A comparative MATLAB/Simulink framework for drive-cycle-based traction motor sizing in battery electric four-wheelers

Shweta S. Suryavanshi
Department of Mechanical Engineering, Pimpri Chinchwad College of Engineering, Pune 411044, Maharashtra, India
Sagar Wankhede
Department of Mechanical Engineering, Pimpri Chinchwad College of Engineering, Pune 411044, Maharashtra, India
Pravin M. Ghanegaonkar
Department of Mechanical Engineering, Savitribai Phule Pune University, Pune 411007, Maharashtra, India
Devakant Baviskar
Department of Mechanical Engineering, Terna Engineering College, Navi Mumbai 400706, Maharashtra, India
Surekha Khetree
Department of Mechanical Engineering, Bharati Vidyapeeth College of Engineering, Navi Mumbai 400614, Maharashtra, India
Choon Kit Chan
Faculty of Engineering and Quantity Surveying, INTI International University, Nilai 71800, Negeri Sembilan, Malaysia
Sohankumar G. Prajapati
Department of Electrical Engineering, Government Engineering College, Patan 384265, Gujarat, India
Vijay Chaudhary
Industries Commissionerate, Gandhinagar 382010, Gujarat, India
Subhav Singh
Noida Institute of Engineering and Technology, Greater Noida 201324, Uttar Pradesh, India; Division of Research and Development, Lovely Professional University, Phagwara 144411, Punjab, India
Deekshant Varshney
Centre for Research Impact and Outcome, Chitkara University, Rajpura 140417, Punjab, India; Centre for Promotion of Research, Graphic Era (Deemed to be University), Dehradun 248002, Uttarakhand, India

Article ID: 4688

Keywords: electric vehicle; traction motor; motor power sizing; drive cycle; vehicle dynamics; MATLAB/Simulink; process innovation

Abstract

As more battery electric vehicles (BEVs) are being introduced, the need for accurate traction motor sizing to achieve optimal performance, energy efficiency, driving range and cost has become more important. The conventional analytical sizing methods are based on worst-case conditions and often result in over- or under-sizing a motor, with the resulting negative impact on system efficiency and economic viability. In this study, a MATLAB/Simulink model is developed which compares directly between analytical sizing and drive cycle-based simulation of a battery electric four-wheeler for a Maruti Zen passenger car. The equations of the vehicle dynamics with the four forces: rolling resistance, aerodynamic drag, acceleration, and gradient force approximate the tractive force, wheel torque, and motor power. The vehicle is tested in three standardised drive cycles (New European Driving Cycle (NEDC), Highway Fuel Economy Test (HWFET) and the Artemis Urban Drive Cycle (UDC)), and the results are compared to the analytical method. The analytical approach predicts a 23.23–67.99 kW power band for the road gradient range (0°–18°) analysed, while drive-cycle simulation suggests 15.29 kW (NEDC), 14.52 kW (HWFET) and 22.10 kW (UDC)—a 67.5–78.6% decrease from the analytical upper bound. The results show that drive-cycle-based sizing can provide a more accurate, application-specific assessment of traction-motor sizing and help to minimize the risk of over-sizing and increase efficiency. In addition to re-working known vehicle-dynamics equations, this work is novel in that the power gap between the two routes of analytical and drive-cycle sizing is benchmarked for a vehicle and set of parameters, and a low-cost, practical screening tool for selecting a traction motor appropriate for the operating environment and duty profile is provided to manufacturers and researchers.

Published

2026-09-24

How to Cite

Shweta S. Suryavanshi, Sagar Wankhede, Ghanegaonkar, P. M., Baviskar, D., Surekha Khetree, Choon Kit Chan, Sohankumar G. Prajapati, Vijay Chaudhary, Subhav Singh, & Deekshant Varshney. (2026). A comparative MATLAB/Simulink framework for drive-cycle-based traction motor sizing in battery electric four-wheelers. Energy Storage and Conversion, 4(2). https://doi.org/10.59400/esc4688

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Vol. 4 No. 3 (2026): In Progress

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Copyright (c) 2026 Shweta S. Suryavanshi, Sagar Wankhede, Pravin M. Ghanegaonkar, Devakant Baviskar, Surekha Khetree, Choon Kit Chan, Sohankumar G. Prajapati, Vijay Chaudhary, Subhav Singh, Deekshant Varshney

This work is licensed under a Creative Commons Attribution 4.0 International License.

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