High Fidelity Equivalent Circuit Model Parameter Extraction for Characterization and Simulation of Li-Ion Cells in Battery Electric Vehicles

Abstract

The battery management system (BMS) of battery electric vehicles (BEVs) requires highly fidelity equivalent circuit model of battery to replicate its behavior in real-time applications. The estimation of parameters of battery model is a nonlinear, high-dimensional, and complex problem. In this paper, the determination of battery parameters is expressed as an optimization problem with an objective function defined as minimization of the Manhattan distance between catalog voltage and estimated voltage curve. The dependency of model parameters on C-rate and State of Charge (SOC) has also been accounted. Six different heuristic optimization approaches are implemented for minimizing the objective function, and their performances have been compared statistically using parametric and nonparametric tests and based on their convergence characteristics. The proposed method is tested on Energy Innovation Group (EIG) battery with nominal voltage 2.5 V and capacity 8 Ah. The battery parameters are also obtained using the pulse current charge–discharge test and used as a benchmark to compare the results of the proposed method.

Keywords:

• battery management system
• parameter estimation
• Heuristics approach
• C-rate
• State of Charge

Additional information

Notes on contributors

Venu Sangwan

Venu Sangwan is currently pursuing Ph.D. in the Electrical Engineering Department at Malaviya National Institute of Technology, Jaipur, India. She received Bachelor’s degree in Electrical Engineering from CDLU, Sirsa in 2011 and M.E. in Electrical Engineering from PEC University of Technology, Chandigarh in 2014. Her research interests include battery and power management system, electrical vehicles, machine learning, and power electronics. She has published 12 papers in reputed international conference and 2 journals.

Avinash Sharma

Avinash Sharma received the B.Tech. degree from Malaviya National Institute of Technology Jaipur in 2016 and the Master’s degree in Electrical and Computer Engineering from Concordia University in 2018. Currently, he is working as an Imaging Scientist at Algolux in Canada. His primary research interests include computer vision, machine learning, reinforcement learning, and control system and their application in autonomous driving and robotics.

Rajesh Kumar

Dr. Rajesh Kumar is a Professor in Department of Electrical Engineering, Malaviya National Institute of Technology (MNIT), Jaipur. He received his M.E. degree from MNIT and Ph.D. degree in intelligent systems from University of Rajasthan, India in 2005. He was Post Doctorate Research Fellow in the Department of Electrical and Computer Engineering at the National University of Singapore (NUS), Singapore, from 2009 to 2011. He has more than 400 publications related to these areas in various international journals and conference proceedings. He has delivered more than 90 talks, 11 patents, 1 technology transfer, and currently 2 research projects. His field of interest includes computational intelligence, bio-inspired algorithms, system prediction models, smart power networks, medical assistive systems, and data analysis.

Akshay K. Rathore

Dr. Akshay Kumar Rathore is an Associate Professor at Concordia University, Montreal, Canada. From November 2010 to February 2016, he was an Assistant Professor in the Department of Electrical and Computer Engineering, National University of Singapore. He received his M.Tech. degree in Electrical Machines and Drives from Indian Institute of Technology, BHU, Varanasi, India in 2003 and was awarded Gold Medal for securing highest standing among all electrical engineering specializations. He received his PhD in Power Electronics from University of Victoria, BC, Canada in 2008. He had two subsequent postdoctoral appointments with University of Wuppertal, Germany, and University of Illinois at Chicago, USA. His field of interest includes analysis, design, and development of high-density soft-switching power electronics systems, in particular, current-fed topologies for renewables, distributed generation, microgrid, and electric transportation applications. He has published more than 200 research papers in international journals and conferences including 72 IEEE Transactions. His research is mainly focused on current-fed converters and multilevel inverters.