Multiobjective optimal design of wireless power transfer devices using a Genetic Algorithm and accurate analytical formulae

In this work, the Non-dominated Sorting Genetic Algorithm (NSGA) is employed for the multiobjective optimal design of Resonant Inductive Power Transfer (RIPT) devices. A thorough review of the literature has been performed in order to propose accurate analytical formulae for computing the lumped parameters of the system equivalent circuit. A particular attention is paid on the representation of the skin and proximity effects, and on the consideration of any relative position between the coils. The tool permits to observe design trends by comparing optimal individuals in the Pareto front, and is illustrated on an electric vehicle battery charging application. In that case, a design able to transfer 3 kW at 60 kHz, with 93.53 % efficiency through 25 cm air with a fixed radial space footprint of 25 cm, and capable to support a lateral misalignment of 10 cm, was obtained.