the wireless telemetry sensor during driving through a calibration experiment are as follows:

[0019] 2-1) Install a torque sensor on each half-axle of the test vehicle to obtain standard torque data, and fix the two half-axles on the half-axle test bench;

[0020] 2-2) When no torque is applied to the two half-axles, record the initial values ​​of the wireless telemetry sensors on the two half-axles respectively;

[0021] 2-3) gradually applying torque to the half-shaft according to a certain torque increment, and repeatedly measuring and recording the detection signal value of the wireless telemetry sensor;

[0022] 2-4) Based on the standard torque data and the distribution characteristics of the recorded wireless telemetry sensor detection signal values, data for correcting the output results of the wireless telemetry sensor during driving is obtained.

[0023] Preferably, before performing multiple whole vehicle impact tests on the test vehicle, a whole vehicle test is performed on the test vehicle according to the test content for identifying the impact load to determine the optimal sampling rate.

[0024] Preferably, the specific method of determining the optimal sampling rate is as follows:

[0025] ① According to the sampling theorem, determine the sampling rate range of the vehicle test run;

[0026] ② Within the sampling rate range, according to the test conditions determined in the test method, the half-axle torque signal of the test vehicle is collected at different sampling rates to obtain the PSD spectrum of the half-axle torque signal;

[0027] ③Analyze the PSD spectrum of the half-shaft torque signal obtained in step ② to determine the optimal sampling rate.

[0028] Preferably, in step 3), according to the test content of identifying the impact load, the specific steps of performing multiple vehicle impact tests on the test vehicle and obtaining the real-time torque data of the two half-axles of the test vehicle are as follows:

[0029] 3-1) Based on the optimal sampling rate and the test content for identifying impact loads, multiple vehicle impact tests are conducted on the test vehicle, and torque data is collected;

[0030] 3-2) Compare the torque data obtained from multiple vehicle impact tests and use the data from the most obvious impact as the actual collected data;

[0031] 3-3) Based on the actual collected data and the data used to correct the output results of the wireless telemetry sensor during driving, the corresponding real-time torque data of the two half-axles are obtained respectively.

[0032] Preferably, in step 2), the wireless telemetry sensor is arranged at a position close to the output end of the test vehicle drive assembly.

[0033] The beneficial effects of the present invention are as follows:

[0034] A method for accurately obtaining the impact load of a support bearing of an automobile drive assembly comprises the following steps:

[0035] 1) Determine the test content for identifying impact loads and establish a drive assembly dynamics simulation model;

[0036] 2) Install wireless telemetry sensors on both axles of the test vehicle to obtain real-time torque during driving. Calibration experiments are then performed to obtain data used to correct the output of the wireless telemetry sensors during driving.

[0037] 3) Based on the test content for identifying impact loads, multiple full-vehicle impact tests are conducted on the test vehicle to obtain real-time torque data on both half-axles of the test vehicle and record the speed data of the drive assembly input end of the test vehicle during the entire driving process;

[0038] 4) The real-time torque data of the two half-axles of the test vehicle and the speed data of the drive assembly input end are input into the drive assembly dynamics simulation model for dynamic simulation to obtain the impact load data of the vehicle drive assembly support bearing.

[0039] The present invention combines the real-time data obtained from the impact working conditions of the entire vehicle with virtual prototype technology to obtain automobile drive assembly support bearing impact load data that is closer to the actual situation, significantly improving the accuracy of impact load identification.

[0040] This method can accurately measure the impact load of support bearings, providing accurate and crucial data for comprehensively evaluating the static safety factor and fatigue life of support bearings. This allows for a comprehensive assessment of bearing risks before product development is complete, effectively reducing unnecessary quality losses during the development phase due to incomplete identification of load boundaries and insufficient product design verification, thereby improving product design robustness.

[0041] The bearing impact load identified by the present invention has wide applicability and can cover similar vehicle models equipped with similar drive assemblies, effectively avoiding the waste of test resources, shortening the development cycle, and reducing development costs.

[0042] Preferably, in step 2), the specific steps of obtaining data for correcting the output results of the wireless telemetry sensor during driving through a calibration experiment are as follows:

[0043] 2-1) Install a torque sensor on each half-axle of the test vehicle to obtain standard torque data, and fix the two half-axles on the half-axle test bench;

[0044] 2-2) When no torque is applied to the two half-axles, record the initial values ​​of the wireless telemetry sensors on the two half-axles respectively;

[0045] 2-3) gradually applying torque to the half-shaft according to a certain torque increment, and repeatedly measuring and recording the detection signal value of the wireless telemetry sensor;

[0046] 2-4) Based on the standard torque data and the distribution characteristics of the recorded wireless telemetry sensor detection signal values, data for correcting the output results of the wireless telemetry sensor during driving is obtained.

[0047] The present invention reconstructs the correlation between the detection signal and the torque signal based on the actual installation status of the current wireless telemetry sensor, which can ensure that the acquired measurement data is derived from the current accurate wireless telemetry sensor status and actual installation conditions. It can effectively eliminate the measurement deviation caused by the change of the installation position of the wireless telemetry sensor, thereby significantly improving the accuracy of torque measurement.

[0048] Preferably, before performing multiple whole vehicle impact tests on the test vehicle, a whole vehicle test is performed on the test vehicle according to the test content for identifying the impact load to determine the optimal sampling rate.

[0049] Preferably, the specific method of determining the optimal sampling rate is as follows:

[0050] ① According to the sampling theorem, determine the sampling rate range of the vehicle test run;

[0051] ② Within the sampling rate range, according to the test conditions determined in the test method, the half-axle torque signal of the test vehicle is collected at different sampling rates to obtain the PSD spectrum of the half-axle torque signal;

[0052] ③Analyze the PSD spectrum of the half-shaft torque signal obtained in step ② to determine the optimal sampling rate.

[0053] The present invention uses the sampling theorem as its theoretical basis and adopts different sampling rates to collect data multiple times under constant working conditions. By analyzing the collected data, the optimal sampling rate is accurately obtained, which strictly meets the requirements of the sampling theorem and ensures that the signal remains undistorted during the collection and transmission process. In the subsequent vehicle impact test, the original signal can be restored with high precision, which not only significantly improves the efficiency of data processing, but also effectively reduces the test cost.

[0054] Preferably, in step 3), according to the test content of identifying the impact load, the specific steps of performing multiple vehicle impact tests on the test vehicle and obtaining the real-time torque data of the two half-axles of the test vehicle are as follows:

[0055] 3-1) Based on the optimal sampling rate and the test content for identifying impact loads, multiple vehicle impact tests are conducted on the test vehicle, and torque data is collected;

[0056] 3-2) Compare the torque data obtained from multiple vehicle impact tests and use the data from the most obvious impact as the actual collected data;

[0057] 3-3) Based on the actual collected data and the data used to correct the output results of the wireless telemetry sensor during driving, the corresponding real-time torque data of the two half-axles are obtained respectively.

[0058] The present invention conducts multiple vehicle impact tests and uses the data with the most obvious impact as the actual collected data. It can effectively simulate the impact conditions that bearings are subjected to under extreme working conditions, and further obtain the impact load data of the supporting bearings, providing some valuable reference for subsequent technical research and product design.

[0059] In the vehicle impact test of the present invention, the real-time torque of the left and right half-axles is obtained more accurately by combining the collected data with the data determined by the calibration test and used to correct the output results of the wireless telemetry sensor during driving.

[0060] Preferably, in step 2), the wireless telemetry sensor is arranged at a position close to the output end of the drive assembly.

[0061] By arranging the wireless telemetry sensor near the output end of the drive assembly, the present invention can effectively shorten the transmission distance between the wireless telemetry sensor and the impact source, greatly reduce the influence of the impact load attenuation during the transmission process on the detection results of the wireless telemetry sensor, and ensure that the data collected by the wireless telemetry sensor can more realistically and accurately reflect the actual load conditions at the output end of the drive assembly.

[0062] Glossary:

[0063] Sampling Theorem: In the process of analog / digital signal conversion, when the sampling rate f s Greater than the highest frequency f in the signal max When it is twice as much, that is, f s >2f max , the digital signal after sampling completely retains the information in the original signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is a flow chart of the present invention;

[0065] Figure 2 A schematic diagram of a flow chart of an embodiment of the present invention;

[0066] Figure 3 A schematic diagram of vehicle impact load collection resource preparation according to an embodiment of the present invention;

[0067] Figure 4 A schematic diagram of a test vehicle for an embodiment of the present invention is prepared;

[0068] Figure 5 Schematic diagram of the basic principle of torque detection by a wireless telemetry sensor in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] like Figures 1 to 5 As shown, the method for accurately obtaining the impact load of the support bearing of the automobile drive assembly includes the following steps:

[0070] Before identifying the impact load on the vehicle drive assembly support bearing, follow the steps below: Figure 2 、 Figure 3 As shown, preparation work on resources for collecting impact loads of the whole vehicle and preparation of the test vehicle are carried out.

[0071] When identifying the impact load of the automobile drive assembly support bearing in the present invention, the required resources include the following aspects:

[0072] Software: The SoMat eDAQ data logger includes built-in load acquisition software and load spectrum data processing software (ncode). Before the test begins, these software components undergo detailed setup and debugging, including configuration of all channel signals, selection of target data, and setting of acquisition parameters.

[0073] Hardware: SoMat eDAQ data acquisition instrument, sensors, computer, connecting cables, adapters (as needed), etc. Building a test system based on this hardware includes establishing connections between the sensors, data acquisition equipment, and computer, laying out and securing the overall wiring, and installing and securing the data acquisition equipment.

[0074] Other test resources: test vehicle, counterweight, test site, and driver. Specific parameters of the test vehicle in this embodiment are detailed in Table 1.

[0075] Table 1

[0076] Model A00-class car Drive Mode Front-engine, front-wheel drive Maximum speed 101km / h Curb weight 840Kg Fully loaded mass 1140KG counterweight 180Kg Maximum motor speed 10480rpm Overall speed ratio 8.06

[0077] 1) Determine the test content for identifying impact loads based on specific needs and establish a drive assembly dynamics simulation model. In this embodiment, the drive assembly dynamics simulation model has been calibrated during the establishment process;

[0078] Specifically, the test content for identifying impact loads includes test conditions and test operating conditions. In the present invention, the determination of the test content is the result of comprehensive consideration of multi-dimensional factors such as vehicle driving experience, product development requirements, test site facility conditions, and user-specific technical requirements. In particular, in response to the user's requirements for assessment of extraordinary operating conditions (i.e., special operating condition verification requirements that require breaking through conventional design boundary conditions), this test scheme dynamically adjusts the vehicle operating mode and operating condition parameter combination to achieve accurate identification of the bearing system's load-bearing characteristics under extreme operating conditions.

[0079] As shown in Table 2, the test content adopted in this embodiment includes testing the impact load of the vehicle under different driving modes, vehicle weight distribution, test conditions, slopes, and accelerator and brake pedal operations:

[0080] Table 2

[0081]

[0082]

[0083] ① Vehicle driving mode: covers ECO mode, SPORT mode and other modes.

[0084] ② Vehicle counterweight: uniformly in full load state.

[0085] ③Test conditions:

[0086] Flat road acceleration / deceleration: On a flat road with a slope of 0%, test the impact load at speeds of 20Km / h, 40Km / h, 60Km / h and 80Km / h under four operation combinations: half throttle and light braking, full throttle and light braking, half throttle and heavy braking, and full throttle and heavy braking.

[0087] Special road surfaces: On special road surfaces such as twisted road surface, washboard road, Belgian road, tile road surface and cobblestone road, impact load tests are carried out at vehicle speeds of 15 km / h (twisted road surface and washboard road) and 40 km / h (Belgian road, tile road surface and cobblestone road), respectively. No specific operation of the accelerator pedal and brake pedal is involved.

[0088] Acceleration / deceleration when reaching the top of the slope: With slopes of 10%, 20%, and 30%, use a combination of full throttle and heavy braking to test the bearing impact load when the vehicle reaches the top of the slope and accelerates / decelerates.

[0089] In this example, a drivetrain dynamics simulation model was constructed based on the test vehicle's drivetrain using the professional dynamics analysis software platform AVL EXCITE. After the model was constructed, it was calibrated, and relevant parameters in the drivetrain dynamics simulation model were adjusted and optimized. This process was repeated until the simulation model output closely matched the actual test data within a reasonable error range, ensuring the high accuracy and reliability of the established drivetrain dynamics simulation model.

[0090] 2) Installing wireless telemetry sensors on both axles of the test vehicle to obtain real-time torque during driving and performing calibration experiments to obtain data used to correct the output of the wireless telemetry sensors during driving. The specific steps are as follows:

[0091] 2-1) Install a torque sensor on each half-axle of the test vehicle to obtain standard torque data, and fix the two half-axles on the half-axle test bench;

[0092] 2-2) When no torque is applied to the two half-axles, record the initial values ​​of the wireless telemetry sensors on the two half-axles respectively;

[0093] 2-3) gradually applying torque to the half-shaft according to a certain torque increment, and repeatedly measuring and recording the detection signal value of the wireless telemetry sensor;

[0094] 2-4) Based on the standard torque data and the distribution characteristics of the recorded wireless telemetry sensor detection signal values, data for correcting the output results of the wireless telemetry sensor during driving is obtained.

[0095] In this embodiment, the wireless telemetry sensor uses a bridge circuit composed of multiple strain gauges. The wireless telemetry sensor converts the torque load signal received by the half-shaft into a voltage signal. The wireless telemetry sensor is located close to the output end of the drive assembly (i.e., the transmission end), thereby shortening the transmission distance between the sensor and the impact source and minimizing the impact of the impact load attenuation during the transmission process on the sensor detection results. Figure 5 As shown in Figure 2, the basic principle of using this wireless telemetry sensor to detect torque is as follows:

[0096] A half-bridge strain gauge rosette (e.g., Rosette A and Rosette B) is attached to opposite sides of the half-shaft. The unidirectional strain gauges in these two rosettes are perpendicular to each other, forming a Wheatstone full bridge. This wireless telemetry sensor consists of a rotor module (Rotor-Unit) and a stator module (Stator-Unit). The rotor module is mounted on the half-shaft and rotates with it, while the stator module is stationary. It contains key measuring components, such as strain gauges. When the half-shaft deforms under torque load, the resistance of the strain gauge changes, thereby detecting the torque signal. The transmitting and receiving copper rings form a complete electromagnetic induction circuit (Transmission Coil), providing stable power to the rotor module without wired connections. When the half-shaft is subjected to torque load, the strain gauge resistance changes due to the deformation of the half-shaft, causing an imbalance in the Wheatstone full bridge. This imbalance in the bridge causes a voltage change on the receiving copper ring. This voltage signal is transmitted through the transmitting copper ring to the stator module and then to the control module. The control module conditions the signal and outputs it to the data acquisition system. During the calibration process, the collected voltage signal is matched one-to-one with the corresponding standard torque obtained by a standard high-precision torque sensor. Through data analysis and processing, data is generated to correct the output of the wireless telemetry sensor during driving. This establishes a relationship between the voltage and torque signals (e.g., fitting curves, display functions, etc.). This allows the test vehicle to be used in subsequent vehicle impact tests to align the output voltage signal with the standard torque during driving, resulting in a precise real-time torque reading, thereby improving the accuracy of real-time torque data acquisition.

[0097] like Figure 5 As shown, the wireless telemetry sensor connects the various components through a specific line connection method (a-2, b-1', 3, c-1, 3', d-2', etc.) to ensure accurate signal transmission. And because of the special strain gauge arrangement and full-bridge structure, the system can effectively resist the interference of external temperature changes and the tensile, compressive or bending loads on the transmission shaft. When these interference factors appear, the bridge circuit can still maintain balance and the output voltage is 0V, thereby ensuring high-precision torque measurement. In this embodiment, the voltage signal output by the wireless telemetry sensor is used as the detection signal, and in actual applications, other types of sensors (such as a six-component force sensor with wireless telemetry function) can also be used as a high-precision test sensor for the real-time torque of the half-shaft, but they are expensive and not very practical.

[0098] Specifically, by applying known torque loads (obtained by torque sensors) to the two half-shafts respectively, the output voltage signals of the wireless telemetry sensor under different torque conditions are obtained (i.e., the output voltage signal scatter points under different torques). These data are then processed and the display function curve y=f(x) is obtained through data fitting as the relationship curve between the detection signal and the torque signal.

[0099] Before conducting multiple full vehicle impact tests on the test vehicle, the test vehicle is subjected to full vehicle tests based on the test content for identifying the impact load to determine the optimal sampling rate.

[0100] Preferably, the specific method of determining the optimal sampling rate is as follows:

[0101] ① According to the sampling theorem, determine the sampling rate range of the vehicle test run;

[0102] In this embodiment, the maximum speed of the test vehicle's drive end determines the input frequency to be 174.7 Hz. According to the sampling theorem, the minimum sampling rate for this frequency signal should be twice 174.7 Hz, or 349.4 Hz, to fully preserve the information in the original signal. However, since the signal being collected is an impact signal, which has characteristics such as rapid transient changes and energy concentrated in a short period of time, a low sampling rate can easily miss critical information at the moment of impact. Therefore, the sampling rate was appropriately increased.

[0103] ② Within the sampling rate range, according to the test conditions determined in the test method, the half-axle torque signal of the test vehicle is collected at different sampling rates. In this embodiment, the half-axle torque signal under the same working conditions is collected at sampling rates of 1000Hz, 2000Hz, and 5000Hz, and the PSD spectrum of the half-axle torque signal is obtained using nCode software;

[0104] ③ Analyze the PSD spectrum of the half-axle torque signal obtained in step ②. Because a higher sampling rate means more data points are collected in the same time, the data collection data packet composed of these data will occupy a large amount of storage space. If the storage space is full, data collection can no longer be carried out. Therefore, this places high demands on the storage hardware capacity. Therefore, the minimum sampling rate that can collect signals without distortion while covering all operating conditions is generally selected as the optimal sampling rate. In this embodiment, through PSD spectrum analysis, 1000Hz was selected as the optimal sampling rate for the subsequent vehicle impact test. This sampling rate meets the requirement of PSD spectrum analysis to cover all operating conditions without placing an excessive burden on the hardware.

[0105] At the same time, during the vehicle test run, it can also ensure that key elements involved in the test process, such as sensors, data acquisition systems, and software settings, are in normal operation and free of any potential problems.

[0106] 3) Remove the torque sensor from the half-axle and secure the two half-axles in the vehicle. While installing the calibrated two half-axles in the test vehicle, arrange the fixed wiring harness and connect it to the vehicle, ensuring that the wiring harness does not get entangled or interfere with other moving parts to ensure safety. Based on the test content for identifying impact loads, conduct a full vehicle test on the test vehicle (this full vehicle test is performed while the test vehicle is driving). The specific method for obtaining the corresponding real-time torque data of the two half-axles is as follows:

[0107] 3-1) Based on the determined optimal sampling rate of 1000 Hz and in combination with the test content for identifying impact loads, multiple vehicle impact tests are performed on the test vehicle, and torque data is collected. In this embodiment, three vehicle impact tests and data collection are performed for each test condition and test operating condition.

[0108] 3-2) Compare the torque data from multiple vehicle impact tests, using the most significant impact data as the actual data. Specifically, process and analyze the collected data, using the most significant impact data from the three vehicle impact tests as the actual data. This effectively simulates the impact conditions experienced by the bearing under extreme operating conditions, further derives load boundary conditions, and provides valuable reference for subsequent technical research and product design.

[0109] 3-3) Based on the actual collected data and the data used to correct the wireless telemetry sensor's output during driving (i.e., the relationship curve y = f(x) between the detection signal and the torque signal), real-time torque data for the corresponding left and right axles is obtained. In this embodiment, by combining the actual collected data with the relationship between the detection signal and the torque signal determined through calibration testing, the obtained real-time torque data for the left and right axles is more accurate.

[0110] The speed of the input end of the drive assembly is obtained by:

[0111] ① Install a speed sensor at the half-shaft drive end to obtain speed data, and the installation test point of the speed sensor is close to the power input end;

[0112] ② Read speed-related data directly from the test vehicle CAN bus.

[0113] 4) The real-time torque data of the two half-axles of the test vehicle and the speed data of the drive assembly input end are input into the drive assembly dynamics simulation model for dynamic simulation to obtain the impact load data of the vehicle drive assembly support bearing.

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications made to the present invention by those skilled in the art without departing from the spirit of the present invention shall fall within the scope of protection of the present invention.

Claims

1. A method for accurately obtaining the impact load of a vehicle drive assembly support bearing, characterized in that: The following steps are involved: 1) Determine the test content for identifying impact loads and establish a drive assembly dynamics simulation model; 2) Wireless telemetry sensors were installed on both axles of the test vehicle to obtain real-time torque during driving. Calibration experiments were then performed to obtain data used to correct the output of the wireless telemetry sensors during driving. 3) Based on the test content for identifying impact loads, multiple full-vehicle impact tests are conducted on the test vehicle to obtain real-time torque data on both half-axles of the test vehicle and record the speed data of the drive assembly input end of the test vehicle during the entire driving process; 4) The real-time torque data of the two half-axles of the test vehicle and the speed data of the drive assembly input end are input into the drive assembly dynamics simulation model for dynamic simulation to obtain the impact load data of the vehicle drive assembly support bearing.

2. The method for accurately obtaining the impact load of the support bearing of the automobile drive assembly according to claim 1, characterized in that: In step 2), the specific steps for obtaining data for correcting the output results of the wireless telemetry sensor during driving through the calibration experiment are as follows: 2-1) Install a torque sensor on each half-axle of the test vehicle to obtain standard torque data, and fix the two half-axles on the half-axle test bench; 2-2) With no torque applied to the two half-axles, record the initial values ​​of the wireless telemetry sensors on the two half-axles: 2-3) Apply torque to the half-shaft gradually according to a certain torque increment, and measure and record the detection signal value of the wireless telemetry sensor multiple times; 2-4) Based on the standard torque data and the distribution characteristics of the recorded wireless telemetry sensor detection signal values, data for correcting the output results of the wireless telemetry sensor during driving is obtained.

3. The method for accurately obtaining the impact load of the support bearing of the automobile drive assembly according to claim 1, characterized in that: Before conducting multiple full vehicle impact tests on the test vehicle, the test vehicle is subjected to full vehicle tests based on the test content for identifying the impact load to determine the optimal sampling rate.

4. The method for accurately obtaining the impact load of the support bearing of the automobile drive assembly according to claim 3, characterized in that: The specific method to determine the optimal sampling rate is as follows: ① According to the sampling theorem, determine the sampling rate range of the vehicle test run; ② Within the sampling rate range, according to the test conditions specified in the test method, the half-axle torque signal of the test vehicle is collected at different sampling rates to obtain the PSD spectrum of the half-axle torque signal; ③ Analyze the PSD spectrum of the half-shaft torque signal obtained in step ② to determine the optimal sampling rate.

5. The method for accurately obtaining the impact load of a vehicle drive assembly support bearing according to claim 1 or 3, characterized in that: In step 3), according to the test content of identifying the impact load, multiple vehicle impact tests are performed on the test vehicle to obtain the real-time torque data of the two half-axles of the test vehicle. The specific steps are as follows: 3-1) Based on the optimal sampling rate and the test content for identifying impact loads, multiple vehicle impact tests are conducted on the test vehicle, and torque data is collected; 3-2) Compare the torque data obtained from multiple vehicle impact tests and use the data from the most obvious impact as the actual collected data; 3-3) Based on the actual collected data and the data used to correct the output results of the wireless telemetry sensor during driving, the real-time torque data of the corresponding two half-axles are obtained.

6. The method for accurately obtaining the impact load of a vehicle drive assembly support bearing according to claim 1, characterized in that: In step 2), the wireless telemetry sensor is arranged near the output end of the drive assembly of the test vehicle.

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