| Issue |
E3S Web Conf.
Volume 564, 2024
International Conference on Power Generation and Renewable Energy Sources (ICPGRES-2024)
|
|
|---|---|---|
| Article Number | 02004 | |
| Number of page(s) | 6 | |
| Section | Electric Vehicles and Drives | |
| DOI | https://doi.org/10.1051/e3sconf/202456402004 | |
| Published online | 06 September 2024 | |
A Bidirectional ANN-Based On-Board LEV Charging System
Institute of Aeronautical Engineering, Department of EEE, Hyderabad, Telangana, India - 500043
* Corresponding author: munavathvasantha2016@gmail.com
This paper introduces a Bidirectional Artificial Neural Network-Based On-Board Charging System for light electric vehicles (LEVs), addressing limitations of unidirectional systems in smart grid environments. The proposed solution aims to solve present challenges, such as low efficiency and high volume, by providing improved performance for supply and battery- side operations. To accomplish ripple-free loading and unloading, it uses a two- stage construction with two stages, AC-DC and DC- DC are employed along with a non-isolated bidirectional switched inductor buck-boost (BSIBB) converter. The high gain capability of the BSIBB converter eliminates the need for transformers, reducing total harmonic distortion (THD) and ensuring effective grid charging. Design and performance analyses validate the system’s suitability for LEV charging applications. ANN is artificial intelligence-based algorithm which gives better performance than state of art controllers.
Key words: Artificial Neural Network(ANN) / light electric vehicles LEV / bidirectional switched inductor buck-boost (BSIBB) / bidirectional inductor-based buck-boost converter (IBBBC)
© The Authors, published by EDP Sciences, 2024
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