Researcher Database

（Last updated : 2024-02-02 12:38:33）

SHIMIZU YUKI

Department / Course College of Science and Engineering Department of Electrical and Electronic Engineering

Title / Position Assistant Professor

Other Affiliations
1.	Graduate School of Science and Engineering

Academic background
1.	2020/04～2022/03	Division of Electrical Engineering and Information Science │ Graduate School of Engineering │ Osaka Prefecture University
2.	2016/04～2018/03	Division of Electrical Engineering and Information Science │ Graduate School of Engineering │ Osaka Prefecture University

Business career
1.		│ College of Science and Engineering, Department of Electrical and Electronic Engineering │ Ritsumeikan University
2.	2022/04 ～	│ College of Science and Engineering, Department of Electrical and Electronic Engineering │ Ritsumeikan University
3.	2021/04 ～ 2022/03	│ │ Osaka Institute of Technology
4.	2018/04 ～ 2020/03	│ │ Toyota Motor Corporation

Subject of research
1.	Online Parameter Identification of Permanent Magnet Synchronous Motors
2.	Shape Optimization of Permanent Magnet Synchronous Motors Using Machine Learning

Research summary
Shape Optimization of Permanent Magnet Synchronous Motors Using Machine Learning In recent years, various products have been electrically driven due to environmental concerns, and motors, which convert electrical energy into mechanical energy, are used as their power source. Currently, interior permanent magnet synchronous motors (IPMSMs) are widely adopted (Fig. 1). IPMSMs have a high degree of freedom, and their design requires a time-intensive finite element analysis. Thus, IPMSMs face the problem of a long development period. This study proposes an automatic design system that can efficiently design IPMSMs in a short time by using machine learning to model the nonlinear relationship between motor shape and driving characteristics. I would like to complete this research and contribute to the further development of the motor industry from the viewpoint of shortening the development period. Due to intensifying international competition, the manufacturing industry has been forced to complete product development in less than half the time of the past while maintaining product performance and reliability. Given this situation, this research will lead to the creation of innovation in the motor industry, and will have a tremendous impact on the industry, especially in terms of shortening the development period. In the future, it will be necessary to examine aspects such as safety, reliability, and cost, in addition to performance, to put AI technology to practical use in the design field of companies. Therefore, we would like to contribute to the further development of the industry as a whole by working closely with companies to solve these issues and put AI technology to practical use based on the results of this research on motor performance.

Present specialized field
Synchronous motor, Power electronics, Machine learning, Deep learning

Papers
1.	2023/09/04	Comparison of SS and SP Circuit Topologies for Wireless Power Transfer Systems Capable of Bi-directional Power Transmission │ Proc. of the 2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe) │ (Co-authored)
2.	2023/09/04	Design and Experimental Verification of SP-Type Resonant Wireless Power Transfer System Capable for Bidirectional Power Transmission │ Proc. of the 2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe) │ (Co-authored)
3.	2023/08/01	Investigation of Rotor Topologies for Reducing Torque Ripple in Double-Layer IPMSMs for Automotive Applications │ IEEE Transactions on Industrial Electronics │ 70 (8),pp.8276-8285 (Co-authored)
4.	2023/05/01	Maximum Torque per Ampere Control of IPMSM Using Online Flux Linkage Plane Estimation Considering Cross Saturation │ IEEJ Journal of Industry Applications │ 12 (3),pp.319-325 (Co-authored)
5.	2023/05	Investigation of Iron Loss Prediction Model for Automatic Design System of IPMSMs │ Proc. of the COMPUMAG2023 │ (Sole-authored)
Display All（17）

Winning science prize
1.	2021/08	IEEJ Industry Applications Society Excellent Presentation Award (Reducing Design Time of Permanent Magnet Volume Minimization for IPMSM for Automotive Applications Using Machine Learning)

Message
1.	Leave yourself to curiosity I am studying the application of artificial intelligence to the field of electrical systems such as motors and power circuits. Originally an engineer in the field of electrical systems, I was involved in a variety of tasks such as motor design and analysis, battery design, and control. From the first half to the second half of the 2010s, the advent of deep learning technology led to the rapid development of the field of artificial intelligence, and many attractive technologies were born. I was one of those who was fascinated by that technology, especially the technology that "artificial intelligence creates" called the deep generative model. And, out of curiosity that I absolutely wanted to use that technology, I started researching artificial intelligence that creates motor designs. Thus, my strong curiosity is the driving force behind my actions, and when deciding the direction of my research, I always asks myself, "Is it exciting?" I would like to leave my curiosity to myself and continue my research with a lot of fun.

Department laboratory expense researcher number
10962532

researchmap Researcher code
R000012563

External Researcher ID
ORCID ID

Researcher ID