An electrochemical impedance spectroscopy method for prediction of the state of charge of a nickel-metal hydride battery at open circuit and during discharge

A multivariate method for predicting state of charge, from electrochemical data, of a nickel-metal hydride (NiMH)-battery is presented. Partial least square (PLS) regression is used to evaluate electrochemical impedance spectra and predict state of charge. The impedance spectra are analysed in the frequency range 239–0.6 Hz. The impedance is measured for different states of charge at open-circuit conditions and during continuous discharge at loads ranging between 0.2 C and 0.8 C. When measuring the impedance during discharge, the AC-current signal is imposed on the DC-current. The predictive capability of the method is tested by a cross validation procedure and the root mean square error of prediction is 7% when using the outlier identification capability of the PLS-regression method. The state of charge is evaluated with a single model, independently of whether the cell is subjected to open-circuit or polarised conditions. The predictive performance of the present model decreases at state of charge values less than 10%.