Cita:
H. Miniguano, A. Barrado, A. Lázaro, P. Zumel and C. Fernández, "General Parameter Identification Procedure and Comparative Study of Li-Ion Battery Models," in IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 235-245, Jan. 2020
Patrocinador:
Ministerio de Economía y Competitividad (España)
Agradecimientos:
This work was supported by the Ministry of Economy and Competitiveness and FEDER funds through the research project “Storage and Energy Management for Hybrid Electric Vehicles based on Fuel Cell, Battery, and Supercapacitors”—ELECTRICAR-AG-(DPI2014- 53685-C2-1-R).
Proyecto:
Gobierno de España. DPI2014-53685-C2-1-R
Accurate and robust battery models are required for the proper design and operation of battery-powered systems. However, the parametric identification of these models requires extensive and sophisticated methods to achieve enough accuracy. This article shows aAccurate and robust battery models are required for the proper design and operation of battery-powered systems. However, the parametric identification of these models requires extensive and sophisticated methods to achieve enough accuracy. This article shows a general and straightforward procedure, based on Simulink and Simscape of Matlab, to build and parameterize Li-ion battery models. The model parameters are identified with the Optimization Toolbox of Matlab, by means of an iterative process to minimize the sum of the squared errors. In addition, this procedure is applied to a selection of five different models available in the literature for electric vehicle applications, obtaining a comparative study between them. Also, the performance of each battery model is evaluated through two current profiles from two driven profiles known as the Urban Driving Cycle (ECE-15 or UDC) and the Hybrid Pulse Power Characterization (HPPC). The experimental results obtained from a Li-ion polymer battery have been compared with the data provided by the models, confirming the effectiveness of the proposed procedure, and also, the application field of each model as a function of the required accuracy.[+][-]