The Library
Theory of battery ageing in a lithium-ion battery : capacity fade, nonlinear ageing and lifetime prediction
Tools
Tools
Tools
Atalay, Selcuk, Sheikh, Muhammad, Mariani, Alessandro, Merla, Yu, Bower, Ed and Widanage, Widanalage Dhammika (2020) Theory of battery ageing in a lithium-ion battery : capacity fade, nonlinear ageing and lifetime prediction. Journal of Power Sources, 478 . 229026. doi:10.1016/j.jpowsour.2020.229026
|
PDF
WRAP-theory-battery-ageing-lithium-ion-battery-Widanage-2020.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (3371Kb) | Preview |
Official URL: https://doi.org/10.1016/j.jpowsour.2020.229026
Abstract
Forecasting the lifetime of Li-ion batteries is a critical challenge that limits the integration of battery electric vehicles (BEVs) into the automotive market. Cycle-life performance of Li-ion batteries is intrinsically linked to the fundamental understanding of ageing mechanisms. In contrast to most previous studies which utilise empirical trends (low real-time information) or rough simplifications on mathematical models to predict the lifetime of a Li-ion battery, we deployed a novel ageing formulation that includes heterogeneous dual-layer solid electrolyte interphase (SEI) and lithium-plating ageing mechanisms with porosity evaluation. The proposed model is parameterized and optimized for mass transport and ageing parameters based on fresh and an aged cell and validated against our experimental results. We show that our advanced ageing mechanisms can accurately calculate experimentally observed cell voltage and capacity fade with respect to cycling number and can predict future fade for new operating scenarios based on constant-current and a dynamic power profile cycling experimental data consisting of high discharge C-rates and fast-charging periods. Our model is able to capture the linear and nonlinear (knee-point) capacity fade characteristics with a high accuracy of 98% goodness-of-fit-error and we compared our model performance with well-accepted existing model in literature.
| Item Type: | Journal Article | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | |||||||||
| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | |||||||||
| Library of Congress Subject Headings (LCSH): | Lithium ion batteries -- Mathematical models, Electrochemistry | |||||||||
| Journal or Publication Title: | Journal of Power Sources | |||||||||
| Publisher: | Elsevier S.A. | |||||||||
| ISSN: | 0378-7753 | |||||||||
| Official Date: | 1 December 2020 | |||||||||
| Dates: |
|
|||||||||
| Date of first compliant deposit: | 22 October 2020 | |||||||||
| Volume: | 478 | |||||||||
| Article Number: | 229026 | |||||||||
| DOI: | 10.1016/j.jpowsour.2020.229026 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access | |||||||||
| RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
