Construction Method for Reliability Test Driving Cycle of Electric Vehicle Drive System Based on Users' Big Data

doi:10.3901/JME.2021.14.129

Abstract

Abstract: To construct the reliability test driving cycle of the electric vehicle drive system correlated with users' load, based on 300 actual users load data with 3.54 million kilometers, fragment of conditions are extracted and characteristic parameters are constructed with the failure dominant load of the electric drive system. Using principal component analysis and K-Means clustering analysis methods, the operating segments of the electric drive system under user conditions are divided into five typical conditions. Based on the damage accumulation model, the damage caused to the components of the electric drive system under different conditions are analyzed, and the optimal unit damage intensity distribution models are determined for each condition. Based on the continuity turning point of the damage distribution, the segments with higher unit damage strength are selected as reliability test driving cycle. Based on Markov state transition probability matrix, using Markov chain Monte Carlo method to generate pseudo-random numbers for stitching of conditions, then the reliability test load spectrum of the electric vehicle drive system is constructed. The comparison of the constructed reliability test load spectrum with the standard cyclic conditions and customers damage shows that the reliability test loading spectrum of the electric drive system is constructed with higher damage strength, which can effectively cover more than 90% of the strength under user conditions, so as to provide reference and basis for the reliability design and verification of electric vehicle drive or transmission system.

Key words: users' big data, electric vehicle drive system, reliability test, construction of conditions, Markov process

CLC Number:

U461

ZHAO Lihui, WANG Zhen, FENG Jinzhi, ZHENG Songlin, NING Xin. Construction Method for Reliability Test Driving Cycle of Electric Vehicle Drive System Based on Users' Big Data[J]. Journal of Mechanical Engineering, 2021, 57(14): 129-140.

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