Large-Scale Battery System Development and User-Specific Driving Behavior Analysis for Emerging Electric-Drive Vehicles

Emerging green-energy transportation, such as hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs), has a great potential for reduction of fuel consumption and greenhouse emissions. The lithium-ion battery system used in these vehicles, however, is bulky, expensive and unreliable, and has been t...

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Bibliographic Details
Published inEnergies (Basel) Vol. 4; no. 5; pp. 758 - 779
Main Authors Wu, Jie, Li, Kun, Jiang, Yifei, Lv, Qin, Shang, Li, Sun, Yihe
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.05.2011
Subjects
Aging
aging effect
Automobiles
battery system
Electric vehicles
Electricity distribution
Electronic mail systems
Emissions
Energy consumption
Energy efficiency
Energy industry
Energy storage
Environmental impact
Greenhouse gases
hybrid vehicle
Hybrid vehicles
Lithium
Market penetration
Systems development
user-specific driving pattern
United States > US
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Summary:Emerging green-energy transportation, such as hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs), has a great potential for reduction of fuel consumption and greenhouse emissions. The lithium-ion battery system used in these vehicles, however, is bulky, expensive and unreliable, and has been the primary roadblock for transportation electrification. Meanwhile, few studies have considered user-specific driving behavior and its significant impact on (P)HEV fuel efficiency, battery system lifetime, and the environment. This paper presents a detailed investigation of battery system modeling and real-world user-specific driving behavior analysis for emerging electric-drive vehicles. The proposed model is fast to compute and accurate for analyzing battery system run-time and long-term cycle life with a focus on temperature dependent battery system capacity fading and variation. The proposed solution is validated against physical measurement using real-world user driving studies, and has been adopted to facilitate battery system design and optimization. Using the collected real-world hybrid vehicle and run-time driving data, we have also conducted detailed analytical studies of users’ specific driving patterns and their impacts on hybrid vehicle electric energy and fuel efficiency. This work provides a solid foundation for future energy control with emerging electric-drive applications.
ISSN:1996-1073
1996-1073
DOI:10.3390/en4050758