Optimal Design of IPT Bipolar Power Pad for Roadway-Powered EV Charging Systems
Article
Jafari, H, Olowu, TO, Mahmoudi, M et al. (2021). Optimal Design of IPT Bipolar Power Pad for Roadway-Powered EV Charging Systems
. 44(3), 350-355. 10.1109/ICJECE.2021.3075639
Jafari, H, Olowu, TO, Mahmoudi, M et al. (2021). Optimal Design of IPT Bipolar Power Pad for Roadway-Powered EV Charging Systems
. 44(3), 350-355. 10.1109/ICJECE.2021.3075639
This article proposes a multiobjective design optimization of rectangular bipolar power pads (BPP) for dynamic inductive power transfer (IPT) with application in electric vehicles. Minimization of IPT’s design cost, loss that includes core and winding, and maximization of the IPT system’s tolerance against horizontal/vertical misalignment are considered as objective functions during the optimization process. The design variables of the proposed algorithm are the shield plate length and width, ferrite bar length and width, the overlapping length of the coils, and the coil width and inner length of the coil. Power electronic limitations by defining the IPT’s quality factor (4 < Qs < 10), maximum allowable electromagnetic field (EMF) exposure (EMF ≤ EMFMax), efficiency of all possible solutions greater than 80% (η > 80%), and upper/lower limits of design parameters are considered as the constraints of this optimization problem. The time-harmonic electromagnetic physics model of the BPP is analyzed using an finite element method magnetics (FEMM) software coupled with MATLAB. A nondominated genetic algorithm (NSGA-II) is employed as the optimization solver, in which the electromagnetic measurements from the FEMM software are used to evaluate the fitness values of the proposed objectives. The proposed BPP design optimization is applied on a 10-kW IPT system as a case study. The optimization results produced 15 Pareto optimal solutions. A validation study of two Pareto front solutions (PFS) is also presented. The Pareto optimal solutions allow the designer to select the best design parameters based on the objectives of highest priority.
