Towards Long Lifetime Battery: AI-Based Manufacturing and Management|Kailong Liu;Zhongbao Wei;Chenghui Zhang;Yunlong Shang;Remus Teodorescu;Qing-Long Han|National Engineering Laboratory for Electric Vehicles,School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China - 期刊导航|首站-论文投稿智能助手|论文发表|论文智能投稿|期刊自助发表推荐|杂志社快速发表|查同导刊-域田数据官方网站

典型文献

Towards Long Lifetime Battery: AI-Based Manufacturing and Management

文献摘要：

Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification, smart grid, but also strengthen the battery supply chain. As battery inevitably ages with time, losing its capacity to store charge and deliver it efficiently. This directly affects battery safety and efficiency, making related health management necessary. Recent advancements in automation science and engineering raised interest in AI-based solutions to prolong battery lifetime from both manufacturing and management perspectives. This paper aims at presenting a critical review of the state-of-the-art AI-based manufacturing and management strategies towards long lifetime battery. First, AI-based battery manufacturing and smart battery to benefit battery health are showcased. Then the most adopted AI solutions for battery life diagnostic including state-of-health estimation and ageing prediction are reviewed with a discussion of their advantages and drawbacks. Efforts through designing suitable AI solutions to enhance battery longevity are also presented. Finally, the main challenges involved and potential strategies in this field are suggested. This work will inform insights into the feasible, advanced AI for the health-conscious manufacturing, control and optimization of battery on different technology readiness levels.

文献关键词：

中图分类号：

[1] 自动化技术、计算机技术（TP） / 计算技术、计算机技术（TP3） / 计算机的应用（TP39） / 信息处理(信息加工)（TP391）

[2] 医药、卫生（R） / 药学（R9） / 药理学（R96） / 实验药理学（R965）

[3] 经济（F） / 工业经济（F4） / 中国工业经济（F42）

作者姓名：

Kailong Liu;Zhongbao Wei;Chenghui Zhang;Yunlong Shang;Remus Teodorescu;Qing-Long Han

作者机构：

Warwick Manufacturing Group,University of Warwick,Coventry CV47AL,United Kingdom;National Engineering Laboratory for Electric Vehicles,School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China;School of Control Science and Engineering,Shandong University,Jinan 250061,China;Department of Energy Technology,Aalborg University,Aalborg 9220,Denmark;School of Science,Computing and Engineering Technologies,Swinburne University of Technology,Melbourne,VIC 3122,Australia

文献出处：

自动化学报（英文版）

引用格式：

[1]Kailong Liu;Zhongbao Wei;Chenghui Zhang;Yunlong Shang;Remus Teodorescu;Qing-Long Han-.Towards Long Lifetime Battery: AI-Based Manufacturing and Management)[J].自动化学报（英文版）,2022(07):1139-1165

A类：

B类：

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AB值：

0.639819

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