Joon Moon;Muhammad Qaisar Fahim;Hamza Anwar;Qadeer Ahmed
{"title":"电动汽车充电路径的能量与时间优化","authors":"Joon Moon;Muhammad Qaisar Fahim;Hamza Anwar;Qadeer Ahmed","doi":"10.1109/TTE.2025.3532826","DOIUrl":null,"url":null,"abstract":"This article investigates energy-efficient, charging-aware route planning for battery electric vehicles (BEVs) while accounting for uncertainties in charging station availability and time-varying traffic conditions. The study focuses on integrating recharge scheduling into route planning, addressing challenges such as limited charging infrastructure, intermittent access, and temporal factors like charger waiting times based on availability, charging durations, and fluctuating traffic conditions. A time-aware charging selection algorithm is introduced to adjust schedules based on operating costs and time components, such as traffic-dependent travel times, waiting times, and charging times. The case study shows that time-adaptive recharging planning increases energy consumption by 1.6%, while reducing travel time by 12% and costs by 14% compared to the baseline, which does not account for temporal impacts. Additionally, it provides insights into the preferences and timing factors in charging station selection that contribute to these differences. The findings highlight the importance of considering time factors such as waiting and recharging times in the planning of electric vehicle (EV) operations.","PeriodicalId":56269,"journal":{"name":"IEEE Transactions on Transportation Electrification","volume":"11 3","pages":"7823-7832"},"PeriodicalIF":8.3000,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing Energy and Time for Electric Vehicle Charging Routes\",\"authors\":\"Joon Moon;Muhammad Qaisar Fahim;Hamza Anwar;Qadeer Ahmed\",\"doi\":\"10.1109/TTE.2025.3532826\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article investigates energy-efficient, charging-aware route planning for battery electric vehicles (BEVs) while accounting for uncertainties in charging station availability and time-varying traffic conditions. The study focuses on integrating recharge scheduling into route planning, addressing challenges such as limited charging infrastructure, intermittent access, and temporal factors like charger waiting times based on availability, charging durations, and fluctuating traffic conditions. A time-aware charging selection algorithm is introduced to adjust schedules based on operating costs and time components, such as traffic-dependent travel times, waiting times, and charging times. The case study shows that time-adaptive recharging planning increases energy consumption by 1.6%, while reducing travel time by 12% and costs by 14% compared to the baseline, which does not account for temporal impacts. Additionally, it provides insights into the preferences and timing factors in charging station selection that contribute to these differences. The findings highlight the importance of considering time factors such as waiting and recharging times in the planning of electric vehicle (EV) operations.\",\"PeriodicalId\":56269,\"journal\":{\"name\":\"IEEE Transactions on Transportation Electrification\",\"volume\":\"11 3\",\"pages\":\"7823-7832\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2025-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Transportation Electrification\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10849817/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Transportation Electrification","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10849817/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Optimizing Energy and Time for Electric Vehicle Charging Routes
This article investigates energy-efficient, charging-aware route planning for battery electric vehicles (BEVs) while accounting for uncertainties in charging station availability and time-varying traffic conditions. The study focuses on integrating recharge scheduling into route planning, addressing challenges such as limited charging infrastructure, intermittent access, and temporal factors like charger waiting times based on availability, charging durations, and fluctuating traffic conditions. A time-aware charging selection algorithm is introduced to adjust schedules based on operating costs and time components, such as traffic-dependent travel times, waiting times, and charging times. The case study shows that time-adaptive recharging planning increases energy consumption by 1.6%, while reducing travel time by 12% and costs by 14% compared to the baseline, which does not account for temporal impacts. Additionally, it provides insights into the preferences and timing factors in charging station selection that contribute to these differences. The findings highlight the importance of considering time factors such as waiting and recharging times in the planning of electric vehicle (EV) operations.
期刊介绍:
IEEE Transactions on Transportation Electrification is focused on components, sub-systems, systems, standards, and grid interface technologies related to power and energy conversion, propulsion, and actuation for all types of electrified vehicles including on-road, off-road, off-highway, and rail vehicles, airplanes, and ships.