Automotive Battery Prognostics Using Dual Extended Kalman Filter

This paper proposes a strategy for estimating the remaining useful life of automotive batteries based on dual Extended Kalman Filter. A nonlinear model of the battery is exploited for the on-line estimation of the State of Charge, and this information is used to evaluate the actual capacity and predict its future evolution, from which an estimate of the remaining useful life is obtained with suitable margins of uncertainty. Simulation results using experimental data from lead-acid batteries show the effectiveness of the approach.