Optimal Power Management in battery/ SCAP of Electric Vehicles using Artificial Intelligence techniques
Author(s):
Cassia Jemi M.A, Dr.T.Dharma Raj
Keywords:
Battery Energy management HESS SCAP Deep Convolutional Neural Network
Abstract
Energy management is a critical technology in Electric Vehicle (EV) for maximizing efficiency, and fuel economy, as well as reducing pollutant emissions.The Energy storage systems (ESS) is the prime factor that accounts for the Electric Vehicle (EV) performance and reliability. However, the conventional ESS is heavy, costly and bulky in nature and so the EV characteristics like mileage are limited. The improvement of thermal battery behaviour is the only energy source which reduces the cost and thus optimizes the performance of EVs. The Fuel cell (FC) is also a good alternative source with higher efficiency and zero emissions but, it has a sluggish dynamic responsiveness, lengthy startup time, brittle output characteristics, and expensive cost. FCs has a major advantage of incorporating ESS, which have the ability to cover the fast power variations. A major problem when using more battery cells is that a huge peak power or quick charging/discharging can harm one or more cells. Hybrid Energy storage systems (HESS) consisting of supercapacitors and battery are used in EVs where the supercapacitors serve as a supplementary energy resource for satisfying the instant high power demands. Several control strategies have been suggested to coordinate the power flow between the supercapacitors and the energy sources.
Article Details
Unique Paper ID: 163226

Publication Volume & Issue: Volume 0, Issue no

Page(s): 56 - 60
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