Abstract
Motor design can be said as multi-modal optimization problem, as many performances should be considered. In addition, a time-consuming finite element method (FEM) is required for accurate analysis of the motor, and such computational burden becomes worse when the FEM is applied to multi-modal optimization problem. In this paper, adaptive-sampling kriging algorithm (ASKA) is proposed to relieve the computation cost of multi-modal optimization problem. The ASKA utilizes kriging interpolation model with generated samples by Compact Search Sampling (CSS) and Exclusive Space-filling Method (ESM). The CSS improves the accuracy of the solutions by generating samples near the expected solutions, and the ESM guarantees the diversity of solutions by generating samples far from existing samples, avoiding solution-near area. Using CSS and ESM, the ASKA adjusts the number of samples effectively and reduces function call considerably. The superior performance of the ASKA was verified by mathematical test functions with complex objective function regions. To validate the feasibility of actual electric machines, the ASKA was applied to optimal design of permanent magnet assisted synchronous reluctance motors for electric vehicles and optimum design with diminished torque ripple is derived.
Highlights
In order to satisfy the strengthened environmental regulations due to excessive emission of greenhouse gases, interests in eco-friendly vehicles such as electric vehicles (EVs) have been increasing and many studies have been conducted on EVs
To validate the feasibility of actual electric machines, the adaptive-sampling kriging algorithm (ASKA) was applied to optimal design of permanent magnet assisted synchronous reluctance motors for electric vehicles and optimum design with diminished torque ripple is derived
As motors for EV propulsion require high-power density, high efficiency, and mechanical stability at high-speed operation, the interior permanent magnet synchronous motor (IPMSM) has been widely used for EVs owing to high torque density, superior power factor, and efficiency by using both magnet torque and reluctance torque [1], [2]
Summary
In order to satisfy the strengthened environmental regulations due to excessive emission of greenhouse gases, interests in eco-friendly vehicles such as electric vehicles (EVs) have been increasing and many studies have been conducted on EVs. Plot of the kriging surrogate model of random sampling and MJS when the objective region is defined as (1), and the number of samples are equal as 25. B. COMPACT SEARCH SAMPLING The CSS is the step that improves the accuracy of the solutions of the kriging surrogate model by generating samples near the solutions: one on the predicted solution, and the other one among the points of first contour surrounding the predicted solutions. Add ESM sample: Using kriging surrogate model contour information, the exclusive boundary is set around each solution.
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