Battery monitoring and prognostics optimization techniques: Challenges and opportunities

被引:58
作者
Semeraro, Concetta [1 ]
Caggiano, Mariateresa [2 ,3 ]
Olabi, Abdul-Ghani [4 ]
Dassisti, Michele [2 ]
机构
[1] Univ Sharjah, Dept Ind & Management Engn, Sharjah, U Arab Emirates
[2] Polytech Univ Bari, Dept Mech Math & Management DMMM, Bari, Italy
[3] Scuola Univ Super IUSS Pavia, Dept Sci Technol & Soc, Pavia, Italy
[4] Univ Sharjah, Dept Sustainable & Renewable Energy Engn, Sharjah, U Arab Emirates
关键词
Battery; Model-based approaches; Data-driven approaches; Hybrid approaches; Optimization techniques; LITHIUM-ION BATTERY; REMAINING USEFUL LIFE; STATE-OF-HEALTH; SUPPORT VECTOR MACHINE; SIMPLIFIED ELECTROCHEMICAL MODEL; PROCESS FAULT-DETECTION; CHARGE ESTIMATION; NEURAL-NETWORK; ONLINE STATE; DATA-DRIVEN;
D O I
10.1016/j.energy.2022.124538
中图分类号
O414.1 [热力学];
学科分类号
摘要
In recent years, many researchers have been conducted on batteries' health monitoring and prognostics, mainly focusing on the batteries' state of charge (SOC). Accurately estimating the state of health (SOH) and predicting the remaining useful life (RUL) of battery components are very important for the prognosis and health management of the overall battery system. However, due to the non-linear dynamics caused by the electrochemical characteristics in batteries, the accurate estimations of SOC, SOH and RUL prediction are still challenging and many technologies have been developed to solve this challenge. This paper reviews and discusses state of the art in SOC and SOH and RUL estimation techniques for all battery types. A novel framework is developed and presented to compare all battery techniques based on three dimensions: battery performance (Z dimension), approaches (X dimension), and criteria (Y dimension) to fulfil. All studies are reviewed and discussed based on the dimensions and the criteria defined in the framework. Based on this investigation, this study summarizes at the end the key outcomes and suggests future research challenges. (C) 2022 Published by Elsevier Ltd.
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页数:25
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