Multiobjective Optimization of Inductive Power Transfer Double-D Pads for Electric Vehicles

This article proposes a multiobjective optimization method of a primary double-D pad for inductive power transfer systems. First, a parametric sweep analysis is conducted to choose the crucial design parameters. Then, using the nondominated sorting genetic algorithm II, the structure of the double-D pad can be optimized based on two key objectives; ensuring a good coupling coefficient while minimizing the worst-case stray leakage magnetic fields. Several useful design guidelines are found from the optimization results, including how the dimensions of both the coil and layers affect the coupling coefficient and stray leakage magnetic fields around the pad. A practical coil suitable for wireless charging of electric vehicles at level 2, similar to that recommended in SAE J2954, is used as the reference and also as the starting point for the optimization. Two of the coil structures resulting from the optimization are chosen and investigated further to assess their performance with different secondary pad misalignments using finite element methods. Finally, an experimental setup is built to validate the optimal pad structures.

Automated summary

This article proposes a multiobjective optimization method for improving the design of primary double-D pad in inductive power transfer systems. Optimization is performed through parametric sweep and genetic algorithms to balance coupling coefficient and minimize stray leakage magnetic fields. Design guidelines are extracted from optimization results, and the effectiveness of the optimized structures is validated through experimental setups.