A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer

Yigeng Huangfu,Yuntian Liu,Fei Gao,Dongdong Zhao,Jiani Xu

doi:10.3390/en11051211

Abstract

A novel method for Li-ion battery state of charge (SOC) estimation based on a super-twisting sliding mode observer (STSMO) is proposed in this paper. To design the STSMO, the state equation of a second-order RC equivalent circuit model (SRCECM) is derived to represent the dynamic behaviors of the Li-ion battery, and the model parameters are determined by the pulse current discharge approach. The convergence of the STSMO is proven by Lyapunov stability theory. The experiments under three different discharge profiles are conducted on the Li-ion battery. Through comparisons with a conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF), the superiority of the proposed observer for SOC estimation is validated.

Highlights

Due to tremendous oil consumption and aggravated environmental pollution, electric vehicles (EVs) have exhibited great promise as a new, alternative means of transportation in upcoming decades [1]
The superiority of the super-twisting sliding mode observer (STSMO) is proven by comparing with the well-established algorithm, namely, the adaptive extended Kalman filter (AEKF) proposed in [12]
To further illustrate theprofile advantages of the proposed observer, the state of charge (SOC) estimation results are firstly compared with the conventional sliding mode observer (CSMO) to verify the necessity of high-order sliding mode (HOSM) application

Summary

Introduction

Due to tremendous oil consumption and aggravated environmental pollution, electric vehicles (EVs) have exhibited great promise as a new, alternative means of transportation in upcoming decades [1]. Among various power batteries for EVs, such as lead–acid and nickel–hydrogen batteries, the Li-ion battery demonstrates its great superiority in terms of high capacity and power density, fast charge capability, long service life, no memory effect, and low self-charge [2]. An accurate battery SOC indication is the foundation of other state estimations such as state of power (SOP). It is substantial in maximizing battery energy utilization and in preventing the battery from over-charging/over-discharging. The SOC cannot be directly measured by sensors. It must be estimated by well-developed methods with the aid of measurable signals such as the voltage and current of the battery

Objectives

Methods

Results

Conclusion