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NARX neural network optimized by polynomial chaos and forward orthogonal least squares for lithium-ion battery SOC estimation

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Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
Accurate estimation of the State of Charge (SOC) of lithium-ion batteries is crucial for optimizing battery performance, extending service life, and ensuring safe operation. In neural network-based SOC estimation, dynamic neural networks are indispensable,...