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.
Highlights
Hybrid and electric vehicles (EVs) represent a means of transport with low CO2 emissions
The MATLAB simulation results of all three tests for Urban Dynamometer Driving Schedule (UDDS), UDDS-Environmental Protection Agency (EPA) and FTP driving cycles, for same initial conditions show an excellent accuracy for adopted battery model versus ADVISOR Rint and an estimation error less than 2%, confirmed by the results from Table 3, Tables A1 and A2 from Appendix A
Since from three different sources, the simulation results converge to an average error of less than 2% and show an accurate estimate value, we can conclude that these results validate the Li-ion Co battery
Summary
Hybrid and electric vehicles (EVs) represent a means of transport with low CO2 emissions. It is already becoming a reality that, “among the batteries with low memory effects”, the Li-ion outperforms the most popular nickel-based technologies. They excel by “lighter weight, high density of energy, long life and low self-discharge rate” [1]. HEVs/EVs continue to be powered for a long time by both nickel-metal hydride (Ni-MH) batteries and lithium-ion [1,2,3,4,5,6,7,8,9,10,11,12]. The power of the battery “decreases drastically in cold weather”, and “when operating at high temperatures, its performance and life cycle visibly deteriorate” [10].
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