ironloss_prediction_of_IPMSM_by_XGBoost

Python implementation for iron loss prediction of interior permanent magnet synchronous motors by XGBoost (paper)

Overview

This library contains an implementation of an automatic design system for interior permanent magnet synchronous motors as presented in [1]

Dependencies

• python>=3.8
• numpy
• pandas
• sklearn>=0.24.2
• xgboost>=1.6.1
• optuna>=2.10.1

Architecture

data: You can download the dataset used for the paper here or here.
regression: A characteristics prediction model is implemented.

Feedback

For questions and comments, feel free to contact Yuki Shimizu.

License

MIT

Citation

[1] Y. Shimizu, “Efficiency Optimization Design that Considers Control 
of Interior Permanent Magnet Synchronous Motors based on Machine Learning 
for Automotive Application,” IEEE Access, Vol. 11, pp. 41-49, 2023.