{"title":"太阳能电动车混合电源系统的智能功率分配策略","authors":"P. Vishnu Sidharthan, Yashwant Kashyap","doi":"10.1109/icgea54406.2022.9791973","DOIUrl":null,"url":null,"abstract":"Technological developments in Battery electric vehicles (BEV) gains the utmost attention in recent transportation scenarios. Internal Combustion Engine (ICE) vehicles are facing several issues due to their effects on the environment, fuel cost, and availability. This shifts the automotive trends towards Electric Vehicles (EV). However, BEV faces few problems on range anxiety and battery life depletion for varying driving conditions. Supercapacitor (SC) coupled with batteries is the right solution for these rising problems. This paper focuses on the energy management of a battery-SC Hybrid Source System for a Solar Electric Vehicle (SEV). SC handles sudden power variations during varying driving load demands and solar irradiance. The proposed fuzzy logic power allocation strategy achieves improved battery life, source performances, and reduced battery peak currents for different driving and environmental factors. MATLAB/Simulink simulation results verify the significance of the integration of SC by reducing the battery stresses. The proposed strategy improves the battery longevity by 43% and 20% compared to BEV and hybrid conventional strategy respectively for a Worldwide Harmonized Light-duty Vehicles Test Procedure (WLTP) driving profile. Different driving conditions are considered in this work with varying driving and environmental conditions to prove the effectiveness of the proposed strategy.","PeriodicalId":151236,"journal":{"name":"2022 6th International Conference on Green Energy and Applications (ICGEA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Intelligent Power Allocation Strategy of Hybrid Source System in Solar Electric Vehicle\",\"authors\":\"P. Vishnu Sidharthan, Yashwant Kashyap\",\"doi\":\"10.1109/icgea54406.2022.9791973\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Technological developments in Battery electric vehicles (BEV) gains the utmost attention in recent transportation scenarios. Internal Combustion Engine (ICE) vehicles are facing several issues due to their effects on the environment, fuel cost, and availability. This shifts the automotive trends towards Electric Vehicles (EV). However, BEV faces few problems on range anxiety and battery life depletion for varying driving conditions. Supercapacitor (SC) coupled with batteries is the right solution for these rising problems. This paper focuses on the energy management of a battery-SC Hybrid Source System for a Solar Electric Vehicle (SEV). SC handles sudden power variations during varying driving load demands and solar irradiance. The proposed fuzzy logic power allocation strategy achieves improved battery life, source performances, and reduced battery peak currents for different driving and environmental factors. MATLAB/Simulink simulation results verify the significance of the integration of SC by reducing the battery stresses. The proposed strategy improves the battery longevity by 43% and 20% compared to BEV and hybrid conventional strategy respectively for a Worldwide Harmonized Light-duty Vehicles Test Procedure (WLTP) driving profile. Different driving conditions are considered in this work with varying driving and environmental conditions to prove the effectiveness of the proposed strategy.\",\"PeriodicalId\":151236,\"journal\":{\"name\":\"2022 6th International Conference on Green Energy and Applications (ICGEA)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 6th International Conference on Green Energy and Applications (ICGEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icgea54406.2022.9791973\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 6th International Conference on Green Energy and Applications (ICGEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icgea54406.2022.9791973","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent Power Allocation Strategy of Hybrid Source System in Solar Electric Vehicle
Technological developments in Battery electric vehicles (BEV) gains the utmost attention in recent transportation scenarios. Internal Combustion Engine (ICE) vehicles are facing several issues due to their effects on the environment, fuel cost, and availability. This shifts the automotive trends towards Electric Vehicles (EV). However, BEV faces few problems on range anxiety and battery life depletion for varying driving conditions. Supercapacitor (SC) coupled with batteries is the right solution for these rising problems. This paper focuses on the energy management of a battery-SC Hybrid Source System for a Solar Electric Vehicle (SEV). SC handles sudden power variations during varying driving load demands and solar irradiance. The proposed fuzzy logic power allocation strategy achieves improved battery life, source performances, and reduced battery peak currents for different driving and environmental factors. MATLAB/Simulink simulation results verify the significance of the integration of SC by reducing the battery stresses. The proposed strategy improves the battery longevity by 43% and 20% compared to BEV and hybrid conventional strategy respectively for a Worldwide Harmonized Light-duty Vehicles Test Procedure (WLTP) driving profile. Different driving conditions are considered in this work with varying driving and environmental conditions to prove the effectiveness of the proposed strategy.