Titlebar

Export bibliographic data
Literature by the same author
plus on the publication server
plus at Google Scholar

 

Review—Dynamic Models of Li-Ion Batteries for Diagnosis and Operation : A Review and Perspective

Title data

Krewer, Ulrike ; Röder, Fridolin ; Harinath, Eranda ; Braatz, Richard D. ; Bedürftig, Benjamin ; Findeisen, Rolf:
Review—Dynamic Models of Li-Ion Batteries for Diagnosis and Operation : A Review and Perspective.
In: Journal of The Electrochemical Society. Vol. 165 (2018) Issue 16 . - S. A3656-A3673.
ISSN 1945-7111
DOI: https://doi.org/10.1149/2.1061814jes

Abstract in another language

This article discusses the options and challenges of dynamic models for the diagnosis and operation of Li-ion batteries. It provides a concise yet understandable overview on models and dynamics, and it discusses future developments needed to progress the field. The diagnosis and operation of batteries require an understanding of the main processes and their dynamics, parameters, and time constants. Processes with large time constants, such as thermal transport are equally important for safe high-performance operation as are processes with shorter time constants such as diffusion. Depending on the specific problem or operating condition, taking all of the scales into account is often unavoidable. Three separate, yet closely connected model classes are reviewed in terms of physical insight and their capabilities and limits: mechanistic models, equivalent circuit models, and data-driven models. We provide guidance for the selection of a suitable model for the particular diagnosis and operation problem of interest. The optimization of battery diagnosis and operation require versatile and simple models that span multiple time scales and allow physical insight and ease of parameterization. Fusing the existing modeling approaches may help to fully exploit their potential while integrating first-principles physical insight and measurement data.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Engineering Science
Faculties
Faculties > Faculty of Engineering Science > Junior Professor Methods of Monitoring and Managing Batteries > Junior Professor Methods of Monitoring and Managing Batteries - Juniorprof. Dr.-Ing. Fridolin Röder
Result of work at the UBT: No
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 20 Nov 2020 07:53
Last Modified: 27 Nov 2020 07:34
URI: https://eref.uni-bayreuth.de/id/eprint/59657