Abstract
The state of health (SOH) is an important indicator of lithium-ion batteries in electric vehicles (EVs), and therefore accurate SOH estimation plays a fundamental role in ensuring the reliable operation and safety of EVs. Currently, a variety of methods have been developed for online/offline battery SOH estimation, while most of them present high complexity due to complex tests, modelling, and algorithm implementation. Develo** a rapid and accurate SOH estimation approach based on the simple test is a research hotspot to reduce the estimation cost. This paper summarizes and reclassifies the existing estimation methods considering the estimation complexity in practical applications. First, the rapid estimation methods are categorized into electrical parameters-based estimation and material properties-based estimation. Second, the working principles and performance of the rapid estimation methods are introduced combined with the review and experimental studies. Finally, this paper compares them in view of advantages and disadvantages and suggests the future trend for further improvement when used in practice. It is believed that this investigation can provide valuable guidance for academic research and engineering applications.
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Wang, Z. et al. (2024). Investigation into Rapid State of Health Estimation of Lithium-Ion Batteries in Electric Vehicles. In: Ball, A.D., Ouyang, H., Sinha, J.K., Wang, Z. (eds) Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023). TEPEN IncoME-V DAMAS 2023 2023 2023. Mechanisms and Machine Science, vol 151. Springer, Cham. https://doi.org/10.1007/978-3-031-49413-0_82
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