Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Session Overview
PC-M4: Optimization and Design
Thursday, 18/Jul/2019:
10:50am - 12:40pm

Session Chair: Piergiorgio Alotto
Session Chair: Takeo Ishikawa
Location: Patio 44-55

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Optimum Design Evaluation and Experiment of PMA-SynRM for Power Improvement

YoungHyun Kim, Qian Yan, JungHo Lee

Hanbat national university, Korea, Republic of (South Korea)

This paper deals with the optimum design of permanent magnet assisted synchronous reluctance motor (PMA-SynRM) for power improvement. The focus of this paper is found firstly a design solution through the comparison of torque density and d, q-axis inductance according to the rotor magnet and flux barrier shape, secondly, a mixed resolution with central composite design (CCD) is introduced and analysis of variance (ANOVA) is conducted to determine the significance of the fitted regression model. The proposed procedure allows the definition of the rotor magnet and flux barrier shape, dimensions starting from an existing motor or a preliminary design according to the rated wattage

Determination Scheme of Stator Parameters for Making Rotating Fields Circular in a Single-Phase Induction Motor

Dae Yong Um, Gwan Soo Park

Pusan National University, Korea, Republic of (South Korea)

Unlike three-phase induction motors, circular rotating fields cannot be inherently formed in single-phase induction motors(SPIMs). In this paper, the parameters of the stator winding for circular rotating magnetic fields are derived. The effects of parameters on operating performance are analyzed to determine whether the parameters are suitable to improve performance without distorting circular rotating magnetic fields. Then, the design scheme to improving operating performance while keeping circular rotating magnetic fields. The analyzed results and proposed algorithm provide insight into the design of high-performance capacitor-run SPIMs.

Research on Structural Parameters Optimization of Reluctance Resolver Based on Multi-objective Particle Swarm Optimization

Zhike Xu, Long Du, Feng Mao, Long Jin

School of Electrical Engineering, Southeast University, Nanjing, China

Variable reluctance(VR) resolvers are mainly used in the servo control system to obtain the rotor position and speed feedback information of the motor. In order to further improve the accuracy, this paper takes the reluctance resolver as the research object and uses ansoft to establish its finite element analysis model. The optimized parameters are the width of stator slot opening, the rotor sinusoidal coefficient and the minimum air gap length. The total harmonic distortion and zero-position voltage of the output signals are selected as objective functions. The mathematical model based on support vector regression machines is established by the simulation samples. The multi-objective particle swarm optimization algorithm is used to optimize the model to obtain the optimal parameters. The multi-objective particle swarm optimization algorithm replaces finite element numerical computation of electromagnetic fields. The simulation and experimental results verify the feasibility of the algorithm.

Efficiency Improvement of SPMSG in the Engine-Generator System of a PHEV Shown to be Compatible with an Optimal Operating Line

Ho-Chang Jung1, Deok-Jin Kim1, Dongsu Lee2

1Advanced Power System R&D Center, Korea; 2University of Illinois at Urbana-Champaign, United States of America

This paper presents a numerical optimization scheme of a surface permanent magnet synchronous generator (SPMSG) for achieving maximum efficiency. The generator and engine are linked and the optimal operating line is identified. A genetic algorithm is combined with a mesh adaptive direct search to create an intelligent memetic algorithm used to find the maximum efficiency distribution of SPMSG compatible to the OOL. The proposed optimization scheme includes both electrical and mechanical losses. Efficiency accuracy is confirmed by the resultant efficiency map. A prototype based on an optimized model is experimentally validated and shown to be well-suited for an EGS of a PHEV.

Design and Optimization of Hybrid Metamaterial Slab for Mid-Range Wireless Power Transmission with Low Working Frequency

Yang Wenjia, Siu Lau Ho, Weinong Fu, Xinsheng Yang

Hong Kong Polytechnic University, Hong Kong S.A.R. (China)

Metamaterials have been extensively used in the mid-range Resonant Wireless Power Transmission (R-WPT) system for transmission efficiency enhancement. The hybrid metamaterials that exhibit inhomogeneous material properties can be used to guide the wave propagation of electromagnetic fields and hence they are effective for transmission enhancement. This paper reports the designs and optimization of a hybrid metamaterial slab that has a multiple unit structure working at different frequencies in different positions of the slab. The performance of the slab at low frequency regime in terms of accuracy as well as the merits of the proposed design and optimization methodology are showcased as reported in this paper.

An Economical Three-Phase Fault Current Limiter Considering Different Types of Fault

Jiaxin Yuan1, Pengcheng Gan1, Liangliang Wei1,2, Hang Zhou1, Zhaoyang Zhang1, Yanhui Gao3, Kazuhiro Muramatsu3, Baichao Chen1

1School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China; 2Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501, Japan; 3Department of Electrical and Electronic Engineering, Saga University, Saga 840-8512, Japan

The application of a fault current limiter is an effective method to limit fault currents. Saturated core fault current limiters (SFCLs) are particularly promising devices for this challenge. The most serious fault in an electric power system is a three-phase short-circuit fault. The simultaneous use of three single-phase current limiters requires significant amounts of ferromagnetic material and space. An economical three-phase saturated core fault current limiter (ETSFCL) is proposed in this study, which uses a common yoke and permanent magnet to reduce material and space restrictions. This structure has good performance for single-phase, two-phase and three-phase faults. The basic operating principle of the ETSFCL is introduced based on the analysis of the magnetic and equivalent electrical circuits of the ETSFCL. Finite-element analysis simulations are performed by ANSOFT to validate the effectiveness of the fault clipping performance of the ETSFCL.

A Preference-based Physical Programming Method for Multi-objective Designs of Electromagnetic Devices

Siguang An1, Shiyou Yang2, Ning Wang2

1China Jiliang University, China, People's Republic of; 2Zhejiang University, China, People's Republic of

To reduce the unnecessary information bombing a decision maker and to improve the efficiency of solution procedures for multi-objective design problems, a vector preference-based physical programming method is proposed. To specify the region of interests of a decision maker, a preference frame is constructed with an aspiration point, a reservation point and a preference zone; to obtain multi-solutions in a single run, different pseudo preferences are updated synchronously. Dynamic pseudo-preference translation offset vector is developed to accommodate different mapping mechanisms of varieties of optimization problems and increase the robustness of the algorithm. Typical test functions and inverse problem are solved to testify the effectiveness and efficiency of the proposed method.

Multi-objective Optimization based on the Response Surface Models for the Soft Magnetic Composite Machine

Xiaoyu Liu1, Weinong Fu2, Hui Li1

1Chongqing University, China, People's Republic of; 2The Hong Kong Polytechnic University, Hong Kong

Soft magnetic composite (SMC) materials are especially suitable for developing electrical machines with complex structure and three dimensional (3-D) magnetic flux path. Axial-flux permanent-magnet (PM) machines today are important technology in many applications especially the in-wheel applications. In this work, the multi-objective optimization is applied for the SMC axial-flux PM electric vehicle (EV). The calculation of core loss based on the simulation of the JA model by the moving least-square (MLS) method is employed to investigate the SMC stator core. 3-D magnetic time-stepping field finite element analysis (FEA) is conducted to find the flux density when the rotor rotates. The comparison of the calculated results and the measurement of the prototype verify that the proposed method is accurate for the SMC axial-flux PM motor.

Optimal design of Electric Motor based on Remesh-free Finite-element Method of Magnetic Field and Thermal Field Co-Simulation

Xiaoyu Liu1, Yunpeng Zhang2, Weinong Fu2

1Chongqing University, China, People's Republic of; 2The Hong Kong Polytechnic University, Hong Kong

In this report, the methodology for multi objective optimization problem (MOP) of electric motor has been proposed to reduce the computing time. It employed the overlapping remesh-free finite element method (FEM). It avoids the disadvantage in traditional method that the mesh needs to be rebuilt while large geometrical variations happen during the optimization process. The MOP take the torque density and the temperature-rise versus current as the objective functions of the MOP. These objective functions are modeled by the improved response surface model based on moving least-square algorithm for the load. Experimental results of a prototype are used to validate the proposed optimization algorithm.

Circularly Polarized Antenna Design by Control based Adaptive Differential Evolution

Xiu Zhang1, Xiaohui Lu1, Xin Zhang1, Weinong Fu2, Shuangxia Niu2

1Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission,Tianjin Normal University, China, People's Republic of; 2Department of Electrical Engineering, The Hong Kong Polytechnic University

Antenna designs are commonly modeled as simulation-based optimization problems with multimodal and non-differentiable properties. These properties justify the invention of more effective optimization algorithms. Differential evolution (DE) has already been applied to tackle such design problems. Existing methods do not fully mining control theory for configuration of DE, this paper designs a structure to generate the combinations of algorithmic parameters, mutation and crossover operators. A control based adaptive DE is proposed to assist the finding of potential good solutions. The proposed method is then applied to deal with circularly polarized antenna problems. Simulation results show that the proposed method is more effective and reliable than the compared algorithms. These findings show the usefulness of the method in handling antenna design problems.

A Robust Design Optimization Approach for Electromagnetic Devices Considering Probability Uncertainties

Bo Ma1, Jing Zheng2, Gang Lei1, Jianguo Zhu1,3

1Faculty of Engineering and Information Technology, University of Technology Sydney, NSW 2007, Australia; 2State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, School of Mechanical and Vehicle Engineering, Hunan University, Changsha, China; 3School of Electrical and Information Engineering, University of Sydney, New South Wales, Australia

For the robust optimization problems with probabilistic uncertainties, classical approaches based on Monte Carlo method usually require a huge amount of samples for the robustness estimation of the performance. This paper proposes an efficient robust optimizer based on univariate dimensional reduction method and evolutionary algorithms. The univariate dimensional reduction method is applied for the probabilistic property estimation of the performance functions with significantly reduced sample number. The comparison results of the proposed approach and classical approach based on Monte Carlo method for a numerical example illustrate the feasibility of the presented approach.

A study on the optimal design of BLDC Slot-less PM motor using Response Surface Method

Dong-Hoon Jung1, Jun-Hui Won1, Hyung-Woo Lee2, Chan-Bae Park2, Ho-Joon Lee3, Ju Lee1

1Department of Electrical Engineering, Hanyang University, Seoul 04763, Republic of Korea; 2Department of Railway Vehicle System Engineering, Korea National University of Transportation, Uiwang 16106, Republic of Korea; 3Department of Electric Automatization, Busan Institute of Science Technology University, Busan, 46639, Republic of Korea

Permanent magnet (PM) motors, which are capable of precise control with wide operation range and high power density, are widely used in various industrial fields such as automobile, aerospace, home appliance, defense industry and so on. Especially, because slot-less motor has no teeth and their corresponding slots, it has a variety of electromagnetic and structural advantages compared to the slotted motor. Therefore, the study and development of the slot-less PM motor is actively underway as the servo and driving motor. In this paper, the electromagnetic characteristics of the BLDC slot-less PM motor are analyzed by Finite Elements Analysis (FEA). Furthermore, the optimal design of BLDC slot-less PM motor is conducted with Response Surface Method (RSM) and 3-Dimensional FEA (3-D FEA) to satisfy the requirements of a driving motor of guided weapon: the high torque constant and low rotor inertia. And the effective design method, using the magnetic and electric loading of the BLDC slot-less PM motor considering the electromagnetic characteristics and rotor inertia, is proposed. Finally, the validity of the design method and output characteristics of the BLDC slot-less PM motor is verified through the experimental tests with the prototype.

Sensitivity Analysis for Multi-objective Optimization of the Benchmark TEAM Problem

Minsik Seo, Namhee Ryu, Seungjae Min

Hanyang University, Korea, Republic of (South Korea)

In this paper, design sensitivity is calculated using a gradient-based algorithm for the multi-objective benchmark TEAM problem. The material derivative concept of shape sensitivity analysis is used to derive the parametric design sensitivity. The original objective function is replaced with the p-norm expression to handle the minimax problem. The computed sensitivity is validated with the finite difference. The result shows that the analytical sensitivity agrees well with the numerical one.

Design and Optimization of PM Arrangement for a Dual-Layer-Permanent-Magnet Synchronous Motor

Yiduan Chen, Weinong Fu, Wenjia Yang

The Hong Kong Polytechnic University, Hong Kong S.A.R. (China)

In this paper, different permanent magnet (PM) arrangements of a dual-layer-permanent-magnet (DLPM) synchronous motor are presented. The configurations of the PM arrangement in the motors are designed in general patterns and optimized by a multi-objective genetic algorithm. The magnetic fields of the DLPM motors with different PM arrangements are analyzed coupling with mechanical motion using finite element method (FEM) and the respective performances are quantitatively compared, including the torque density, losses, harmonic spectra and corresponding power efficiency. The results show that the DLPM motor with the optimal PM arrangement has 48% higher torque capability and 3.2% higher power efficiency compared with a motor with a conventional PM arrangement, which validates that the optimization method for the PM arrangement provides an effective design approach of PM machines.

Multi-objective optimization of contactors based on the improved nondominated sorting genetic algorithm III

Wenying Yang, Jiuwei Guo, Yang Liu, Guofu Zhai

School of Electrial Engineering and Automation,Harbin Institute of Technology, China, People's Republic of

Contactors are typical electromagnetic devices. The optimization of contactors is typical multi-objective optimization problems which usually contain more than two objectives. But with the increment of the number of objectives, it will cause the worse diversity of the optimal solution set and decrease the convergence speed of the optimization algorithm, especially for the traditional algorithms. To solve the above problems, an evolutionary multi-objective optimization (EMO) algorithm based on nondominated sorting, reference points and differential evolution (DE) is proposed in this paper. The novel algorithm can fast converge to the optimal solution set with good diversity. Meanwhile, a method based on fuzzy membership is also proposed to select the compromise solution in the paper. Compared to traditional algorithms such as the nondominated sorting genetic algorithm II(NSGAII) and multi-objective particle swarm optimization algorithms (MOPSO), the diversity of optimal solution set obtained by the novel algorithm is significantly better than that obtained by traditional algorithms.