Author:
Vasantha M.,Jagan Mohan V.C
Abstract
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.
Reference16 articles.
1. Review of the Impact of Vehicle-to-Grid Technologies on Distribution Systems and Utility Interfaces
2. Pandeyand R. Singh B., “A Power Factor Corrected Resonant EV Charger Using Reduced Sensor Based Bridgeless Boost PFC Converter,” IEEE Trans. Ind. Appl. (Early Access).
3. Ahmadi A., Tavakoli A., Jamborsalamati P., Rezaei N., Miveh M.R., Gandoman F.H., Heidari A.,Nezhad A. E., “Power quality improvement in smart grids using electric vehicles: a review,” IET Electric.Syst.
4. Adaptive Current Control for a Bidirectional Interleaved EV Charger With Disturbance Rejection
5. Gachovska T., Scarlatescu G., Radimov N.,and Ranjbar M.T., “Bidirectional 3.3 kW On-Board Battery Charger,” IEEE Energy Con.Cong. and Expo., 2020,pp. 1884-1890.