{"id":26160113,"url":"https://github.com/otvam/magnet_webinar_eqn_models","last_synced_at":"2026-03-10T16:18:38.454Z","repository":{"id":164272508,"uuid":"635013279","full_name":"otvam/magnet_webinar_eqn_models","owner":"otvam","description":"2023 MagNet Challenge Webinar: Equation-based Baseline Models","archived":false,"fork":false,"pushed_at":"2025-03-28T14:54:42.000Z","size":7815,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-07-17T04:08:07.079Z","etag":null,"topics":["core","ferrite","ieee","igcc","igse","loss","magnet","pels","power-electronics"],"latest_commit_sha":null,"homepage":"","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/otvam.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2023-05-01T19:13:14.000Z","updated_at":"2025-03-28T14:54:45.000Z","dependencies_parsed_at":"2025-07-16T08:17:40.951Z","dependency_job_id":"de222808-505e-46ac-95f8-41054d84c718","html_url":"https://github.com/otvam/magnet_webinar_eqn_models","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/otvam/magnet_webinar_eqn_models","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/otvam%2Fmagnet_webinar_eqn_models","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/otvam%2Fmagnet_webinar_eqn_models/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/otvam%2Fmagnet_webinar_eqn_models/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/otvam%2Fmagnet_webinar_eqn_models/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/otvam","download_url":"https://codeload.github.com/otvam/magnet_webinar_eqn_models/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/otvam%2Fmagnet_webinar_eqn_models/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30342165,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-10T15:55:29.454Z","status":"ssl_error","status_checked_at":"2026-03-10T15:54:58.440Z","response_time":106,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["core","ferrite","ieee","igcc","igse","loss","magnet","pels","power-electronics"],"created_at":"2025-03-11T11:59:56.369Z","updated_at":"2026-03-10T16:18:38.436Z","avatar_url":"https://github.com/otvam.png","language":"MATLAB","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MagNet: Equation-based Baseline Models\n\n## Introduction\n\nThis repository contains the **slides** and **code** related to the following **webinar**:\n* **2023 MagNet Challenge Webinar: Equation-based Baseline Models**\n* **IEEE PELS Webinar - May 12 2023**\n* **Thomas Guillod - Dartmouth College**\n\nThe **webinar** is based on the following **paper**:\n* **Calculation of Ferrite Core Losses with Arbitrary Waveforms using the Composite Waveform Hypothesis**\n* **Thomas Guillod, Jenna S. Lee, Haoran Li, Shukai Wang, Minjie Chen, and Charles R. Sullivan**\n* **https://doi.org/10.1109/APEC43580.2023.10131348**\n* **IEEE APEC 2023**\n\nThis webinar focuses on **equation-based loss models for soft-magnetic materials**:\n* Several models are presented (SE, iGSE, iGCC, and Stenglein equation).\n* The model performances are evaluated for different frequencies, waveshapes, and temperatures.\n* The advantages and drawbacks of equation-based models and machine learning models are discussed.\n* A MATLAB implementation of the iGSE and iGCC is discussed in detail and the pitfalls are highlighted.\n\n## Main Files\n\n* [slides.pdf](slides.pdf) - Slides of the webinar (CC BY-ND 4.0)\n* [paper.pdf](paper.pdf) - APEC 2023 paper (IEEE copyright)\n* [run_igse.m](run_igse.m) - Parametrize and evaluate the iGSE model\n* [run_igcc.m](run_igcc.m) - Parametrize and evaluate the iGCC model\n\n## Dataset\n\n* For the software implementation, the EPCOS/TDK N87 ferrite material is considered.\n* The material is measured at ambient temperature (25C) without DC bias.\n* For parametrizing the models, the following dataset is used:\n    * 346 symmetric triangular waveforms (50% duty cycle)\n    * Dataset contained in [N87_25C_fit.mat](data/N87_25C_fit.mat)\n* For evaluating the models, the following dataset is used:\n    * 2446 asymmetric triangular waveforms (10% to 90% duty cycle)\n    * Dataset contained in [N87_25C_eval.mat](data/N87_25C_eval.mat)\n* Both datasets are extracted from the following repository:\n    * Guillod, T. and Lee, J. S. and Li, H. and Wang, S. and Chen, M. and Sullivan, C. R.\n    * Calculation of Ferrite Core Losses with Arbitrary Waveforms using the Composite Waveform Hypothesis: Reproducibility Dataset\n    * Zenodo Repository, 2022\n    * [10.5281/zenodo.7368936](https://doi.org/10.5281/zenodo.7368936)\n\n## Warnings\n\n\u003e **Warning**\n\u003e This implementation is provided for **pedagogical purposes**:\n\u003e * The goal of this code is to highlight the **typical workflow** of equation-based loss models.\n\u003e * The implementation is **not meant** to be **comprehensive and/or accurate**.\n\n\u003e **Warning**\n\u003e In order to limit the complexity of the code, **several assumptions** are made:\n\u003e * Single material measured at ambient temperature\n\u003e * Only triangular signals are considered\n\u003e * No DC bias and relaxation effects\n\u003e * Simple model parametrization\n\u003e * Reduced dataset size\n\n## Compatibility\n\n* Tested with MATLAB R2021a and R2023a.\n* The `optimization_toolbox` is required.\n* The `signal_toolbox` is required.\n* The `statistics_toolbox` is required.\n\n## Author\n\n**Thomas Guillod, Dartmouth College** - [GitHub Profile](https://github.com/otvam)\n\n## License\n\nThis project is licensed under the **MIT License**, see [LICENSE.md](LICENSE.md).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fotvam%2Fmagnet_webinar_eqn_models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fotvam%2Fmagnet_webinar_eqn_models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fotvam%2Fmagnet_webinar_eqn_models/lists"}