Parameter optimization method for antimisalignment of inductive power transfer system based on genetic algorithm

The mutual inductance parameters change from time to time. When conducting dynamic wireless power transfer using an inductive power transfer system, it results in larger fluctuation of output power. Therefore, a parameter optimization method is necessary to improve the stability of inductive power transfer system during dynamic misalignment. In this study, a nonlinear programing model with objective function of minimum voltage gain difference was established by taking S-LCC topology as an example. Genetic algorithm and nonlinear programming were combined to optimize the compensating parameters of the system and to realize minimum fluctuation of output voltage gain of the system within any given range of mutual inductance parameters. Optimization results show that output stability can be realized by adjusting the compensation capacitance in the primary side. The feasibility of the theory was verified through stimulation and test prototype. Test results show that when the mutual induction range is from 29.3 mu H to 84.3 mu H, the voltage gain of the system varies from 0.67 to 0.77. The fluctuation ratio of voltage gain is 6.7%, and the fluctuation ratio of voltage gain under the circumstance of resonance parameters is 40.2%.