| Issue |
EPJ Web Conf.
Volume 375, 2026
Recent Technologies and Innovations in Electronics and Photonics (RTEP-2026)
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 10 | |
| Section | Emerging Interdisciplinary Research and Applications | |
| DOI | https://doi.org/10.1051/epjconf/202637503001 | |
| Published online | 26 June 2026 | |
https://doi.org/10.1051/epjconf/202637503001
Taguchi-TOPSIS Methodology for Optimizing Electric Vehicle Charging: A Data-Driven Approach to Enhancing Charging Efficiency and Minimizing Energy Consumption
1 Department of Electrical and Electronics Engineering, AMET Deemed to be University, Chennai, India.
2 Department of Mechanical Engineering, Bonam Venkata Chalmayya Engineering College, Odalarevu, Allavaram Mandal, Dr. B R Ambedkar Konaseema District, Andhra Pradesh.
3 Department of Mechanical Engineering, KIT-Kalingarkarunanidhi Institute of Technology, Coimbatore.
4 Department of Electronics and Communication Engineering, KG Reddy College of Engineering and Technology, Hyderabad, Telangana.
5 Research Scholar, Department of Electrical and Electronics Engineering, AMET Deemed to be University, Chennai, India
6 Research Scholar, Department of Electrical and Electronics Engineering, AMET Deemed to be University, Chennai, India.
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 26 June 2026
Abstract
Efficiency in charging is essential to reduce the charging time and the amount of energy required, which has become a critical requirement due to the increased use of electric vehicles (EVs). To address this problem, the Taguchi-TOPSIS technique was employed to find the ideal combination for reducing the EV charging time and energy consumption, taking into account important parameters like the charging power, battery temperature, voltage, and cable length. To measure the effect of the input parameters on the output variables, the S/N ratios of all input parameters were computed, and the ranking of the EV charging parameters was done through the delta values. Residual plots were plotted to verify the precision of the model developed. The ANOVA findings indicate that the battery temperature parameter is the most significant one affecting EV charging time and energy consumption. The optimal combination identified through this analysis was P3-T1-V3-L1, where the specific parameters for the optimal setup included: a charging power of 9 kW, a battery temperature of 15°C, a voltage of 500V, and a cable length of 1 meter. This configuration ensures efficient charging procedures by lowering energy consumption and time required for charging.
© The Authors, published by EDP Sciences, 2026
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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