Yoshitsugu Otomo

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Assistant professor

Nagasaki University

Japan

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Yoshitsugu Otomo is an Assistant Professor at Nagasaki University, Japan. His research focuses on topology optimization, wireless power transfer devices, and motor design, as evidenced by his recent publications on torque ripple reduction and the design of permanent magnet motors. He employs advanced techniques such as Monte Carlo tree search and surrogate modeling to enhance the efficiency and performance of electrical systems.

Recent Grants

Grant: Close

JSPS KAKENHI JP23K13312

Open Date: 2023-04-01

Close Date: 2026-03-01

Grant: Close

JSPS KAKENHI JP22K20431

Open Date: 2022-08-01

Close Date: 2024-03-01

Grant: Close

JSPS KAKENHI JP21H01315

Open Date: 2021-04-01

Close Date: 2024-03-01

Grant: Close

JSPS KAKENHI JP19J20375

Open Date: 2019-04-01

Close Date: 2022-03-01

Yoshitsugu Otomo

Research Interests

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About

Recent Grants

Articles (20)

Factors for Reducing Torque Ripple in a Topology-Optimized Shape of SynRM Considering Multiple Driving Points

Topology optimization of asymmetric Interior permanent magnet motors using Gaussian basis function

Topology optimization of permanent magnet motors using Gabor filter

Monte Carlo tree search applied to design of wireless power transfer system

Design and Improvement of Torque Characteristics of Half-Wave Rectified Variable Field Flux Motor with Axal Gap Structure

Parameter and Topology Optimizations for Wireless Power Transfer Device Considering Magnetic and Circuit Properties

Surrogate Modeling and Application of Half-Wave Rectified Brushless Synchronous Motor for Model-Based Design

Optimal Design Method for Wireless Power Transfer Devices Considering Magnetic and Electronic Circuits

Design and improvement of torque characteristics of half‐wave rectified variable field flux motor with axial gap structure

Equivalent circuit of high frequency inductor to consider eddy currents and resonance

Reduced Order Modeling of Half-Wave Rectified Brushless Synchronous Motor for Model-Based Design

2.5-D Multi-Phase Topology Optimization of Permanent Magnet Motor Using Gaussian Basis Function

Neural Network for Both Metal Object Detection and Coil Misalignment Prediction in Wireless Power Transfer

Prediction of Current-Dependent Motor Torque Characteristics Using Deep Learning for Topology Optimization

Sensorless metal object detection for wireless power transfer using machine learning

Topology optimization of magnetic cores for WPT using the geometry projection method

Machine Learning Based Metal Object Detection for Wireless Power Transfer Using Differential Coils

Analysis of Litz Wire Losses Using Homogenization-Based FEM

Topology Optimization Using Gabor Filter: Application to Synchronous Reluctance Motor

Synthesis of a Cauer Equivalent Circuit for Electric Devices From Computed and Measured Data

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