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Energies 2019, 12(1), 153; https://doi.org/10.3390/en12010153

Robust Design Optimization with Penalty Function for Electric Oil Pumps with BLDC Motors

1
Department of Electrical Engineering, Honam University, 417 Eodeung-daero, Gwangsan-gu, Gwangju 62399, Korea
2
Department of Automotive Engineering, Honam University, 417 Eodeung-daero, Gwangsan-gu, Gwangju 62399, Korea
*
Author to whom correspondence should be addressed.
Received: 29 November 2018 / Revised: 21 December 2018 / Accepted: 27 December 2018 / Published: 2 January 2019
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Abstract

In this paper, we propose and evaluate a robust design optimization (RDO) algorithm for the shape of a brushless DC (BLDC) motor used in an electric oil pump (EOP). The components of the EOP system and the control block diagram for driving the BLDC motor are described. Although the conventional deterministic design optimization (DDO) method derives an appropriate combination of design goals and target performance, DDO does not allow free searching of the entire design space because it is confined to preset experimental combinations of parameter levels. To solve this problem, we propose an efficient RDO method that improves the torque characteristics of BLDC motors by considering design variable uncertainties. The dimensions of the stator and the rotor were selected as the design variables for the optimal design and a penalty function was applied to address the disadvantages of the conventional Taguchi method. The optimal design results obtained through the proposed RDO algorithm were confirmed by finite element analysis, and the improvement in torque and output performance was confirmed through experimental dynamometer tests of a BLDC motor fabricated according to the optimization results. View Full-Text
Keywords: optimal design; oil pump; brushless DC; motor; robust; vehicles optimal design; oil pump; brushless DC; motor; robust; vehicles
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Yoon, K.-Y.; Baek, S.-W. Robust Design Optimization with Penalty Function for Electric Oil Pumps with BLDC Motors. Energies 2019, 12, 153.

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