Kavitha Kumari, K.S and Chitra, L. and Arun Kumar, J and Saranya, S.C (2023) ANN based SEPIC Converter for Electric Vehicle Charging. In: UNSPECIFIED.
Full text not available from this repository.Abstract
In this paper, a Single Ended Primary Inductance Converter (SEPIC) topology with Power Factor Correction (PFC) is presented as a method for charging the battery of an electric vehicle. This converter offers advantages such as reducing the total number of components and reducing the conduction loss during AC to DC conversion, leading to a higher overall system efficiency. The working functionality of the SEPIC-PFC converter is enhanced by using Proportional Integral (PI) controller. By using supercapacitors to collect energy, the batteries experience less stress, resulting in longer battery life and lower costs. The Multi Source Inverter (MSI) is deployed for converting DC voltage into AC voltage, and it also controls the flow of electrical power. The recommended MSI for Electric Vehicle (EV) battery system with ANN Feedback line controller is designed to enhance the effectiveness of the suggested approach by managing the State of Charge (SOC).By integrating an ANN feedback line controller for bidirectional DC/DC converter, energy management is attained with enhanced battery charging and discharging. Based on simulation results attained in MATLAB/Simulink, the proposed control technique is shown to perform well and is robust. The suggested method demonstrates that, with the offered sufficient training data for the ANN models, highly precise SOC estimated outcomes are accomplished. © 2024 Elsevier B.V., All rights reserved.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Engineering > Electrical and Electronic Engineering |
| Divisions: | Engineering and Technology > Aarupadai Veedu Institute of Technology, Chennai > Electrical & Electronics Engineering |
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 01 Dec 2025 05:23 |
| URI: | https://vmuir.mosys.org/id/eprint/2452 |
Dimensions
Dimensions