Topology Optimization of Electric Machines: A Review

被引:18
作者
Nishanth, F. N. U. [1 ]
Wang, Bingnan [2 ]
机构
[1] Univ Wiconsin Madison, Dept Elect & Comp Engn, Madison, WI 53706 USA
[2] Mitsubishi Elect Res Labs MERL, 201 Broadway, Cambridge, MA 02139 USA
来源
2022 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE) | 2022年
关键词
Topology optimization; electric machine optimization; electric machines; RELUCTANCE MOTORS; DESIGN; TORQUE;
D O I
10.1109/ECCE50734.2022.9948073
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The development of high performance and power dense electric machines invariably requires exploration of the design space to identify promising designs. Conventional electric machine design optimization techniques aim at identifying optimal values for parameterized geometric variables by varying them within a specified range using an optimization algorithm. However, such approaches are limited by the parameterization which is typically determined by manufacturing constraints and the experience of the designer. Optimizing electric machine performance by using the material distribution as a design handle is known as topology optimization. This approach is enabled by the recent advances in additively manufactured metals that allow manufacturing complex geometries. While the application of topology optimization to structural mechanics has been widely studied, its application to identify optimal electric machine designs is an emerging area of research. In this paper, the state-of-the-art in topology optimization of electric machines is reviewed. First, the need for topology optimization is described, and the benefits and challenges of this technique over the conventional parametric optimization are identified. Next, the different topology optimization techniques reported in literature are described and their relative merits are discussed. Finally, a research outlook is provided for this technology.
引用
收藏
页数:8
相关论文
共 65 条
[21]   Multimaterial Magneto-Structural Topology Optimization of Wound Field Synchronous Machine Rotors [J].
Guo, Feng ;
Salameh, Mohamad ;
Krishnamurthy, Mahesh ;
Brown, Ian P. .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2020, 56 (04) :3656-3667
[22]   Topology Optimization Method Based on On-Off Method and Level Set Approach [J].
Hidaka, Yuki ;
Sato, Takahiro ;
Igarashi, Hajime .
IEEE TRANSACTIONS ON MAGNETICS, 2014, 50 (02) :617-620
[23]   Novel Hybridization of Parameter and Topology Optimizations: Application to Permanent Magnet Motor [J].
Hiruma, Shingo ;
Ohtani, Makoto ;
Soma, Shingo ;
Kubota, Yoshihisa ;
Igarashi, Hajime .
IEEE TRANSACTIONS ON MAGNETICS, 2021, 57 (07)
[24]   A further review of ESO type methods for topology optimization [J].
Huang, Xiaodong ;
Xie, Yi-Min .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2010, 41 (05) :671-683
[25]   Topology optimized and 3D printed polymer-bonded permanent magnets for a predefined external field [J].
Huber, C. ;
Abert, C. ;
Bruckner, F. ;
Pfaff, C. ;
Kriwet, J. ;
Groenefeld, M. ;
Teliban, I. ;
Vogler, C. ;
Suess, D. .
JOURNAL OF APPLIED PHYSICS, 2017, 122 (05)
[26]  
Khan A., 2022, IEEE T MAGNETICS
[27]   Topology Optimization of Rotor in Synchronous Reluctance Motor Using Level Set Method and Shape Design Sensitivity [J].
Kim, Young Sun ;
Park, Il Han .
IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2010, 20 (03) :1093-1096
[28]   On the Use of Topology Optimization for Synchronous Reluctance Machines Design [J].
Korman, Oguz ;
Di Nardo, Mauro ;
Degano, Michele ;
Gerada, Chris .
ENERGIES, 2022, 15 (10)
[29]  
Kuci E., 2021, STRUCTURAL MULTIDISC, P1
[30]   Additive manufacturing of soft magnets for electrical machines - a review [J].
Lamichhane, T. N. ;
Sethuraman, L. ;
Dalagan, A. ;
Wang, H. ;
Keller, J. ;
Paranthaman, M. P. .
MATERIALS TODAY PHYSICS, 2020, 15