Abstract
To obtain accurate optimal design results in electric machines, the finite element analysis (FEA) technique should be used; however, it is time-consuming. In addition, when the design of experiments (DOE) is conducted in the optimal design process, mechanical design, analysis, and post process must be performed for each design point, which requires a significant amount of design cost and time. This study proposes an automated DOE procedure through linkage between an FEA program and optimal design program to perform DOE easily and accurately. Parametric modeling was developed for the FEA model for automation, the files required for automation were generated using the macro function, and the interface between the FEA and optimal design program was established. Shape optimization was performed on permanent magnet synchronous motors (PMSMs) for small electric vehicles to maximize torque while maintaining efficiency, torque ripple, and total harmonic distortion of the back EMF using the built-in automation program. Fifty FEAs were performed for the experimental points selected by optimal Latin hypercube design and their results were analyzed by screening. Eleven metamodels were created for each output variable using the DOE results and root mean squared error tests were conducted to evaluate the predictive performance of the metamodels. The optimization design based on metamodels was conducted using the hybrid metaheuristic algorithm to determine the global optimum. The optimum design results showed that the average torque was improved by 2.5% in comparison to the initial model, while satisfying all constraints. Finally, the optimal design results were verified by FEA. Consequently, it was found that the proposed optimal design method can be useful for improving the performance of PMSM as well as reducing design cost and time.
Highlights
The necessity of eco-friendly vehicles has been highlighted owing to environmental pollution and depletion of fossil fuels
To obtain the design of experiments (DOE) results, several models had to be designed and finite element analysis (FEA) were required. The novelty of this distinguishes it from previous studies for the following reasons: First, optimal design can be processed based on a novel automated DOE procedure based on FEA, so it can be done faster and more accurately
As manual DOE requires a lot of lot of effort and time, this study suggests the automation of the DOE process
Summary
The necessity of eco-friendly vehicles has been highlighted owing to environmental pollution and depletion of fossil fuels. The work in [6] proposed an optimization process of a PMSM to optimize the weight, output power, and suitability It performed shape optimization of permanent magnets and rotor core using FEA with the fuzzy inference system strategy. The study in [11] optimized a PMSM by combining an optimal algorithm and metamodel, i.e., the genetic algorithm and the Kriging model, based on DOE. To obtain the DOE results, several models had to be designed and FEAs were required. The novelty of this distinguishes it from previous studies for the following reasons: First, optimal design can be processed based on a novel automated DOE procedure based on FEA, so it can be done faster and more accurately. DOEthis and accurately, this study proposes an through linkage an FEA program and between an optimal program.and
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
