Comparative Analysis of Advanced OCV PredictionMechanism for Batteries Used in Vehicular Systems

0*, Mark Bowkett**, Thomas Stockley***, Alessandro Mariani****, Jonathan Williams*****
*-** Senior Researcher, CAPSE, Faculty of Computing, Engineering and Science, University of South Wales,UK.
*** Senior Research Assistant, CAPSE, Faculty of Computing, Engineering and Science, University of South Wales,UK.
**** Research Student, CAPSE, Faculty of Computing, Engineering and Science, University of South Wales,UK.
***** CAPSE Director, CAPSE, Faculty of Computing, Engineering and Science, University of South Wales,UK.
Periodicity:May - July'2015
DOI : https://doi.org/10.26634/jps.3.2.3478

Abstract

This paper presents an advanced Open Circuit Voltage (OCV) prediction technique for battery cells. The work contains an investigation to examine the relaxation voltage curves, to analyse the potential for the OCV prediction technique in a practical system. The technique described in this paper employs one simple equation to predict the equilibrated cell voltage after a small rest period. The practical work detailed in this paper was conducted at the Center for Automotive and Power System Engineering (CAPSE) battery laboratories at the University of South Wales (USW). The results indicate that the proposed OCV prediction technique is highly effective and using this technique appreciable benefit can be accrued.

Keywords

System Analysis, OCV, Battery System, Predication Mechanism, Performance Analysis.

How to Cite this Article?

Thanapalan, K., Bowkett, M., Stockley, T., Mariani, A., and Williams, J. (2015). Comparative Analysis of Advanced OCV Prediction Mechanism for Batteries Used in Vehicular Systems. i-manager’s Journal on Power Systems Engineering, 3(2), 1-7. https://doi.org/10.26634/jps.3.2.3478

References

[1]. Aylor, J.H. (1992). A battery State of Charge Indicator for Electric Wheelchairs. Transactions on Industrial Electronics, IEEE, Vol.39(5), pp.398-409.
[2]. Bitterlin, I. F. (2004). Standby-battery autonomy versus power quality. Journal of Power Source, Vol.136(2), pp.351-355.
[3]. Chiang, Y. H., Sean, W. Y., Ke, J.C. (2011). Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electric vehicles,” J. Power Sources, Vol.196, No.8, pp.3921–3932.
[4]. Divya, K. C., & Ostergaard, J. (2009). Battery energy storage technology for power systems—An overview. Electric Power Systems Research, Vol.79(4), pp.511-520.
[5]. Juraschka, H., Thanapalan, K. K. T., Gusig, L. O., & Premier, G. C. (2014). Optimization Strategies for Combined Heat and Power Range Extended Electric Vehicles. In S. Helber, M. Breitner, D. Rösch, C. Schön, J.-M. G. von der Schulenburg, P. Sibbertsen, A. Wolter (Eds.), Operations Research Proceedings 2012 (pp. 315–320). Springer International Publishing.
[6]. Mariani, A., Stockley, T., Thanapalan, K., Williams, J., & Stevenson, P. (2014). Simple and effective OCV prediction mechanism for VRLA battery systems. In the Proceedings of the 3rd International Conference on Mechanical Engineering and Mechatronics, Prague, Czech Republic, pp.140-149.
[7]. Mariani, A., Thanapalan, K., Stevenson, P., & Williams, J. (2013). Techniques for estimating the VRLA batteries ageing, degradation and failure modes. In 19th Int. Conf. on Automation & Computing, UK, pp.43-47.
[8]. Ribeiro, P. F., Johnson, B. K., Crow, M. L., Arsoy, A., & Liu, Y. (2001). Energy Storage Systems for Advanced Power Applications. Proceedings of the IEEE., Vol.89(12), pp.1744-1746.
[9]. Roscher,M. A., & Sauer,D. U. (2011). “Dynamic electric behavior and open-circuit-voltage modeling of LiFePO4- based lithium ion secondary batteries,” J. Power Sources, Vol.196, No. 1, pp. 331–336.
[10]. Ruetschi, P. (2003). Silver-silver sulphate reference electrodes for use in lead-acid batteries. Journal of Power Sources, Vol.116(1-2), pp.53-60.
[11]. Sima, A. (2006, October 13). Sony exploding batteries – The chronicles. Softpedia. Retrieved from http://news.softpedia.com/news/Sony-Exploding- Batteries-Chronicles-37848.shtml
[12]. Stephen, D. (1999). The Kd Model, Methods of Measurement, and Application of Chemical Reaction Codes. Office of Environmental Restoration U.S. Department of Energy, Washington, DC 20585.
[13]. Stockley, T., Thanapalan, K., Bowkett, M., & Williams, J. (2014). Design and Implementation of Open Circuit Voltage Prediction Mechanism for Lithium-Ion Battery Systems. Systems Science & Control Engineering: An Open Access Journal, Vol. 2(1), pp.1-12.
[14]. Thanapalan, K., Williams J., Premier, G., & Guwy, A. (2011). Design and Implementation of Renewable Hydrogen Fuel Cell Vehicles. Renew. Energy Power Qual. J., Vol.9, pp.310-315.
[15]. Tremblay, O., & Dessaint, L. A. (2009). Experimental Validation of a Battery Dynamic Model for EV Applications, World Electric Vehicle Journal, Vol.3, pp.1-10.
[16]. Zhang, Y., &Harb, J. N. (2013). Performance characteristics of lithium coin cells for use in wireless sensing systems: Transient behaviour during pulse discharge. Journal of Power Sources, Vol.229, pp.299 – 307.
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