Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 172, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2021.114647
Keywords
Li-ion battery-pack; Equivalent electric circuit; Genetic algorithm; Electric vehicle applications; HIL simulation
Categories
Funding
- Solar Energy Research Center SERC-Chile [CONICYT/FONDAP 15110019]
- ING2030 CORFO - Chilean government [16ENI2-71940]
Ask authors/readers for more resources
This article presents an optimization procedure based on genetics algorithms (GA) to obtain an equivalent electric circuit model (EECM) of a Li-ion battery pack, successfully identifying and validating the parameters of the EECM. Experimental results demonstrate that the GA-based approach allows accurate representation of the highly dynamic behavior of the Li-ion battery with high precision.
This article presents the optimization procedure based on genetics algorithms (GA) to obtain an equivalent electric circuit model (EECM) of a Li-ion battery pack. In the first part, a series of experimental tests in time and frequency domains were carried out. These tests were used to identify the parameters of the EECM under different State-of-Charge (SoC) for a commercial battery-pack. Each EECM consists of a voltage source connected in series with a resistor and a set of k networks composed of a resistor in parallel with a capacitor, where k = 1, 2 o 3 (1RC, 2RC, and 3RC). Subsequently, parametric identification of the EECM was performed using optimization techniques. At this stage, the topology that gives the lowest estimation error was determined, where the options analyzed were to use 1RC, 2RC, or 3RC networks. The objective function consists of minimizing the mean square error between measured and calculated impedances of the different proposed circuit models. GA was used to solve this optimization problem. The minimum error obtained was 1.07% and 1.05% for the EECM with 2RC and 3RC networks, respectively. Finally, these EECMs were implemented in Matlab?/Simulink to validate the Li-ion battery-pack model response for an electric vehicle application. A hardware-in-the-loop (HIL) simulation platform was developed to simulate the performance of an electric vehicle (EV) under different driving cycles. The results show that the GA-based approach allows obtained an EECM of low order to represent the highly dynamic behavior of a Li-ion battery with high accuracy.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available