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Automotive Engineering ›› 2025, Vol. 47 ›› Issue (11): 2250-2264.doi: 10.19562/j.chinasae.qcgc.2025.11.018

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Research on the Drive-Brake Load Characteristics of Electric Vehicles Under User Data

Lihui Zhao1,2,3,Shaojie Shen1,Shuo Weng1,2,3,Desheng Chen4,Dongdong Zhang1,2,3()   

  1. 1.School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093
    2.CMIF Key Laboratory for Strength and Reliability Evaluation of Automotive Structures,Shanghai 200093
    3.Public Technology Platform for Reliability Evaluation of New Energy Vehicles in Shanghai,Shanghai 200093
    4.CITIC Dicastal Co. ,Ltd. ,Qinhuangdao 066000
  • Received:2024-12-06 Revised:2025-05-07 Online:2025-11-25 Published:2025-11-28
  • Contact: Dongdong Zhang E-mail:dongdongzhang@usst.edu.cn

Abstract:

The study of drive-brake load characteristics of electric vehicles based on user operation data is an important foundation for the reliability-oriented design of electric drive systems. In this paper, by integrating telematics big data with vehicle longitudinal dynamics modeling, typical driving condition characteristics, user behavior differences, and the gap between user targets and existing standards are systematically investigated. Firstly, a longitudinal dynamics model is developed and validated using over one million kilometers of real-world driving data from seven regions, enabling the transformation of user operation data into drive-brake loads. Secondly, an analysis of operating time, mileage, and acceleration characteristics under different driving conditions is conducted. The results show that frequent speed variations under low to medium speeds are key factors contributing to damage in critical components. Lastly, regional differences in user behavior are compared, and a user target profile suited to Chinese road conditions is constructed. A further comparison with existing standards reveals significant discrepancies in load frequency within the low-to-medium load range. The research results can provide data support and methodological references for the reliability-oriented design and validation standard development of electric drive systems.

Key words: user big data, electric drive system, working condition characteristics, reliability