@article{He:2023:10.1039/d2ra06004c,
author = {He, R and Xie, W and Wu, B and Brandon, NP and Liu, X and Li, X and Yang, S},
doi = {10.1039/d2ra06004c},
journal = {RSC Advances: an international journal to further the chemical sciences},
pages = {2036--2056},
title = {Towards interactional management for power batteries of electric vehicles},
url = {http://dx.doi.org/10.1039/d2ra06004c},
volume = {13},
year = {2023}
}

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TY  - JOUR
AB  - With the ever-growing digitalization and mobility of electric transportation, lithium-ion batteries are facing performance and safety issues with the appearance of new materials and the advance of manufacturing techniques. This paper presents a systematic review of burgeoning multi-scale modelling and design for battery efficiency and safety management. The rise of cloud computing provides a tactical solution on how to efficiently achieve the interactional management and control of power batteries based on the battery system and traffic big data. The potential of selecting adaptive strategies in emerging digital management is covered systematically from principles and modelling, to machine learning. Specifically, multi-scale optimization is expounded in terms of materials, structures, manufacturing and grouping. The progress on modelling, state estimation and management methods is summarized and discussed in detail. Moreover, this review demonstrates the innovative progress of machine learning based data analysis in battery research so far, laying the foundation for future cloud and digital battery management to develop reliable onboard applications.
AU  - He,R
AU  - Xie,W
AU  - Wu,B
AU  - Brandon,NP
AU  - Liu,X
AU  - Li,X
AU  - Yang,S
DO  - 10.1039/d2ra06004c
EP  - 2056
PY  - 2023///
SN  - 2046-2069
SP  - 2036
TI  - Towards interactional management for power batteries of electric vehicles
T2  - RSC Advances: an international journal to further the chemical sciences
UR  - http://dx.doi.org/10.1039/d2ra06004c
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000910080700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
UR  - https://pubs.rsc.org/en/content/articlelanding/2023/RA/D2RA06004C
UR  - http://hdl.handle.net/10044/1/102689
VL  - 13
ER  - 

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