Artificial Intelligence Technique-Based EV Powertrain Condition Monitoring and Fault Diagnosis: A Review
Artificial Intelligence Technique-Based EV Powertrain Condition Monitoring and Fault Diagnosis: A Review
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DOI：
10.1109/jsen.2023.3285531
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发表时间：
2023-08
影响因子：
4.3
通讯作者：
Xiaotian Zhang;Yihua Hu;Chao Gong;Jiamei Deng;Gaolin Wang
中科院分区：
文献类型：
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作者：
Xiaotian Zhang;Yihua Hu;Chao Gong;Jiamei Deng;Gaolin Wang
电动汽车的动力传动系统由电机、传动装置、逆变器、电池组等组成，是一个高度集成的系统。它的可靠性和安全性不仅关系到工业成本，更重要的是关系到人类的生命安全。该综述有助于全面总结基于人工智能（AI）/AI支持的电动汽车动力总成状态监测和故障诊断方法，可用于电动汽车应用。AI在PE上的应用是一种新的尝试，可以解决许多问题，性能优于传统方法，甚至可以实现传统方法无法实现的功能。本文通过案例总结、分类、比较和传统方法与基于AI的方法之间的定量分析，全面讨论了与AI支持的方法相关的动机、优势、局限性和挑战。此外，审查最后提出了这一领域的前瞻性未来趋势。
Electric powertrain used in electric vehicles (EVs), which is constituted of a motor, transmission unit, inverter, battery packs, and so on, is a highly integrated system. Its reliability and safety are not only related to industrial costs but more importantly to the safety of human life. This review contributes to comprehensively summarizing artificial intelligence (AI)-based/AI-supported approaches in EV powertrain condition monitoring and fault diagnosis that can be used in EV applications. The application of AI on PE in EV is a new attempt, which can solve many issues with better performance than traditional methods and even achieve functions that the conventional methods cannot achieve. This article thoroughly discusses the motivation, advantages, limitations, and challenges associated with AI-supported methods through case summaries, classification, comparisons, and quantitative analyses between conventional and AI-based approaches. Furthermore, the review concludes by proposing forward-looking future trends in this field.