{"title":"操作和环境对电池寿命和车辆性能的影响:电动出租车的案例研究","authors":"Zisis Lampropoulos , Spyridon Spyridopoulos , Traianos Karageorgiou , Grigorios Koltsakis","doi":"10.1016/j.nxener.2025.100441","DOIUrl":null,"url":null,"abstract":"<div><div>The gradual electrification of the road transport sector has raised a lot of concerns about the reliability of battery electric vehicles (BEVs). Many potential customers not only lack awareness about the benefits of electrification, total costs and charging infrastructure, but are especially worried about battery lifetime and vehicle performance, information which manufacturers often struggle to provide accurately. This work proposes a methodology to predict BEV lifetime based on complete vehicle simulation employing a physics-based, electrochemical-thermal-aging battery model. In addition, the model calculates the performance degradation over time in terms of energy consumption, range, battery charging efficiency and vehicle acceleration. Physics-based models are harder to develop and computationally costlier than data-driven models. However, once developed, they can be used in a much broader range of conditions and, more importantly, be applied also when no adequate on-road data are yet available. The proposed methodology is applied in a case study of BEV taxis in the city of Thessaloniki, Greece. In particular, the impact of battery preheating prior to charging is evaluated by simulation, showing that preheating could increase lifetime and mileage of BEV taxis by 14% in South European climates. In another application, it is calculated that mid-shift fast-charging could even double the life of the battery compared to fast-charging only before shift change, leading simultaneously to improved performance when compared within the same operational period. Such results could support battery and vehicle manufacturers as well as fleet managers to guide BEV taxi owners towards optimal charging behavior. The modeling approach presented in this paper can be further extended to other vehicle groups, environmental, driving and charging conditions, making it a powerful tool not only for manufacturers, but also for policymakers and charging infrastructure companies.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"9 ","pages":"Article 100441"},"PeriodicalIF":0.0000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Operational and environmental impacts on battery lifetime and vehicle performance: A case study for electric taxis\",\"authors\":\"Zisis Lampropoulos , Spyridon Spyridopoulos , Traianos Karageorgiou , Grigorios Koltsakis\",\"doi\":\"10.1016/j.nxener.2025.100441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The gradual electrification of the road transport sector has raised a lot of concerns about the reliability of battery electric vehicles (BEVs). Many potential customers not only lack awareness about the benefits of electrification, total costs and charging infrastructure, but are especially worried about battery lifetime and vehicle performance, information which manufacturers often struggle to provide accurately. This work proposes a methodology to predict BEV lifetime based on complete vehicle simulation employing a physics-based, electrochemical-thermal-aging battery model. In addition, the model calculates the performance degradation over time in terms of energy consumption, range, battery charging efficiency and vehicle acceleration. Physics-based models are harder to develop and computationally costlier than data-driven models. However, once developed, they can be used in a much broader range of conditions and, more importantly, be applied also when no adequate on-road data are yet available. The proposed methodology is applied in a case study of BEV taxis in the city of Thessaloniki, Greece. In particular, the impact of battery preheating prior to charging is evaluated by simulation, showing that preheating could increase lifetime and mileage of BEV taxis by 14% in South European climates. In another application, it is calculated that mid-shift fast-charging could even double the life of the battery compared to fast-charging only before shift change, leading simultaneously to improved performance when compared within the same operational period. Such results could support battery and vehicle manufacturers as well as fleet managers to guide BEV taxi owners towards optimal charging behavior. The modeling approach presented in this paper can be further extended to other vehicle groups, environmental, driving and charging conditions, making it a powerful tool not only for manufacturers, but also for policymakers and charging infrastructure companies.</div></div>\",\"PeriodicalId\":100957,\"journal\":{\"name\":\"Next Energy\",\"volume\":\"9 \",\"pages\":\"Article 100441\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Next Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949821X25002042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Next Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949821X25002042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Operational and environmental impacts on battery lifetime and vehicle performance: A case study for electric taxis
The gradual electrification of the road transport sector has raised a lot of concerns about the reliability of battery electric vehicles (BEVs). Many potential customers not only lack awareness about the benefits of electrification, total costs and charging infrastructure, but are especially worried about battery lifetime and vehicle performance, information which manufacturers often struggle to provide accurately. This work proposes a methodology to predict BEV lifetime based on complete vehicle simulation employing a physics-based, electrochemical-thermal-aging battery model. In addition, the model calculates the performance degradation over time in terms of energy consumption, range, battery charging efficiency and vehicle acceleration. Physics-based models are harder to develop and computationally costlier than data-driven models. However, once developed, they can be used in a much broader range of conditions and, more importantly, be applied also when no adequate on-road data are yet available. The proposed methodology is applied in a case study of BEV taxis in the city of Thessaloniki, Greece. In particular, the impact of battery preheating prior to charging is evaluated by simulation, showing that preheating could increase lifetime and mileage of BEV taxis by 14% in South European climates. In another application, it is calculated that mid-shift fast-charging could even double the life of the battery compared to fast-charging only before shift change, leading simultaneously to improved performance when compared within the same operational period. Such results could support battery and vehicle manufacturers as well as fleet managers to guide BEV taxi owners towards optimal charging behavior. The modeling approach presented in this paper can be further extended to other vehicle groups, environmental, driving and charging conditions, making it a powerful tool not only for manufacturers, but also for policymakers and charging infrastructure companies.