Title :
Energy management system based on fuzzy control approach for hybrid electric vehicle
Author :
Yifeng, Wang ; Yun, Zhang ; Jian, Wu ; Ning, Chen
Author_Institution :
Sch. of Mech. & Automotive Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
Abstract :
In order to realize optimal distribution between two types of energy in hybrid electric vehicle (HEV) and assure the reasonable operation of motor and battery, an optimal method based on energy fuzzy control strategy is presented. The proposed energy fuzzy control strategy is modeled in SIMULINK and incorporated into the vehicle simulation software ADVISOR. Then, to the lack of the traditional method of getting membership function and fuzzy rules, it is presented that using the genetic algorithms optimizes the membership function of the original fuzzy logic controller. Finally, using simulation compares the optimized fuzzy logic controller and the original fuzzy logic controller, and the results show that the optimized fuzzy logic control strategy is effective in improving the fuel economy of HEV.
Keywords :
control engineering computing; fuel economy; fuzzy control; genetic algorithms; hybrid electric vehicles; ADVISOR; SIMULINK; energy management system; fuel economy; fuzzy control; fuzzy logic controller; fuzzy rules; genetic algorithms; hybrid electric vehicle; membership function; Acceleration; Batteries; Energy management; Fuzzy control; Fuzzy logic; Genetic algorithms; Hybrid electric vehicles; Hybrid power systems; Immune system; Power system modeling; Energy Control; Fuzzy Control; Genetic Algorithms; HEV;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5191855