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




Rabah Mohammed, Immonen Eero, Shahsavari Sajad, Haghbayan Mohammad-Hashem, Murashko Kirill, Immonen Paula

Khalid Al-Begain, Mauro Iacono, Lelio Campanile, Andrzej Bargiela

European Conference on Modelling and Simulation

PublisherEuropean Council for Modelling and Simulation

2021

Proceedings: European Conference for Modelling and Simulation

Proceedings of the 35th ECMS International Conference on Modelling and Simulation ECMS 2021

Proceedings - European Council for Modelling and Simulation, ECMS

Communications of the ECMS

1

35

235

242

978-3-937436-72-2

2522-2414

DOIhttps://doi.org/10.7148/2021-0235

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

https://research.utu.fi/converis/portal/detail/Publication/66341359



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 2024-26-11 at 22:05