Shahid Ali Khan , Iftikhar Hussain , Amrit Kumar Thakur , Shi Yu , Kwun Ting Lau , Sihong He , Kejian Dong , Jingtan Chen , LI Xiangrong , Muhammad Ahmad , Jiyun Zhao
{"title":"Advancements in battery thermal management system for fast charging/discharging applications","authors":"Shahid Ali Khan , Iftikhar Hussain , Amrit Kumar Thakur , Shi Yu , Kwun Ting Lau , Sihong He , Kejian Dong , Jingtan Chen , LI Xiangrong , Muhammad Ahmad , Jiyun Zhao","doi":"10.1016/j.ensm.2023.103144","DOIUrl":null,"url":null,"abstract":"<div><p>Battery energy storage systems<span> (BESS) are essential for integrating renewable energy sources<span> and enhancing grid stability and reliability. However, fast charging/discharging of BESS pose significant challenges to the performance, thermal issues, and lifespan. This paper provides not only an overview of the recent advancements of battery thermal management systems (BTMS) for fast charging/discharging of BESS but also machine learning (ML) approach to optimizing its design and operation. Various thermal management strategies are highlighted in this review, such as liquid-based, phase-change material-based, refrigerant-based, and ML-based methods, offering improved thermal performance and better safety for fast charge/discharge applications. Overall, this paper provides a comprehensive and critical analysis of the current advancements and prospects of BESS thermal management and identifies the current research gaps and future directions for developing a more efficient and reliable BESS.</span></span></p></div>","PeriodicalId":18,"journal":{"name":"ACS Macro Letters","volume":null,"pages":null},"PeriodicalIF":5.1000,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Macro Letters","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405829723005214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"POLYMER SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Battery energy storage systems (BESS) are essential for integrating renewable energy sources and enhancing grid stability and reliability. However, fast charging/discharging of BESS pose significant challenges to the performance, thermal issues, and lifespan. This paper provides not only an overview of the recent advancements of battery thermal management systems (BTMS) for fast charging/discharging of BESS but also machine learning (ML) approach to optimizing its design and operation. Various thermal management strategies are highlighted in this review, such as liquid-based, phase-change material-based, refrigerant-based, and ML-based methods, offering improved thermal performance and better safety for fast charge/discharge applications. Overall, this paper provides a comprehensive and critical analysis of the current advancements and prospects of BESS thermal management and identifies the current research gaps and future directions for developing a more efficient and reliable BESS.
期刊介绍:
ACS Macro Letters publishes research in all areas of contemporary soft matter science in which macromolecules play a key role, including nanotechnology, self-assembly, supramolecular chemistry, biomaterials, energy generation and storage, and renewable/sustainable materials. Submissions to ACS Macro Letters should justify clearly the rapid disclosure of the key elements of the study. The scope of the journal includes high-impact research of broad interest in all areas of polymer science and engineering, including cross-disciplinary research that interfaces with polymer science.
With the launch of ACS Macro Letters, all Communications that were formerly published in Macromolecules and Biomacromolecules will be published as Letters in ACS Macro Letters.