Real Time Design and Implementation of State of Charge Estimators for a Rechargeable Lithium-Ion Cobalt Battery with Applicability in HEVs/EVs—A Comparative Study

Abstract

Estimating the state of charge (SOC) of Li-ion batteries is an essential task of battery management systems for hybrid and electric vehicles. Encouraged by some preliminary results from the control systems field, the goal of this work is to design and implement in a friendly real-time MATLAB simulation environment two Li-ion battery SOC estimators, using as a case study a rechargeable battery of 5.4 Ah cobalt lithium-ion type. The choice of cobalt Li-ion battery model is motivated by its promising potential for future developments in the HEV/EVs applications. The model validation is performed using the software package ADVISOR 3.2, widely spread in the automotive industry. Rigorous performance analysis of both SOC estimators is done in terms of speed convergence, estimation accuracy and robustness, based on the MATLAB simulation results. The particularity of this research work is given by the results of its comprehensive and exciting comparative study that successfully achieves all the goals proposed by the research objectives. In this scientific research study, a practical MATLAB/Simscape battery model is adopted and validated based on the results obtained from three different driving cycles tests and is in accordance with the required specifications. In the new modelling version, it is a simple and accurate model, easy to implement in real-time and offers beneficial support for the design and MATLAB implementation of both SOC estimators. Also, the adaptive extended Kalman filter SOC estimation performance is excellent and comparable to those presented in the state-of-the-art SOC estimation methods analysis.

SOC Estimation of a Rechargeable Li-Ion Battery Used in Fuel Cell Hybrid Electric Vehicles—Comparative Study of Accuracy and Robustness Performance Based on Statistical Criteria. Part II: SOC Estimators

“…In recent years, the lithium-ion battery has proven to be an ideal safety battery for hybrid electric vehicles, with high discharge power, environmental protection, low pollution, and long life [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Some details about its features, modelling, and hybrid combinations with different power sources in a fuel cell electric vehicle (FCEV) and power distribution controlled and optimized by an energy management system (EMS) are shown in Part 1 [20].…”

“…The Li-ion battery as a direct energy supply and its SOC have a significant impact on the HEV's performance. Besides, the amount of SOC is crucial for safe operation of the Li-ion battery and its prolongation of life, so an accurate estimate of the SOC has an important theoretical significance and application value [1,2,5,6]. Typically, for calculation based on the coulomb counting method, the SOC is "tracking according to the discharging current" [5,6,12].…”

“…Besides, the amount of SOC is crucial for safe operation of the Li-ion battery and its prolongation of life, so an accurate estimate of the SOC has an important theoretical significance and application value [1,2,5,6]. Typically, for calculation based on the coulomb counting method, the SOC is "tracking according to the discharging current" [5,6,12]. In the absence of a measurement sensor, the SOC cannot be measured directly; thus, its estimation using a Kalman filter technique is required [5].…”

“…Typically, for calculation based on the coulomb counting method, the SOC is "tracking according to the discharging current" [5,6,12]. In the absence of a measurement sensor, the SOC cannot be measured directly; thus, its estimation using a Kalman filter technique is required [5].…”

“…Typically, the Kalman filter SOC estimators are model based, so both battery models-the linear RC equivalent electrical circuit (ECM) and the nonlinear Simscape generic model developed and analyzed in Part 1 [20] are beneficial for designing and implementing a high accuracy SOC estimator [1][2][3][4][5][6][7][8][9][10][12][13][14][15][16][17][18][19]. For better documentation and information for the reader, the diagrams of both models represented in Part 1 [20] are taken over and repeated in Appendix A.1, Figure A1a-c.…”