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An Adaptive Autotuned Polynomial-Based Extended Kalman Filter for Sensorless Surface Temperature Estimation of Li-Ion Battery Cells

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This paper proposes an adaptive filter for estimating the surface temperature of lithium-ion battery cells in real time. The proposed temperature sensorless method aims to achieve a highly accurate temperature… Click to show full abstract

This paper proposes an adaptive filter for estimating the surface temperature of lithium-ion battery cells in real time. The proposed temperature sensorless method aims to achieve a highly accurate temperature estimation at a relatively low implementation cost. The method employs a system dynamic and measurement models derived using polynomial curve fitting and implemented in the proposed adaptive autotuned extended Kalman filter (AA-EKF). Derivation of the proposed technique followed by experimental verification are demonstrated.

Keywords: battery cells; surface temperature; temperature estimation; filter; temperature; ion battery

Journal Title: IEEE Access
Year Published: 2022

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