We have developed a battery state estimator based on a finite impulse response filter. Simulation results indicate that the estimator gives accurate prediction and numerically-stable performance in the regression of filter coefficients and the open-circuit potential, which yields the battery state of charge. The estimator is also able to predict battery power capabilities. Comparison of the measured and predicted state of charge (SOC) and the charge and discharge power capabilities (state of power, SOP) of a Li-ion battery are provided. Predictions for the SOC and SOP agree well with experimental measurements, demonstrating the estimator's application in battery management systems. In particular, this new approach appears to be more flexible than previous models; we show that it can capture the behavior of batteries governed by various physicochemical phenomena. (C) 2013 The Electrochemical Society. All rights reserved.