An Adaptive Energy Management System for Battery-Supercapacitor Electric Vehicle Based on Frequency Separation

An adaptive Energy Management System (EMS) is proposed for Battery/Supercapacitor (SC) based Hybrid Energy Storage System (HESS) for use in Electric Vehicles (EVs). The objective of this study is to improve the performance and effectiveness of HESS by developing a filter based EMS using fuzzy control while taking actual topographical details into consideration. In this technique the demanded power is split into high frequency and low frequency parts using a low pass filter where the regulating frequency of the filter is adjusted by a Fuzzy Controller. The high and low frequency power components are delivered by the SC and battery respectively. The actual road slope data are computed using Contour Positioning System. The developed adaptive filter technique is examined for different road slope conditions such as city tour, downhill and uphill journeys. The proposed Fuzzy filter based EMS is assessed as per the energy consumption by the sources and its performance is compared with that of the Fuzzy based EMS. The performances of these two controllers are evaluated based on Mean battery power and Ampere hour (Ah) throughput of the battery. The Fuzzy filter based EMS showed a reduction of 28.25%, 44.08% and 23.85% in battery Ah throughput during uphill, city tour and downhill journeys respectively in comparison to only fuzzy controller. This shows that the proposed adaptive EMS technique is able to reduce the impact of power fluctuations on the battery and improve its performance.