A4 Article in conference proceedings

Capacity loss estimation for li-ion batteries based on a semi-empirical model

List of Authors: Rabah Mohammed, Immonen Eero, Shahsavari Sajad, Haghbayan Mohammad-Hashem, Murashko Kirill, Immonen Paula

Conference name: European Conference on Modelling and Simulation

Publisher: European Council for Modelling and Simulation

Publication year: 2021

Journal: Proceedings: European Conference for Modelling and Simulation

Book title *: Proceedings of the 35th ECMS International Conference on Modelling and Simulation ECMS 2021

Journal name in source: Proceedings - European Council for Modelling and Simulation, ECMS

Title of series: Communications of the ECMS

Number in series: 1

Volume number: 35

ISBN: 978-3-937436-72-2

ISSN: 2522-2414

DOI: http://dx.doi.org/10.7148/2021-0235

URL: http://www.scs-europe.net/dlib/2021/ecms2021acceptedpapers/0235_simo_ecms2021_0036.pdf


Understanding battery capacity degradation is instrumental for designing modern electric vehicles. In this paper, a Semi-Empirical Model for predicting the Capacity Loss of Lithium-ion batteries during Cycling and Calendar Aging is developed. In order to redict the Capacity Loss with a high accuracy, battery operation data from different test conditions and different Lithium-ion batteries chemistries were obtained from literature for parameter optimization (fitting). The obtained models were then compared to experimental data for validation. Our results show that the average error between the estimated Capacity Loss and measured Capacity Loss is less than 1.5% during Cycling Aging, and less than 2% during Calendar Aging. An electric mining dumper, with simulated duty cycle data, is considered as an application example.

Last updated on 2021-20-08 at 08:20