Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle
Joint Authors
Gadsden, S. A.
Habibi, Saeid
al-Shabi, M.
Source
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-04-13
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
This paper discusses the application of condition monitoring to a battery system used in a hybrid electric vehicle (HEV).
Battery condition management systems (BCMSs) are employed to ensure the safe, efficient, and reliable operation of a battery, ultimately to guarantee the availability of electric power.
This is critical for the case of the HEV to ensure greater overall energy efficiency and the availability of reliable electrical supply.
This paper considers the use of state and parameter estimation techniques for the condition monitoring of batteries.
A comparative study is presented in which the Kalman and the extended Kalman filters (KF/EKF), the particle filter (PF), the quadrature Kalman filter (QKF), and the smooth variable structure filter (SVSF) are used for battery condition monitoring.
These comparisons are made based on estimation error, robustness, sensitivity to noise, and computational time.
American Psychological Association (APA)
Gadsden, S. A.& al-Shabi, M.& Habibi, Saeid. 2011. Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle. ISRN Signal Processing،Vol. 2011, no. 2011, pp.1-17.
https://search.emarefa.net/detail/BIM-447234
Modern Language Association (MLA)
Gadsden, S. A.…[et al.]. Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle. ISRN Signal Processing No. 2011 (2011), pp.1-17.
https://search.emarefa.net/detail/BIM-447234
American Medical Association (AMA)
Gadsden, S. A.& al-Shabi, M.& Habibi, Saeid. Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle. ISRN Signal Processing. 2011. Vol. 2011, no. 2011, pp.1-17.
https://search.emarefa.net/detail/BIM-447234
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-447234