{"title":"Unlocking Interpretable Prediction of Battery Random Discharge Capacity With Domain Adaptative Physics Constraint (Adv. Energy Mater. 13/2025)","authors":"Yunhong Che, Jia Guo, Yusheng Zheng, Daniel-Ioan Stroe, Wenxue Liu, Xiaosong Hu, Remus Teodorescu","doi":"10.1002/aenm.202570068","DOIUrl":null,"url":null,"abstract":"<p><b>Battery Management</b></p><p>Interpretable and accurate random discharge capacity predictions under varying application scenarios enable better onboard battery management to ensure safe and optimal operations. In article number 2405506, Jia Guo, Yusheng Zheng, Xiaosong Hu, and co-workers developed an electrochemical impedance spectroscopy-constrained domain adaptation framework to predict the capacities during random discharge with non-destructive mechanism diagnosis for onboard dynamic aging understanding.\n\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":111,"journal":{"name":"Advanced Energy Materials","volume":"15 13","pages":""},"PeriodicalIF":24.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202570068","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Energy Materials","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aenm.202570068","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Battery Management
Interpretable and accurate random discharge capacity predictions under varying application scenarios enable better onboard battery management to ensure safe and optimal operations. In article number 2405506, Jia Guo, Yusheng Zheng, Xiaosong Hu, and co-workers developed an electrochemical impedance spectroscopy-constrained domain adaptation framework to predict the capacities during random discharge with non-destructive mechanism diagnosis for onboard dynamic aging understanding.
期刊介绍:
Established in 2011, Advanced Energy Materials is an international, interdisciplinary, English-language journal that focuses on materials used in energy harvesting, conversion, and storage. It is regarded as a top-quality journal alongside Advanced Materials, Advanced Functional Materials, and Small.
With a 2022 Impact Factor of 27.8, Advanced Energy Materials is considered a prime source for the best energy-related research. The journal covers a wide range of topics in energy-related research, including organic and inorganic photovoltaics, batteries and supercapacitors, fuel cells, hydrogen generation and storage, thermoelectrics, water splitting and photocatalysis, solar fuels and thermosolar power, magnetocalorics, and piezoelectronics.
The readership of Advanced Energy Materials includes materials scientists, chemists, physicists, and engineers in both academia and industry. The journal is indexed in various databases and collections, such as Advanced Technologies & Aerospace Database, FIZ Karlsruhe, INSPEC (IET), Science Citation Index Expanded, Technology Collection, and Web of Science, among others.