人工智能在动力电池健康状态预估中的研究综述
摘要： 目前先进的电动汽车开发和应用已成为实现“脱碳”的关键技术。准确的电池健康状态(State of health,SOH)预估可有效地表征动力电池性能,对电动汽车动力电池维护和寿命管理具有重要意义。近年来,以深度学习、强化学习和大数据技术等为代表的新一代人工智能技术在电动汽车电池状态预估的应用已成为研究热点。首先简要介绍人工智能技术、SOH的含义以及影响SOH主要因素,然后分别从电池单体与电池系统的角度对几种人工智能模型在SOH预估中的研究进行总结与讨论,最后结合大数据、云计算、区域链等新兴技术,对电池健康状态预估问题进行展望,为提升当前动力电池全生命周期管理能力提供一些思路。
关键词: 人工智能, 健康状态, 电池系统, 现状与趋势
Abstract: The development and application of advanced electric vehicles has become the key technology to achieve “decarbonization”. Accurate state of health(SOH) prediction of battery can effectively characterize its operation performance. It is of great significance to the maintenance and life management of battery in electric vehicle. In recent years, a new generation of artificial intelligence technology represented by deep learning, reinforcement learning and big data technology has become a research hotspot in the application of battery state prediction. The basic theory of artificial intelligence technology and SOH and SOH influence factors is briefly introduced. Several main artificial intelligence algorithms in SOH prediction are summarized and discussed from the perspective of battery cell and battery system respectively. Finally, combined with emerging technologies such as big data, cloud computing and regional chain, some battery SOH prediction problems are discussed, which provides some ideas for breaking through the bottleneck of current power battery full life cycle management technology.
Key words: artificial intelligence, state of health, battery system, status and trend
中图分类号:
TM912
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