Linear and Nonlinear System Modeling

11Parameter Estimation of First-Order RC Model of Lithium-Ion Batteries in Electric Vehicles Using Slime Mould Algorithm

Ramdutt Arya¹, Shatrughan Modi² and Souvik Ganguli³*

¹Centre for Energy & Environment, Malaviya National Institute of Technology, Jaipur, Rajasthan, India

²School of Computing, Indian Institute of Information Technology, Una, Himachal Pradesh, India

³Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

Abstract

Electric vehicles (EVs) are being considered as the promising solution for carbon-free transportation and the future of mobility. Battery electric vehicles (BEV) are the true EVs that completely run from electricity supplied by their batteries (Li-ion). For dynamic simulation of BEV and use of the battery effectively, it is essential to model the battery and estimate its parameters accurately. Generally, estimation of the battery parameters requires complex, time-consuming, and expensive methods. This chapter focuses on a simple equivalent circuit methods (ECM) is used for battery modeling. Estimation of battery parameters is done by comparing the proposed model output to the known catalogue output with the help of a newly formed heuristic optimizer-slime mould algorithm (SMA). Slime mould algorithm is based on the morphological transformations, oscillation, and foraging of slime mould found in nature, and have shown remarkable exploration and exploitation capabilities. The ...