分布式驱动电动汽车驱动电机轴承故障诊断研究综述

Review of Fault Diagnosis of Drive Motor Bearings for Distributed Drive Electric Vehicles

分布式驱动电动汽车具有驱动传动链短、传动高效、结构紧凑等特点,已成为当前汽车行业发展的一大趋势。电动汽车驱动系统作为电动汽车“三电”核心部件之一,其驱动电机是电动汽车唯一动力源,而轴承作为电机的关键易损部件,对电动汽车的安全性起着重要作用。要想切实提高电动汽车的运行安全,需要掌握驱动电机轴承的故障诊断方法。因此,介绍了分布式驱动电动汽车驱动系统的电机常见故障,重点从机器学习方面对滚动轴承故障诊断经典算法和轮毂电机轴承故障诊断算法进行综述,总结了不同方法的优点、局限性和应用现状,并对机器学习在故障诊断领域的未来发展方向进行了展望。

Distributed drive electric vehicles have the characteristics of short drive chain,efficient transmission and compact structure,which has become a major trend in the development of the current automotive industry.As one of the core components of the"three electrics"of electric vehicles,the drive motor of electric vehicles is the only power source of electric vehicles,and as a key vulnerable component of the motor,the bearing plays an important role in the safety of electric vehicles.In order to effectively improve the operation safety of electric vehicles,it is necessary to master the fault diagnosis method of drive motor bearings.Therefore,the common faults of drive motor for distributed drive electric vehicles is introduced,a review is focused on the classic algorithms for rolling bearing fault diagnosis and hub motor bearing fault diagnosis from the perspective of machine learning,the advantages,limitations and application status of different methods are summarized,and the future development direction of machine learning in the field of fault diagnosis is prospected.