Lithium-ion battery equivalent model over full-range state of charge based on electrochemical process simplification

A B S T R A C T State estimation is a key issue of battery management system (BMS) to improve the energy utilization of lithium-ion battery in electric vehicle, the performance of which relies on the accuracy of equivalent model over full-range sate of charge (SOC). However, the widely applied equivalent circuit model (ECM) has limitations at low SOC range. In this paper, an optimized equivalent model is proposed combining the lithium-ion battery internal electrochemical processes with the ECM. For one thing, the proposed model is able to offer high accuracy by considering solid-phase diffusion into the update of open circuit voltage (OCV) and describing the polarization at the solid-liquid interface from the electrochemical perspective. For another thing, the proposed approximate method for describing internal electrochemical micro-variables with external electric macro-variables allows the model to avoid a series of partial differential equations. In addition, online parameter identification based on the forgetting factor based recursive least square method (FFRLS) makes the proposed model well-adapted to dynamic working conditions. Compared with the ECM under multiple working conditions, the proposed model is proven to provide a better performance over full-range SOC especially at the low-range area below 20%. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes an optimized equivalent model combining the internal electrochemical processes of lithium-ion battery with ECM, providing higher accuracy over full-range SOC. In addition, online parameter identification based on the FFRLS method makes the model well-adapted to dynamic working conditions.