Evaluating the Role of Entropy Change in Lithium-Ion Battery Electro-Thermal Modelling

• Published in: Batteries (Basel) Vol. 11; no. 3; p. 84
• Main Authors: LeBel, Félix-Antoine, Messier, Pascal, Blanchard, Mathieu, Trovão, João Pedro F.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 20.02.2025
• Subjects: Accuracy; Aging; Batteries; Design and construction; Electric cells; electric equivalent circuit; Electric vehicles; electro-thermal model; Electrodes; entropic coefficient; Entropy; Entropy (Physics); Estimation theory; Heat; Heat generation; Lithium; Lithium cells; Lithium-ion batteries; lithium-ion battery; Modelling; Partial differential equations; Physics; Research methodology; Simulation; Thermal analysis; Thermal management; Thermal properties; Canada; United States > US
• ISSN: 2313-0105; 2313-0105
• DOI: 10.3390/batteries11030084

The accurate estimation of lithium-ion cell internal temperature is crucial for the safe operation of battery packs, especially during high discharge rates, as operating outside the safe temperature range can lead to accelerated degradation or catastrophic failures. Heat generation in lithium-ion cells arises primarily from ohmic losses and entropy change (ΔS), yet the latter remains frequently overlooked in battery modelling. However, the impact of considering or discarding ΔS from electro-thermal modelling remains subject to debate. This research highlights the critical role of ΔS in improving the accuracy of electro-thermal models for lithium-ion batteries, particularly in high-fidelity thermal simulations. It presents a systematic integration, ΔS, into electro-thermal models, leveraging the energetic macroscopic representation (EMR) approach to enhance predictive accuracy, a methodology not previously structured in this manner. This paper addresses this issue by performing a comparative analysis of an electro-thermal model (ETM) with and without ΔS. The findings provide clear insights into the role of entropy in electro-thermal modelling, demonstrating that while entropy change has a minimal impact on electrical behaviour prediction, it plays a crucial role in accurately capturing temperature dynamics, helping define the conditions under which it must be considered in simulations. While entropy can be neglected for coarse heat generation estimation, its inclusion enhances temperature prediction accuracy by up to 4 °C, making it essential for applications requiring precise thermal management. This study offers a detailed analysis of the conditions under which ΔS becomes critical to model accuracy, providing actionable guidance for battery engineers and researchers.