A nonlinear fractional-order dynamical framework for state of charge estimation of LiFePO4 batteries in electric vehicles

Borah, Manashita and Moura, Scott and Kato, Dylan and Lee, Jaewoong (2023) A nonlinear fractional-order dynamical framework for state of charge estimation of LiFePO4 batteries in electric vehicles. IFAC-PapersOnLine, 56 (3). pp. 343-348.

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Abstract

An efficient state of charge (SOC) estimation for LiFePO4 batteries in electric vehicles (EVs) has been an open problem so far, largely due to its non-measurable nature. This paper tackles this problem by presenting a fractional-order (FO) dynamical framework to unravel and understand the inherent dynamics of the LiFePO4 battery which leads to an improved estimation of SOC. First, a FO model (FOM) is proposed where the parameters are introduced as nonlinear functionalities of SOC. It has been observed that the FO defined as a nonlinear function of SOC is crucial in identifying its progression during the weakly measurable flat, open circuit curve of the battery; a property the integer order models (IOMs) fail to capture. Second, a fractional order estimator (FOE) is designed incorporating the SOC based nonlinearities of the model parameters. The FO derivative being a memory-based operator improves estimation as it can store historical information of the speed profiles of the EV. The proposed framework of nonlinear FOM and FOE design is validated through both simulation and experimental results. Precise estimation of the battery parameters using the proposed framework can be applied to protect the battery management system, mitigate overcharge or discharge, prevent hazardous accidents, and enhance battery life, eventually leading to an energy-efficient mode of green transportation.

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