Pavel M. Roy, Harsh H. Sawant, Pratik P. Shelar, Prashil U. Sarode, S.H. Gawande
{"title":"Battery health management–a perspective of design, optimization, manufacturing, fault detection, and recycling","authors":"Pavel M. Roy, Harsh H. Sawant, Pratik P. Shelar, Prashil U. Sarode, S.H. Gawande","doi":"10.1016/j.enss.2024.04.001","DOIUrl":null,"url":null,"abstract":"<div><p>This paper explores the key aspects of battery technology, focusing on Li-ion, Lead-acid, and Nickel Metal Hydride (NiMH) batteries. It delves into manufacturing processes and highlighting their significance in optimizing battery performance. In addition, the study investigates battery fault detection, emphasizing the importance of early diagnosis using artificial intellignece (AI) and machine learning (ML) methods. This paper also addresses battery recycling techniques, discussing methods such as pyrometallurgy, hydrometallurgy, mechanical separation, and electrodialysis, considering their environmental impact. This comprehensive analysis sheds light on the evolution of battery technology and its role in sustainable energy systems.</p></div>","PeriodicalId":100472,"journal":{"name":"Energy Storage and Saving","volume":"3 3","pages":"Pages 190-208"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772683524000141/pdfft?md5=03e71e4339fce260728e239e87658325&pid=1-s2.0-S2772683524000141-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Storage and Saving","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772683524000141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper explores the key aspects of battery technology, focusing on Li-ion, Lead-acid, and Nickel Metal Hydride (NiMH) batteries. It delves into manufacturing processes and highlighting their significance in optimizing battery performance. In addition, the study investigates battery fault detection, emphasizing the importance of early diagnosis using artificial intellignece (AI) and machine learning (ML) methods. This paper also addresses battery recycling techniques, discussing methods such as pyrometallurgy, hydrometallurgy, mechanical separation, and electrodialysis, considering their environmental impact. This comprehensive analysis sheds light on the evolution of battery technology and its role in sustainable energy systems.