Title :
Control strategy in hybrid electric vehicle using fuzzy logic controller
Author :
Majdi, Laila ; Ghaffari, Ali ; Fatehi, Nima
Author_Institution :
South Branch, Mech. Dept., Azad Univ., Tehran, Iran
Abstract :
In a hybrid vehicle with dual power systems such as internal combustion engines working with conventional fuels and electric motors, each system has specific operational characteristics and requirements which these have to be matched with each other and at the same time with the vehicle itself. This dual power system is too complex especially from points of nonlinearity, uncertainty, and switching structure and needs to be controlled by an intelligent controller accurately to meet vehicle´s needs, guaranteeing stability, smooth operation and also today´s standards. According to the discrete behavior of HEV, a model of this system has been developed in MATLAB/Simulink. In this work an on-line strategy based on fuzzy logic control is developed for energy flow management between internal combustion engine (ICE), as a major source of energy and batteries as energy storage system (ESS). It will optimize the power output, fuel economy and also meets vehicle´s operational requirements. In addition, Battery State of Charge (SOC) is kept within a suitable range to guarantee the life expectancy of the battery. Using this controller, the model shows major improvement in fuel consumption and emissions levels. The overall design of the controller meant a smooth power flow to the wheels and consequently to the vehicle. The robust properties of the controller and its capabilities during different driving cycles (urban/highway) makes it unique. For validation purposes the simulation results are compared with the results derived from Advisor software and the experimental results in the literature.
Keywords :
electric motors; fuel systems; fuzzy control; hybrid electric vehicles; intelligent control; internal combustion engines; MATLAB/Simulink; battery state of charge; control strategy; dual power systems; electric motors; energy flow management; energy storage system; fuel consumption; fuel economy; fuzzy logic controller; hybrid electric vehicle; intelligent controller; internal combustion engines; nonlinearity; operational characteristics; operational requirements; switching structure; uncertainty; Batteries; Control systems; Fuels; Fuzzy logic; Hybrid electric vehicles; Hybrid power systems; Internal combustion engines; Nonlinear control systems; Power system modeling; Power system stability;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-4774-9
Electronic_ISBN :
978-1-4244-4775-6
DOI :
10.1109/ROBIO.2009.5420563