Simulation and electrification of a conventional vehicle into a battery electric vehicle for sustainability mobility

ABSTRACT

This work explores converting a conventional 1996 Honda Civic Coupe into a battery-electric vehicle (BEV). A simulation model is developed to analyze the vehicle’s dynamic behavior under various conditions, including changes in vehicle mass and road slope. The system specifications are detailed based on a 50 kW AC induction motor, controller, battery, and battery management system. The battery comprises 2,376 NCR18650B cells with a capacity of 23 kWh based on inverter requirements. Energy consumption is simulated using the New European Driving Cycle (NEDC), resulting in 1.69 kWh to travel 10.8 km. Autonomy is estimated at 147 km. The environmental impact of 19.2 g CO₂/km is calculated. The results illustrate the change in maximum speed, acceleration, and distance traveled based on changes in mass and slope. It is concluded that mass variation has a lesser impact on performance than road slope. The work demonstrates the feasibility of converting a conventional vehicle to a BEV with comparable dynamic capabilities using currently available technology. Future development plans include constructing a battery prototype, electrifying the vehicle, and incorporating instrumentation for validation.

KEYWORDS:

• Battery electric vehicle
• vehicle dynamics simulation
• battery management system
• NEDC driving cycle
• Honda Civic conversion

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

Prasanna Moorthy Venugopal

Dr. Prasanna Moorthy Venugopal received his B.E., degree in Electrical and Electronics Engineering in 1995 and his M.E., degree in Power Electronics and Drives with distinction in 2005 from Government College of Technology, Coimbatore. He was awarded a Ph.D., from Anna University, Chennai in 2012. His areas of interest comprises of Power Electronics, Renewable Energy, Fault Detection, EV, Electric Circuits, Electromagnetic fields and DSP. He is currently working as Professor in Government College of Engineering, Bargur, Krishnagiri and has 25 Years of Teaching experience.

Kamali Samudram Manickam

Dr. Kamali Samudram Manickam received B.E degree in Electrical and Electronics Engineering from Government College of Engineering, Salem in 1991 affiliated to University of Madras and holds a Master’s degree (M.E.) from Karunya Institute of Technology, Coimbatore in 2004 affiliated to Anna University and a Ph.D. from Anna University, Chennai in 2015. Her primary areas of interest encompass Power System Control and Optimization as well as Image Processing. She boasts an impressive publication record, having authored more than twenty international journals, four books published by “The Charulatha Publications,” and four patented inventions. She is currently working as a Professor in Annapoorana Engineering College, Salem,Tamilnadu-636308 and she is having 27 years of experience in Teaching.

Malathy Vanniappan

Dr. Malathy Vanniappan is working in SR University, Warangal, Telangana State. She has completed 15 years of service in teaching field and has industrial experience also. She graduated from Thiagarajar College of Engineering, Madurai. She has completed M.E. and Ph.D from Anna University, Chennai. Her area of interest is Image Processing and published mare than twenty journals. She has published 8 books in“The Charulatha Publications.

Gowri Sankar Periyannan Annadurai

Gowri Sankar Periyannan Annadurai currently working as an Associate Professor in Electrical & Electronics Engineering Department of Knowledge Institute of Technology, Salem, Tamilnadu, India. He has done B.E. with Honours in Electrical Engineering from Sona College of Technology, affliated to Anna University, Chennai and M.E & Ph.D. from College of Engineering Guindy, Anna University Chennai, India. His main research directions include artificial intelligence (neural networks, fuzzy logic, genetic algorithm, particle swarm optimization, and imperialist competitive algorithm) for power electronic and power system applications, Intelligent controller for power system and power electronics application and Nanoelectronics and Nanosensor based on new novel nanomaterials.