Bhangu, B S, Bentley, P, Stone, D A et al and Bingham, Chris
(2005)
State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers.
In: Power Electronics and Applications, 2005 European Conference on, September 2005, Dresden, Germany.
Full content URL: http://dx.doi.org/10.1109/EPE.2005.219601
| State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers | | The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Approaches based on the extended Kalman filter (EKF) are presented to provide correction for offset, drift and state divergence - an unfortunate feature of more traditional coulomb-counting techniques. Experimental results are employed to demonstrate the relative attributes of the proposed methodology | | ![[img]](http://eprints.lincoln.ac.uk/style/images/fileicons/application_pdf.png)
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| Item Type: | Conference or Workshop contribution (Presentation) |
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| Item Status: | Live Archive |
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Abstract
The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Approaches based on the extended Kalman filter (EKF) are presented to provide correction for offset, drift and state divergence - an unfortunate feature of more traditional coulomb-counting techniques. Experimental results are employed to demonstrate the relative attributes of the proposed methodology
| Additional Information: | The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Approaches based on the extended Kalman filter (EKF) are presented to provide correction for offset, drift and state divergence - an unfortunate feature of more traditional coulomb-counting techniques. Experimental results are employed to demonstrate the relative attributes of the proposed methodology |
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| Keywords: | State of Charge prediction, State of Health predction, electric vehicle, non-linear observers, Battery management systems (BMS), Energy storage, Estination technique, Hybrid electric vehicle (HEV), Modelling |
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| Subjects: | H Engineering > H600 Electronic and Electrical Engineering |
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| Divisions: | College of Science > School of Engineering |
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| ID Code: | 2552 |
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| Deposited On: | 23 May 2010 20:07 |
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