An optimal energy management development for various configuration of plug-in and hybrid electric vehicle
来源期刊:中南大学学报(英文版)2015年第5期
论文作者:Morteza Montazeri-Gh Mehdi Mahmoodi-k
文章页码:1737 - 1747
Key words:plug-in and hybrid electric vehicle; energy management; configuration; genetic fuzzy controller; fuel consumption; emission
Abstract: Due to soaring fuel prices and environmental concerns, hybrid electric vehicle (HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV’s fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. an optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.
Morteza Montazeri-Gh, Mehdi Mahmoodi-k
(Systems Simulation and Control Laboratory, School of Mechanical Engineering,
Iran University of Science and Technology, Tehran, P.O. Box 16846-13114, Iran)
Abstract:Due to soaring fuel prices and environmental concerns, hybrid electric vehicle (HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV’s fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. an optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.
Key words:plug-in and hybrid electric vehicle; energy management; configuration; genetic fuzzy controller; fuel consumption; emission