Outputvoltage control and efficiency optimization of wireless power transfer system

Abstract:

To address the issues of unstable output voltage and relatively low transfer efficiency in magnetically coupled wireless power transfer (WPT) systems caused by dynamic load variations, coupling coefficient fluctuations, and component parameter drift in practical applications, this paper proposed a dual-side phase-shift cooperative control strategy based on a radial basis function neural network (RBFNN) and an improved perturb and observe (P&O) algorithm. First, this paper constructed and analyzed a mathematical model of the WPT system with a bilateral LCC compensation topology. To address the nonlinearity and uncertainties of the model, this paper designed an RBFNN controller with online self-learning capability. By collecting real-time system output error information to dynamically adjust network weights, it directly generated accurate phase-shift angle control signals and regulated the system output voltage by controlling the phase-shift angle of the controllable rectifier circuit at the receiving end. This effectively overcame the shortcomings of traditional control methods relying on precise models and poor adaptability. Second, to maximize the transfer efficiency while ensuring stable output voltage, the transmitting end adopted a variable-step P&O algorithm to dynamically adjust the phase-shift angle of the inverter circuit for maximum efficiency tracking. Finally, this paper built an experimental prototype for verification. The results demonstrate that the system output voltage exhibits excellent dynamic response performance and can achieve overshoot-free tracking of the desired voltage; it shows strong robustness under disturbances, with a voltage fluctuation range of less than 1%; meanwhile, the system efficiency increases by a maximum of 14.9%, which fully proves the effectiveness of the proposed method.