Abstract
Performance and safety of lithium-ion batteries depend on the ability to efficiently estimate their temperature during charge/discharge operations. We propose a novel algorithm to infer temperature in cylindrical lithium-ion battery cells from measurements of current and terminal voltage. Our approach employs a dual ensemble Kalman filter, which incorporates the enhanced single-particle dynamics to relate terminal voltage to battery temperature and Li-ion concentration. The numerical results and experimental validation from LGChem LiNiMnCoO2 battery (INR21700 M50) cell data demonstrate the method’s ability to estimate temperature at various charge/discharge C-rates.
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