DOI QR코드

DOI QR Code

SOC Estimation Based on OCV for NiMH Batteries Using an Improved Takacs Model

  • Received : 2009.11.12
  • Published : 2010.03.25

Abstract

This paper presents a new method for the estimation of State of Charge (SOC) for NiMH batteries. Among the conventional methods to estimate SOC, Coulomb Counting is widely used, but this method is not precise due to error integration. Another method that has been proposed to estimate SOC is by using a measurement of the Open Circuit Voltage (OCV). This method is found to be a precise one for SOC estimation. In NiMH batteries, the hysteresis characteristic of OCV is very strong compared to other type of batteries. Another characteristic of NiMH battery to be considered is that the OCV of a NiMH battery under discharging mode is lower than it is under charging mode. In this paper, the OCV is modeled by a simple method based on a hyperbolic function which well known as Takacs’s model. The OCV model is then used for SOC estimation. Although the model is simple, the error is within 10%.

Keywords

Acknowledgement

Supported by : MKE (Ministry of Knowledge Economy)

References

  1. Manoj Datta, T. Senjyu, A. Yona, H. Sekine, and T. Funabashi, "Smoothing output power variations of isolated utility connected multiple PV systems by coordinated control," Journal of Power Electronics, Vol.9, No.2, pp. 320-333, Mar. 2009.
  2. Kong Soon Ng, Chin-Sien Moo, Yi-Ping Chen, and Yao-ching Hsieh, "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of litihium-ion batteries," Journal of Applied Energy, Vol. 86, No. 9, pp. 1506-1511, Sep. 2009. https://doi.org/10.1016/j.apenergy.2008.11.021
  3. Wu Guoliang, Lu Rengui, Zhu Chunbo, and CC Chan, "State of charge estimation for NiMH battery based on electromotive force method," Conf. Proc. IEEE Vehicle Power and Propulsion, pp.1-5, Sep. 2008.
  4. Antoni Szumanowski and Yuhua Chang, "Battery management system based on battery nonlinear dynamics modeling," IEEE Trans on Vehicular Tech, Vol. 57, No. 3, pp. 1425-1432, May 2008. https://doi.org/10.1109/TVT.2007.912176
  5. Salameh et. Al, "A mathematical model for lead-acid batteries," IEEE Trans. on Energy Conversion, Vol. 7, No.1, pp. 93-97, Mar. 1992. https://doi.org/10.1109/60.124547
  6. Min Chen and Gabriel A. Rincon-Mora, "Accurate electrical battery model capable of predicting runtime and I-V performance," IEEE Trans. on Energy Conversion, Vol. 21, No. 2, pp. 504-511, Jun. 2006. https://doi.org/10.1109/TEC.2006.874229
  7. D Sutanto and HL Chang, "A new battery model for use with battery energy storage systems and electric vehicles power systems," Conf. Proc. of IEEE Power Engineering Society Winter Meeting, Vol. 1, pp. 470-475, Jan. 2000.
  8. Mark Verbrugge and Edward Tate, "Adaptive state of charge algorithm for nickel metal hydride batteries including hysteresis phenomena," J. of Power Sources, Vol. 126, No. 1-2, pp. 236-249, Feb. 2004. https://doi.org/10.1016/j.jpowsour.2003.08.042
  9. Xidong Tang, Xiaodong Zhang, Brian Koch, and Damon Frisch, "Modeling and estimation of nickel metal hydride battery hysteresis for SOC estimation," Conf. Proc. of Prognostics and Health Management, pp. 1-12, 2008.
  10. J. Takacs, "A phenomenological mathematical model of hysteresis," Int. J. for Computation and Mathematics in Electrical and Electronics Engineering, Vol. 20, No. 4, pp. 1022-1014, 2001. https://doi.org/10.1108/EUM0000000005771
  11. Novie Ayub Windarko, Jaeho Choi, and Deoksu Hyun, "SOC estimation based on OCV for continuous charging/discharging process in NiMH battery," Proc. of 2nd Japan-Korea Workshop Joint Technical Workshop on Semiconductor Power Converter, pp. 1-6, 2009.
  12. Wei Li and Geza Joos, "A power electronic interface for a battery supercapacitor hybrid energy storage systems for wind applications," Conf. Proc. of IEEE PESC 2008, pp. 1762-1768, Jun. 2008.

Cited by

  1. A novel modeling methodology of open circuit voltage hysteresis for LiFePO4 batteries based on an adaptive discrete Preisach model vol.155, 2015, https://doi.org/10.1016/j.apenergy.2015.05.103
  2. Dynamic battery cell model and state of charge estimation vol.308, 2016, https://doi.org/10.1016/j.jpowsour.2016.01.072
  3. Electrical Modeling of Lithium-Polymer Battery vol.16, pp.2, 2011, https://doi.org/10.6113/TKPE.2011.16.2.199
  4. An Adaptive Estimation Scheme for Open-Circuit Voltage of Power Lithium-Ion Battery vol.2013, 2013, https://doi.org/10.1155/2013/481976
  5. Comprehensive study of the influence of aging on the hysteresis behavior of a lithium iron phosphate cathode-based lithium ion battery – An experimental investigation of the hysteresis vol.171, 2016, https://doi.org/10.1016/j.apenergy.2016.02.086
  6. Condition Monitoring of Lithium Polymer Batteries Based on a Sigma-Point Kalman Filter vol.12, pp.5, 2012, https://doi.org/10.6113/JPE.2012.12.5.778
  7. A comprehensive review on estimation strategies used in hybrid and battery electric vehicles vol.42, 2015, https://doi.org/10.1016/j.rser.2014.10.047
  8. On-line estimation of state-of-charge of Li-ion batteries in electric vehicle using the resampling particle filter vol.32, 2014, https://doi.org/10.1016/j.trd.2014.07.013
  9. An Efficient Battery Charging Algorithm based on State-of-Charge Estimation using 3-Phase AC-DC Boost Converter vol.29, pp.9, 2015, https://doi.org/10.5207/JIEIE.2015.29.9.096
  10. A control-oriented simulation model of a power-split hybrid electric vehicle vol.101, 2013, https://doi.org/10.1016/j.apenergy.2012.07.006
  11. Design of a power-split hybrid electric vehicle control system utilizing a rule-based controller and an equivalent consumption minimization strategy vol.228, pp.6, 2014, https://doi.org/10.1177/0954407013517220
  12. Using Padé Approximation in Takács Hysteresis Model vol.51, pp.7, 2015, https://doi.org/10.1109/TMAG.2015.2406299
  13. A novel parameter and state-of-charge determining method of lithium-ion battery for electric vehicles 2017, https://doi.org/10.1016/j.apenergy.2017.05.081
  14. Evaluation on State of Charge Estimation of Batteries With Adaptive Extended Kalman Filter by Experiment Approach vol.62, pp.1, 2013, https://doi.org/10.1109/TVT.2012.2222684
  15. Parameters Identification and Sensitive Characteristics Analysis for Lithium-Ion Batteries of Electric Vehicles vol.11, pp.1, 2017, https://doi.org/10.3390/en11010019