Fuzzy Logic Based Energy Management System for Hybrid Electric Vehicle
Author(s) -
Z Tareq,
Noorasiah Sulaiman,
M. A. Hannan,
Ahmed Mohamed,
Edy Herianto Majlan,
Wan Ramli Wan Daud
Publication year - 2015
Publication title -
review of energy technologies and policy research
Language(s) - English
Resource type - Journals
eISSN - 2409-2134
pISSN - 2313-7983
DOI - 10.18488/journal.77/2015.2.2/77.2.29.36
Subject(s) - supercapacitor , battery (electricity) , energy management , automotive engineering , energy storage , fuzzy logic , computer science , hybrid system , energy management system , reliability (semiconductor) , controller (irrigation) , electric vehicle , matlab , energy (signal processing) , engineering , capacitance , power (physics) , artificial intelligence , operating system , quantum mechanics , electrode , statistics , chemistry , biology , agronomy , physics , machine learning , mathematics
Hybrid electric vehicles have gained attention throughout the globe with its advantage of green technology and reduced greenhouse gases emission. Moreover, hybrid vehicles being powered by battery would be the best option of replacing current petrol or gas dependent vehicles. There are drawbacks though; battery has limited lifetime and is very costly. Hence, it is hybridized with other energy storage systems such as supercapacitor. This paper focuses on the energy management system for the energy storage system consisting battery and supercapacitor of a hybrid electric vehicle using fuzzy logic based controller. The energy management system, which manages energy feed between battery and supercapacitor, is then simulated in Matlab/Simulink to verify its reliability and validity of operation.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom