Innovative Probabilistic Optimization of Resonance Compensation in Dynamic Wireless Power Transfer

This paper presents an innovative methodology for designing resonance compensation in dynamic wireless power transfer systems for electric vehicles. The proposed technique leverages an optimization algorithm to identify the optimal combination of components that maximizes transferred energy while maintaining high transmission efficiency, achieving an effective trade-off between these key performance metrics. Unlike conventional design approaches, this method incorporates component tolerances and employs Monte Carlo simulations to estimate the probability of meeting desired performance criteria. This probabilistic analysis accounts for the combined effects of multiple tolerances, providing a robust evaluation of the solution's reliability by considering both manufacturing variations and aging effects. Designers can use this probabilistic insight to refine their choices by selecting components with stricter tolerances or exploring alternative designs. Furthermore, a MATLAB-based application, MatDWPT, has been developed to automate the design process. This user-friendly tool enables designers to input system specifications and receive optimized component recommendations, with all circuit analysis and optimization steps performed transparently in the background. The results obtained using the toolbox align with experimental measurements.