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Energies 2011, 4(5), 758-779; doi:10.3390/en4050758
Article

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

1,* , 2
,
3
,
3
,
2
 and
1
1 Institute of Microelectronics, Tsinghua University, Beijing 10084, China 2 Department of Electrical, Computer and Energy Engineering, University of Colorado at Boulder, 3 Department of Computer Science, University of Colorado at Boulder, Boulder, CO 80309, USA
* Author to whom correspondence should be addressed.
Received: 15 February 2011 / Revised: 26 March 2011 / Accepted: 13 April 2011 / Published: 29 April 2011
(This article belongs to the Special Issue Hybrid Vehicles)
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Abstract

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.
Keywords: battery system; user-specific driving pattern; hybrid vehicle; aging effect battery system; user-specific driving pattern; hybrid vehicle; aging effect
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Wu, J.; Li, K.; Jiang, Y.; Lv, Q.; Shang, L.; Sun, Y. Large-Scale Battery System Development and User-Specific Driving Behavior Analysis for Emerging Electric-Drive Vehicles. Energies 2011, 4, 758-779.

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