Title :
An intelligent energy management model for a parallel hybrid vehicle under combined loads
Author :
Khayyam, Hamid ; Kouzani, Abbas Z. ; Hu, Eric J.
Author_Institution :
Sch. of Eng. & IT, Deakin Univ., Geelong, VIC
Abstract :
To exploit the benefits offered by parallel HEVs, an intelligent energy management model is developed and evaluated in this paper. Despite most existing works, the developed model incorporates combined wind/drag, slope, rolling, and accessories loads to minimise the fuel consumption under varying driving conditions. A slope prediction unit is also employed. The engine and the electric motor can output power simultaneously under a heavy-load or a slopped road condition. Two simulation were conducted namely slopped-windy-prediction and slopped-windy-prediction-hybrid. The results indicate that the vehicle speed and acceleration is smoother where the hybrid component was included. The average fuel consumption for the first and second simulations were 7.94 and 7.46 liter/100 km, respectively.
Keywords :
electric motors; energy management systems; hybrid electric vehicles; electric motor; fuel consumption; intelligent energy management model; parallel hybrid vehicle; slopped-windy-prediction; Automotive engineering; Electric motors; Energy management; Fuels; Fuzzy logic; Hybrid electric vehicles; Ice; Intelligent vehicles; Internal combustion engines; Propulsion; Fuel consumption; friction; intelligent energy management; modeling; parallel hybrid;
Conference_Titel :
Vehicular Electronics and Safety, 2008. ICVES 2008. IEEE International Conference on
Conference_Location :
Columbus, OH
Print_ISBN :
978-1-4244-2359-0
Electronic_ISBN :
978-1-4244-2360-6
DOI :
10.1109/ICVES.2008.4640869