Overview of Artificial Intelligence in Health Prediction of Power Battery

doi:10.3901/JME.2024.04.391

Abstract

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

CLC Number:

TM912

DAI Guohong, ZHANG Daohan, PENG Simin, MIAO Yifan, ZHUO Yue, YANG Ruixin, YU Quanqing. Overview of Artificial Intelligence in Health Prediction of Power Battery[J]. Journal of Mechanical Engineering, 2024, 60(4): 391-408.

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