{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T04:55:28Z","timestamp":1778561728551,"version":"3.51.4"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Veh."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tiv.2023.3315548","type":"journal-article","created":{"date-parts":[[2023,9,14]],"date-time":"2023-09-14T18:01:11Z","timestamp":1694714471000},"page":"2276-2289","source":"Crossref","is-referenced-by-count":143,"title":["Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9384-3845","authenticated-orcid":false,"given":"Pengfei","family":"Wen","sequence":"first","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5731-3911","authenticated-orcid":false,"given":"Zhi-Sheng","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8290-3910","authenticated-orcid":false,"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6993-2987","authenticated-orcid":false,"given":"Shaowei","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4612-5970","authenticated-orcid":false,"given":"Pu","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Aeronautics and Astronautics, Stanford University, Stanford, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7441-5434","authenticated-orcid":false,"given":"Shuai","family":"Zhao","sequence":"additional","affiliation":[{"name":"AAU Energy, Aalborg University, Aalborg, Denmark"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Global EV outlook 2022: Securing supplies for an electric future","author":"Bibra","year":"2022"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2018.2843126"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2021.3131944"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2014.2299152"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2991454"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.2973551"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2016.04.002"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.03.013"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2018.12.041"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-021-00314-5"},{"issue":"1","key":"ref11","first-page":"71","article-title":"Data-driven approaches for predicting spread of infectious diseases through DINNs: Disease informed neural networks","volume-title":"Lett. Biomath.","volume":"9","author":"Shaier","year":"2022"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPEL.2022.3176468"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPEL.2020.3024914"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3105537"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3089333"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2013.2276473"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2016.07.036"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2018.01.011"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1149\/2.049210jes"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2021.3127035"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2016.2578950"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2019.01.083"},{"key":"ref23","first-page":"3208","article-title":"PDE-Net: Learning PDEs from data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Long","year":"2018"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.108925"},{"key":"ref25","first-page":"932","article-title":"Deep hidden physics models: Deep learning of nonlinear partial differential equations","volume":"19","author":"Raissi","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/9937846"},{"key":"ref27","first-page":"4","article-title":"Deriving the recurrent neural network definition and RNN unrolling using signal processing","volume-title":"Proc. CRACT Workshop Neural Inf. Process. Syst.","volume":"31","author":"Sherstinsky","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.36001\/ijphm.2020.v11i1.2594"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2020.103386"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.05.024"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2018.10.045"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1017\/cbo9780511995569"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2022.109347"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3032642"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.120114"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2016.2622838"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-7753(02)00490-1"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2020.107241"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2020.101342"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1038\/s41560-019-0356-8"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3054429"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2013.2250282"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3055977"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(89)90020-8"},{"key":"ref45","first-page":"1","article-title":"Automatic differentiation in machine learning: A survey","volume":"18","author":"Baydin","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2022.114823"},{"key":"ref47","first-page":"7482","article-title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit","author":"Kendall","year":"2018"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1137\/20M1318043"},{"key":"ref49","article-title":"Multi-objective loss balancing for physics-informed deep learning","author":"Bischof","year":"2021"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2020.3034855"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107195"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2022.104209"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3156965"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2015.08.119"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/s10915-022-01939-z"}],"container-title":["IEEE Transactions on Intelligent Vehicles"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274857\/10443740\/10251604.pdf?arnumber=10251604","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T17:40:16Z","timestamp":1751305216000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10251604\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":55,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tiv.2023.3315548","relation":{},"ISSN":["2379-8904","2379-8858"],"issn-type":[{"value":"2379-8904","type":"electronic"},{"value":"2379-8858","type":"print"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}