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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

Session

OC2: AI and machine learning technologies

Time:

Thursday, 25/May/2023:

3:40pm - 5:20pm

Session Chair: Prof. Oszkar Biro, Budapest University of Technology and Economics, Hungary
Session Chair: Prof. Zhuoxiang Ren, Sorbonne University, France

Presentations

3:40pm - 4:00pm
ID: 359 / OC2: 1
Topics: Static and Quasi-Static Fields, AI and Machine Learning Technologies
Keywords: Deep learning, surrogate model, finite element analysis, magneto-thermal analysis, TEAM Problem

Predicting Transient Thermal Maps via a DNN Method for Solving TEAM Workshop Problem 36

Paolo Di Barba¹, Maria Evelina Mognaschi¹, Anna Maria Cavazzini², Matteo Ciofani², Fabrizio Dughiero², Michele Forzan², Matteo Lazzarin², David Alister Lowther³, Jan K. Sykulski⁴

¹University of Pavia, Italy; ²University of Padova, Italy; ³McGill University, Montreal, Canada; ⁴University of Southampton, Southampton, UK

4:00pm - 4:20pm
ID: 449 / OC2: 2
Topics: Optimization and Design, AI and Machine Learning Technologies
Keywords: Interior Permanent Magnet Synchronous Motor, Shapley Additive Explanations, Topology optimization

Topology Optimization of Permanent Magnet Synchronous Motor with Shapley Additive Explanations

Hidenori Sasaki, Koichi Yamamura

Hosei University, Japan

4:20pm - 4:40pm
ID: 379 / OC2: 3
Topics: AI and Machine Learning Technologies
Keywords: Convolutional neural network, design optimization, iron loss, permanent magnet motor, transformer.

Investigation of Iron Loss Prediction Model for Automatic Design System of IPMSMs

Yuki Shimizu

Ritsumeikan University, Japan

4:40pm - 5:00pm
ID: 424 / OC2: 4
Topics: Material Modelling
Keywords: Magnetic Hysteresis, Magnetic Materials, Neural Networks, Deep Learning

The Application of Neural Networks to the Computation of Magnetic Hysteresis

Niilo Vuokila, Christos Cunning, Jayson Zhang, Nader Akel, Arbaaz Khan, David Lowther

McGill University, Canada

5:00pm - 5:20pm
ID: 300 / OC2: 5
Topics: Optimization and Design, Novel Computational Methods for Machines and Devices, AI and Machine Learning Technologies
Keywords: Deep Learning, Surrogate Model, Finite Element Analysis, Electrical Motors

Comparison of Learning-based Surrogate Models for Electric Motors

Yihao Xu^1,2, Bingnan Wang¹, Yusuke Sakamoto^1,3, Tatsuya Yamamoto³, Yuki Nishimura³

¹Mitsubishi Electric Research Laboratories, United States of America; ²Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02120 USA; ³Advanced Technology R&D Center, Mitsubishi Electric Corporation, Amagasaki, Hyogo 661-8661 Japan