Optimizing power converters for enhanced electric vehicle propulsion: A novel research methodology
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.4.23Keywords:
Electric Vehicles, Power Converter Optimization, Research Methodology, Simulation-based Design, Vehicle-to-Grid, Sustainable TransportationDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This research paper presents a novel methodology for enhancing power converters in electric vehicle (EV) propulsion systems, focusing on optimizing efficiency, reliability, and performance. It integrates theoretical analysis, simulations, and practical experimentation to address current challenges in power converter technology for EVs. The study begins with a literature review to identify gaps and emerging trends in power converter technologies. A theoretical model is then proposed, incorporating advanced semiconductor materials, innovative circuit topologies, and improved thermal management to boost efficiency and power density. Simulation tools, such as finite element analysis and system-level modeling, are used to validate the model and optimize design parameters. These simulations predict converter behavior under various conditions and loads, providing insights for performance improvements. A prototype power converter based on the optimized design is developed to validate the theoretical predictions. Experimental data is collected through rigorous testing, evaluating factors like efficiency, thermal performance, and response time. The experimental results are compared with simulation outcomes to verify the accuracy of the methodology. The study also explores bidirectional power flow for vehicle-to-grid (V2G) applications, assessing the impact on power converters and their role in energy exchange between EVs and the grid. This research offers a systematic approach to advancing power converters in EV propulsion systems, combining theoretical analysis, simulation-based optimization, and practical testing to contribute to the development of sustainable, high-performance electric transportation.Abstract
How to Cite
Downloads
Similar Articles
- Narmetova Y. Karimovna, Abdusamatov Khasanboy, Abdinazarova Iltifotkhon, Nurbaeva Khabiba, Mirzayeva Adiba, Psychoemotional characteristics in psychosomatic diseases , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Kunal Lanjekar, Prashant Kalshetti, Joe C. Lopez, Role of social media in lead generation , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Jayshree Mehta, Pranjal Bhatt, Vikas Raval, Skill development in India: Challenges, current, and future perspectives , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RRFSE: RNN biased random forest and SVM ensemble for RPL DDoS in IoT-WSN environment , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- M. Merla Agnes Mary, S. Britto Ramesh Kumar, DAJO: A Robust Machine Learning–Based Framework for Preprocessing and Denoising Fetal ECG Signals , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
- N. Saranya, M. Kalpana Devi, A. Mythili, Summia P. H, Data science and machine learning methods for detecting credit card fraud , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Jayaganesh Jagannathan, Dr. Agrawal Rajesh K, Dr. Neelam Labhade-Kumar, Ravi Rastogi, Manu Vasudevan Unni, K. K. Baseer, Developing interpretable models and techniques for explainable AI in decision-making , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- B. Kalpana, P. Krishnamoorthy, S. Kanageswari, Anitha J. Albert, Machine learning approaches for predicting species interactions in dynamic ecosystems , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- P. Vivekananth, Navneet Sharma, Cyberbullying Detection Using Continuous Based Bag of Words with Machine Learning by Text Classification , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- M. Iniyan, A. Banumathi, Brower blowfish nash secured stochastic neural network based disease diagnosis for medical WBAN in cloud environment , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
<< < 28 29 30 31 32 33 34 35 36 37 > >>
You may also start an advanced similarity search for this article.

