State-of-Charge Determination From EMF Voltage Estimation: Using Impedance, Terminal Voltage, and Current for Lead-Acid and Lithium-Ion Batteries

State-of-charge (SOC) determination is an increasingly important issue in battery technology. In addition to the immediate display of the remaining battery capacity to the user, precise knowledge of SOC exerts additional control over the charging/discharging process, which can be employed to increase battery life. This reduces the risk of overvoltage and gassing, which degrade the chemical composition of the electrolyte and plates. The proposed model in this paper determines the SOC by incorporating the changes occurring due to terminal voltage, current load, and internal resistance, which mitigate the disadvantages of using impedance only. Electromotive force (EMF) voltage is predicted while the battery is under load conditions; from the estimated EMF voltage, the SOC is then determined. The method divides the battery voltage curve into two regions: 1) the linear region for full to partial SOC and 2) the hyperbolic region from partial to low SOC. Algorithms are developed to correspond to the different characteristic changes occurring within each region. In the hyperbolic region, the rate of change in impedance and terminal voltage is greater than that in the linear region. The magnitude of current discharge causes varying rates of change to the terminal voltage and impedance. Experimental tests and results are presented to validate the new models.

[1]  S. Rodrigues,et al.  A review of state-of-charge indication of batteries by means of a.c. impedance measurements , 2000 .

[2]  J. D. Kozlowski.  A novel online measurement technique for AC impedance of batteries and other electrochemical systems , 2001, Sixteenth Annual Battery Conference on Applications and Advances. Proceedings of the Conference (Cat. No.01TH8533).

[3]  M. Verbrugge,et al.  Adaptive state of charge algorithm for nickel metal hydride batteries including hysteresis phenomena , 2004 .

[4]  R. Tenno,et al.  Evaluation of VRLA battery under overcharging: model for battery testing , 2002 .

[5]  F. Huet.  A review of impedance measurements for determination of the state-of-charge or state-of-health of secondary batteries , 1998 .

[6]  R. W. De Doncker,et al.  The non-linear low-frequency impedance of lead/acid batteries during discharge, charge and float operation , 2001 .

[7]  Yakup S. Ozkazanç,et al.  A new online state-of-charge estimation and monitoring system for sealed lead-acid batteries in Telecommunication power supplies , 2005, IEEE Transactions on Industrial Electronics.

[8]  Chaoyang Wang,et al.  Modeling the overcharge process of VRLA batteries , 2001, Sixteenth Annual Battery Conference on Applications and Advances. Proceedings of the Conference (Cat. No.01TH8533).

[9]  Rik W. De Doncker,et al.  Impedance measurements on lead–acid batteries for state-of-charge, state-of-health and cranking capability prognosis in electric and hybrid electric vehicles , 2005 .

[10]  Yaobin Chen,et al.  Battery pack state of charge estimator design using computational intelligence approaches , 2000, Fifteenth Annual Battery Conference on Applications and Advances (Cat. No.00TH8490).

[11]  Suleiman Abu-Sharkh,et al.  Rapid test and non-linear model characterisation of solid-state lithium-ion batteries , 2004 .

[12]  Ziyad M. Salameh,et al.  A mathematical model for lead-acid batteries , 1992 .

[13]  Andreas Jossen,et al.  Methods for state-of-charge determination and their applications , 2001 .

[14]  Atsuo Kawamura,et al.  A new estimation method of state of charge using terminal voltage and internal resistance for lead acid battery , 2002, Proceedings of the Power Conversion Conference-Osaka 2002 (Cat. No.02TH8579).

[15]  P. T. Krein,et al.  Equalization requirements for series VRLA batteries , 2001, Sixteenth Annual Battery Conference on Applications and Advances. Proceedings of the Conference (Cat. No.01TH8533).

[16]  Adnan H. Anbuky,et al.  VRLA battery state-of-charge estimation in telecommunication power systems , 2000, IEEE Trans. Ind. Electron..

[17]  Adnan H. Anbuky,et al.  A VRLA battery simulation model , 2004 .

[18]  F. Huet,et al.  Investigation of the high-frequency resistance of a lead-acid battery , 2006 .

[19]  Chi Kwan Lee,et al.  State of Health Determination: Two Pulse Load Test for a VRLA Battery , 2006 .

[20]  W.G. Hurley,et al.  State of charge determination in a lead-acid battery: combined EMF estimation and Ah-balance approach , 2004, 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551).