Open AccessThis article is
- freely available
Large-Scale Battery System Development and User-Specific
Driving Behavior Analysis for Emerging Electric-Drive Vehicles
Institute of Microelectronics, Tsinghua University, Beijing 10084, China
Department of Electrical, Computer and Energy Engineering, University of Colorado at Boulder,
Department of Computer Science, University of Colorado at Boulder, Boulder, CO 80309, USA
* Author to whom correspondence should be addressed.
Received: 15 February 2011; in revised form: 26 March 2011 / Accepted: 13 April 2011 / Published: 29 April 2011
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
Article StatisticsClick here to load and display the download statistics.
Notes: Multiple requests from the same IP address are counted as one view.
Cite This Article
MDPI and ACS Style
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.
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(5):758-779.
Wu, Jie; Li, Kun; Jiang, Yifei; Lv, Qin; Shang, Li; Sun, Yihe. 2011. "Large-Scale Battery System Development and User-Specific
Driving Behavior Analysis for Emerging Electric-Drive Vehicles." Energies 4, no. 5: 758-779.