{"title":"The Effect of Optimal Vehicle Velocity Trajectory and Optimal Hybrid Energy Storage on Electric Vehicle Energy Consumption","authors":"Waiard Saikong, T. Kulworawanichpong","doi":"10.1109/RI2C48728.2019.8999922","DOIUrl":null,"url":null,"abstract":"This article proposed a method to increase effectiveness of energy consumption and presented comparison of effects of energy and power consumption from algorithms to investigate optimal velocity trajectory under the condition of late arrival, algorithms to investigate optimal hybrid energy storage system, and cases that collaborated both algorithms. The testing was on the route New York City Cycle - NYCC and route SUT - Suranaree University of Technology Route. The real field measurement was used to find load profile for SUT route. Both were urban traffic routes. The researcher created a mathematic model and tested for optimal velocity trajectory and optimal hybrid energy storage system using particle swarm optimization: PSO methodology. The test revealed that the algorithm to investigate optimal velocity trajectory under the condition of delayed arrival together with the algorithm to investigate optimal hybrid energy storage system - HESS can reduce energy consumption and maximum peak power at most which was at 46.653% and 60.543% respectively on NYCC route and can reduce energy consumption at 21.435% and reduce maximum power at 23.973% on SUT route.","PeriodicalId":404700,"journal":{"name":"2019 Research, Invention, and Innovation Congress (RI2C)","volume":"854 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Research, Invention, and Innovation Congress (RI2C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RI2C48728.2019.8999922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article proposed a method to increase effectiveness of energy consumption and presented comparison of effects of energy and power consumption from algorithms to investigate optimal velocity trajectory under the condition of late arrival, algorithms to investigate optimal hybrid energy storage system, and cases that collaborated both algorithms. The testing was on the route New York City Cycle - NYCC and route SUT - Suranaree University of Technology Route. The real field measurement was used to find load profile for SUT route. Both were urban traffic routes. The researcher created a mathematic model and tested for optimal velocity trajectory and optimal hybrid energy storage system using particle swarm optimization: PSO methodology. The test revealed that the algorithm to investigate optimal velocity trajectory under the condition of delayed arrival together with the algorithm to investigate optimal hybrid energy storage system - HESS can reduce energy consumption and maximum peak power at most which was at 46.653% and 60.543% respectively on NYCC route and can reduce energy consumption at 21.435% and reduce maximum power at 23.973% on SUT route.