Title: Self-Charging System for Electric Vehicles Using Neural
Network
Volume: 11 - Issue: 12 - Date: 08-12-2022
Approved ISSN: 2278-1412
Published Id: IJAECESTU9 | Page No.: 103 -107
Author: Anjali Maurya
Co- Author: Ashish Bhargava
Abstract:-– An electric car's hybrid energy storage system (HESS), which is comprised of a battery and a supercapacitor, has excellent performance in terms of both power density and energy density when used in conjunction with the vehicle. With the help of neural networks and PI controllers, a hybrid electric vehicle (EV) is designed with an eye toward commercialization. An energy management strategy (EMS) for the EV is proposed, which takes into account the superiority achieved by each ESS as well as its protection from the other ESSes under different driving conditions. The specific energy and specific power of electrochemical batteries are, on average, substantially lower than those of conventional gasoline batteries. It is necessary to use a significant number of batteries in order to achieve the appropriate level of performance, which results in an increase in vehicle weight and expense, as well as a reduction in overall vehicle performance.
Key Words:-Electric Vehicles, Hybrid Energy Storage System, Energy Management Strategy
Area:-Engineering
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