{"title":"基于神经进化的混合动力变速器换挡点优化","authors":"J. Bower, Masood Shahverdi, David I. Blekhman","doi":"10.1109/SUSTECH.2018.8671374","DOIUrl":null,"url":null,"abstract":"In a hybrid vehicle the speeds at which the transmission shifts between gears has a large impact on energy consumption. Dynamic Programming (DP) can be used to find the optimal transmission gear for a given torque and speed. Neuroevolution of Augmenting Topologies (NEAT) is then utilized to find the shift lines which allow the transmission to be at the most energy efficient point in an implementable way. Through this strategy, an improvement of 7% was achieved compared to the traditional approach.","PeriodicalId":127111,"journal":{"name":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Neuroevolution Based Optimization of Hybrid Transmission Shift Points\",\"authors\":\"J. Bower, Masood Shahverdi, David I. Blekhman\",\"doi\":\"10.1109/SUSTECH.2018.8671374\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a hybrid vehicle the speeds at which the transmission shifts between gears has a large impact on energy consumption. Dynamic Programming (DP) can be used to find the optimal transmission gear for a given torque and speed. Neuroevolution of Augmenting Topologies (NEAT) is then utilized to find the shift lines which allow the transmission to be at the most energy efficient point in an implementable way. Through this strategy, an improvement of 7% was achieved compared to the traditional approach.\",\"PeriodicalId\":127111,\"journal\":{\"name\":\"2018 IEEE Conference on Technologies for Sustainability (SusTech)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Conference on Technologies for Sustainability (SusTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SUSTECH.2018.8671374\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SUSTECH.2018.8671374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neuroevolution Based Optimization of Hybrid Transmission Shift Points
In a hybrid vehicle the speeds at which the transmission shifts between gears has a large impact on energy consumption. Dynamic Programming (DP) can be used to find the optimal transmission gear for a given torque and speed. Neuroevolution of Augmenting Topologies (NEAT) is then utilized to find the shift lines which allow the transmission to be at the most energy efficient point in an implementable way. Through this strategy, an improvement of 7% was achieved compared to the traditional approach.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
