{"title":"基于粒子群算法的电动汽车驱动路径优化","authors":"George Onoja Idoko","doi":"10.1109/ATEE58038.2023.10108264","DOIUrl":null,"url":null,"abstract":"This paper presents a viable solution to range anxiety experienced by drivers of electric cars. It describes and shows the application of metaheuristics in pathfinding optimization. Particle swarm optimization, which is a metaheuristic optimization method, is used to optimize a travel path for electric vehicles between Bucharest and Cluj-Napoca. The travel path links the driver to the electric vehicle charging stations on their path.","PeriodicalId":398894,"journal":{"name":"2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drive Path Optimization for Electric Vehicles Using Particle Swarm Optimization\",\"authors\":\"George Onoja Idoko\",\"doi\":\"10.1109/ATEE58038.2023.10108264\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a viable solution to range anxiety experienced by drivers of electric cars. It describes and shows the application of metaheuristics in pathfinding optimization. Particle swarm optimization, which is a metaheuristic optimization method, is used to optimize a travel path for electric vehicles between Bucharest and Cluj-Napoca. The travel path links the driver to the electric vehicle charging stations on their path.\",\"PeriodicalId\":398894,\"journal\":{\"name\":\"2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATEE58038.2023.10108264\",\"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 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATEE58038.2023.10108264","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drive Path Optimization for Electric Vehicles Using Particle Swarm Optimization
This paper presents a viable solution to range anxiety experienced by drivers of electric cars. It describes and shows the application of metaheuristics in pathfinding optimization. Particle swarm optimization, which is a metaheuristic optimization method, is used to optimize a travel path for electric vehicles between Bucharest and Cluj-Napoca. The travel path links the driver to the electric vehicle charging stations on their path.
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