Yu Ziqiang,Yu Hui,Yu Renping.Optimization of NVH Performance of Electric Vehicle Reducers Based on Gear Transmission Error[J].Journal of Mechanical Transmission,2023,47(10):104-109.
Yu Ziqiang,Yu Hui,Yu Renping.Optimization of NVH Performance of Electric Vehicle Reducers Based on Gear Transmission Error[J].Journal of Mechanical Transmission,2023,47(10):104-109. DOI: 10.16578/j.issn.1004.2539.2023.10.015.
Optimization of NVH Performance of Electric Vehicle Reducers Based on Gear Transmission Error
Electric vehicle reducer gears have a wide range of torque speed when working
and transmission errors of gear pairs are different under different speed and torque conditions. In order to optimize the noise
vibration and harshness (NVH) performance of the reducer
the transfer error is optimized and improved for the common speed segment and common torque segment of electric vehicles. Firstly
Abaqus and Masta software are used to model and analyze the transmission error under different speed and torque conditions. Then
the gear is modified based on the data of common speed and torque conditions
and the transmission error after modification is analyzed. Finally
the modification effect is obtained by comparing the vibration and noise test of the reducer. The results show that the reducer runs at the usual speed and torque most of the time
the noise of the reducer is reduced by about 5 dB(A) and the NVH performance of the reducer is optimized by modification based on the transmission error data in this working condition.
关键词
电动汽车减速器常用转矩转速段传递误差NVH性能齿轮修形
Keywords
Electric vehicle reducerCommon torque speedTransmission errorNVH performanceGear modification
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Accurate Modification Method of Gears Based on Spatial Lattice
Research on Performance Degradation Prediction Method of Electric Vehicle Reducers Based on MDS-GA-SVR
Research on Gear Modification and Simulation of Hybrid Transmission
Research on Vibration Characteristics of Two-Speed Automatic Transmission Housing for Pure Electric Vehicles
Research on Correcting Eccentric Load of the Internal Gear Tooth Surface by Orthogonal Tests Based on Neural Network Optimization
Related Author
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Related Institution
Precision Manufacturing Institute, Wuhan University of Science and Technology
Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology
Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education, Wuhan University of Science and Technology
Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation, Zhejiang Fangyuan Test Group Co., Ltd.
National and Local Joint Engineering Research Center of Reliability Analysis and Testing for Mechanical and Electrical Products,Zhejiang Sci-Tech University