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Original scientific paper

https://doi.org/10.1080/00051144.2024.2368365

Temperature-dependent hysteresis model for Li-ion batteries

Dávid Bodnár ; Dept. of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Košice, Slovakia *
Daniel Marcin ; Dept. of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Košice, Slovakia
František Ďurovský ; Dept. of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Košice, Slovakia

* Corresponding author.


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Abstract

The increasing importance of accurate battery state estimations in advanced Battery Management Systems (BMS) underscores the need for precise modelling of battery behaviour and
characteristics. While equivalent circuit models are widely utilized for their low computational
demands, they face challenges in maintaining precision and adaptability during dynamic conditions, posing a persistent concern for future advancements. This study focuses specifically on the
battery hysteresis effect, a complicating factor in the modelling and estimation processes. Open
circuit voltage (OCV) measurements and parameter identification for equivalent circuit models were conducted on prevalent Li-ion battery technologies, namely nickel-manganese–cobalt
(NMC) and lithium-iron-phosphate (LFP). The experimental results indicate the hysteresis effect
becomes more significant with lower temperatures. In this paper, a battery model covering the
temperature influence on the hysteresis effect is proposed. The proposed model exhibits an
average root mean square error of less than 13 mV. The model holds promise for application in
modern battery management systems, offering an enhancement to state-of-charge estimation
methodologies.

Keywords

Battery modelling; hysteresis effect; Li-ion; temperature dependence

Hrčak ID:

326282

URI

https://hrcak.srce.hr/326282

Publication date:

25.6.2024.

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