摘要： 目前先進(jìn)的電動汽車開發(fā)和應(yīng)用已成為實現(xiàn)“脫碳”的關(guān)鍵技術(shù)。準(zhǔn)確的電池健康狀態(tài)(State of health,SOH)預(yù)估可有效地表征動力電池性能,對電動汽車動力電池維護(hù)和壽命管理具有重要意義。近年來,以深度學(xué)習(xí)、強化學(xué)習(xí)和大數(shù)據(jù)技術(shù)等為代表的新一代人工智能技術(shù)在電動汽車電池狀態(tài)預(yù)估的應(yīng)用已成為研究熱點。首先簡要介紹人工智能技術(shù)、SOH的含義以及影響SOH主要因素,然后分別從電池單體與電池系統(tǒng)的角度對幾種人工智能模型在SOH預(yù)估中的研究進(jìn)行總結(jié)與討論,最后結(jié)合大數(shù)據(jù)、云計算、區(qū)域鏈等新興技術(shù),對電池健康狀態(tài)預(yù)估問題進(jìn)行展望,為提升當(dāng)前動力電池全生命周期管理能力提供一些思路。

關(guān)鍵詞: 人工智能, 健康狀態(tài), 電池系統(tǒng), 現(xiàn)狀與趨勢

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

中圖分類號: 

TM912

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