DocumentCode :
713425
Title :
A hybrid genetic algorithm with fuzzy logic controller for wireless power transmission system of electric vehicles
Author :
Wei-Cheng Wang ; Cheng-Chi Tai ; Sheng-Jie Wu ; Zih-Yi Liu
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear :
2015
fDate :
17-19 March 2015
Firstpage :
2622
Lastpage :
2627
Abstract :
A hybrid genetic algorithm with the fuzzy logic controller is developed for the high-efficiency power control of a wireless power transmission system for electric vehicles. For power regulation, the constant-frequency phase-shifted PWM is applied to regulate the inverter transmission power. In traditional genetic algorithms, a large search interval was required to avoid getting stuck in local optima. In this case, when the search interval was optimized and gradually converged to the global optimum, the parameter optimization capability in the genetic algorithm would be largely enhanced. In this paper, the compensation scheme of leakage inductance and the coil windings parameters are first analyzed and evaluated; then, the genetic algorithm is used for optimizing the parameters of a fuzzy controller in order to achieve the feedback power control for the proposed control strategy. The simulation results show the effectiveness and superiority of the proposed power control method.
Keywords :
PWM invertors; coils; compensation; electric vehicles; feedback; fuzzy control; genetic algorithms; inductive power transmission; power control; coil winding parameter; constant-frequency phase-shifted PWM; electric vehicle; feedback power control; fuzzy logic controller; high-efficiency power control; hybrid genetic algorithm; inverter transmission power regulation; leakage inductance compensation scheme; parameter optimization capability; wireless power transmission system; Capacitance; Couplings; Fuzzy logic; Genetic algorithms; Niobium; Power transmission; Wireless communication; electric vehicle; fuzzy control; genetic algorithm; wireless power transfer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology (ICIT), 2015 IEEE International Conference on
Conference_Location :
Seville
Type :
conf
DOI :
10.1109/ICIT.2015.7125484
Filename :
7125484
Link To Document :
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