TY - GEN
T1 - A hybrid genetic algorithm with fuzzy logic controller for wireless power transmission system of electric vehicles
AU - Wang, Wei Cheng
AU - Tai, Cheng Chi
AU - Wu, Sheng Jie
AU - Liu, Zih Yi
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/16
Y1 - 2015/6/16
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84937696807&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84937696807&partnerID=8YFLogxK
U2 - 10.1109/ICIT.2015.7125484
DO - 10.1109/ICIT.2015.7125484
M3 - Conference contribution
AN - SCOPUS:84937696807
T3 - Proceedings of the IEEE International Conference on Industrial Technology
SP - 2622
EP - 2627
BT - 2015 IEEE International Conference on Industrial Technology, ICIT 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Conference on Industrial Technology, ICIT 2015
Y2 - 17 March 2015 through 19 March 2015
ER -