| Issue |
EPJ Web Conf.
Volume 341, 2025
2nd International Conference on Advent Trends in Computational Intelligence and Communication Technologies (ICATCICT 2025)
|
|
|---|---|---|
| Article Number | 01019 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/epjconf/202534101019 | |
| Published online | 20 November 2025 | |
https://doi.org/10.1051/epjconf/202534101019
Review of Traction Motors for Electric Vehicle Application
1 Associate Professor, Electrical Engineering Department, P.R. Pote Patil College of Engineering & Management, Amravati
2 Assistant Professor, Electrical Engineering Department, P.R. Pote Patil College of Engineering & Management, Amravati
* Dr.D.A. Shahakar : This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 20 November 2025
Abstract
The accelerating demand for electric vehicles (EVs) and the necessity to reduce fossil fuel dependence have intensified research on advanced traction motor technologies. This paper presents a comparative analysis of key traction motors including DC Series, Induction, Permanent Magnet Synchronous (PMSM), Switch Reluctance (SRM), and Brushless DC (BLDC) motors. A quantitative evaluation is conducted considering torque density, efficiency, and cost-effectiveness. Results indicate that PMSMs achieve peak efficiencies of 93-95% with excellent speed control, while induction motors maintain strong cost-performance ratios. SRMs offer durability and fault tolerance but exhibit torque ripple, whereas BLDCs provide compact integration with high dynamic response. These insights serve as guidelines for EV motor selection. Keywords—Traction Motors, Electric Vehicles, Performance Comparison, Efficiency Analysis, Rare-Earth-Free Motors, Cost Optimization.
Key words: Traction Motors / Electric Vehicles / Hybrid Electric Vehicles / Brushless DC Motors and Axial Induction Motors
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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