{"title":"电动动力系统概念设计的尺寸和效率模型","authors":"Farid Saemi, Moble Benedict","doi":"10.1109/TPEC56611.2023.10078514","DOIUrl":null,"url":null,"abstract":"Small electric aircraft (“drones”) have become common tools in a range of industries. However, engineers do not have the right tools to analyze a drone’s electric powertrain at the conceptual design stage. Aerospace literature describes empirical methods which require costly experimental data, and electrical literature describes computational tools which rely on design details which are unknown at the early design process. We have developed physics-based models that can predict the size and efficiency of drone motors, inverters/controllers, and batteries using readily-available information. We have tuned and validated the models against parametric experimental studies on a dynamometer and propeller test stand. We expect the models to help engineers develop better drone concepts more quickly.","PeriodicalId":183284,"journal":{"name":"2023 IEEE Texas Power and Energy Conference (TPEC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sizing and efficiency models for the conceptual design of electric powertrains\",\"authors\":\"Farid Saemi, Moble Benedict\",\"doi\":\"10.1109/TPEC56611.2023.10078514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Small electric aircraft (“drones”) have become common tools in a range of industries. However, engineers do not have the right tools to analyze a drone’s electric powertrain at the conceptual design stage. Aerospace literature describes empirical methods which require costly experimental data, and electrical literature describes computational tools which rely on design details which are unknown at the early design process. We have developed physics-based models that can predict the size and efficiency of drone motors, inverters/controllers, and batteries using readily-available information. We have tuned and validated the models against parametric experimental studies on a dynamometer and propeller test stand. We expect the models to help engineers develop better drone concepts more quickly.\",\"PeriodicalId\":183284,\"journal\":{\"name\":\"2023 IEEE Texas Power and Energy Conference (TPEC)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Texas Power and Energy Conference (TPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TPEC56611.2023.10078514\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Texas Power and Energy Conference (TPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TPEC56611.2023.10078514","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sizing and efficiency models for the conceptual design of electric powertrains
Small electric aircraft (“drones”) have become common tools in a range of industries. However, engineers do not have the right tools to analyze a drone’s electric powertrain at the conceptual design stage. Aerospace literature describes empirical methods which require costly experimental data, and electrical literature describes computational tools which rely on design details which are unknown at the early design process. We have developed physics-based models that can predict the size and efficiency of drone motors, inverters/controllers, and batteries using readily-available information. We have tuned and validated the models against parametric experimental studies on a dynamometer and propeller test stand. We expect the models to help engineers develop better drone concepts more quickly.