Multi-Parameter Identification of Resonant Wireless Charging System for Electric Vehicles

Abstract

As an energy-saving and environmentally friendly means of transportation, electric vehicles have received more and more attention from the society. Wireless charging technology for electric vehicles is also becoming increasingly popular. However, the drift of parameters in the wireless power transmission (WPT) system often affects the charging efficiency and transmission power of the system. This paper proposes an multi-parameter identification method for resonant circuit capacitance and inductance based on the characteristic variable model. Values of four feature variables are obtained by detecting the primary side voltage, primary side current and secondary side current of the resonant circuit: the effective value of the primary side current and that of the secondary side current, system characteristic frequency and the phase difference of the primary side voltage and current. Then combined with the theoretical calculation formula of the model, an identification model which takes the absolute value of the difference between the theoretical value and the measured value of the characteristic quantity as the objective function is constructed. In this paper, an improved particle swarm optimization (PSO) algorithm is used to optimize the objective function. Aiming at the problem that the standard PSO algorithm is easy to fall into local optimal, a method combining sub-region and neighborhood search is used. Simulation results show that the identification accuracy of this method is more than 97%, which proves the effectiveness of this method; An experimental platform with a power of up to 200 W and 81 kHz was designed, and the experimental results demonstrated the reliability of theoretical analysis and simulation.