Real-time Battery State of Charge and parameters estimation through Multi-Rate Moving Horizon Estimator
T.K. Desai (TU Delft - Team Riccardo Ferrari)
Federico Oliva (University of Rome Tor Vergata)
R. Ferrari (TU Delft - Team Riccardo Ferrari)
Daniele Carnevale (University of Rome Tor Vergata)
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Abstract
For reliable and safe battery operations, accurate and robust State of Charge (SOC) and model parameters estimation is vital. However, the nonlinear dependency of the model parameters on battery states makes the problem challenging. We propose a Moving-Horizon Estimation (MHE)-based robust approach for joint state and parameters estimation. Dut to all the time scales involved in the model dynamics, a multi-rate MHE is designed to improve the estimation performance. Moreover, a parallelized structure for the observer is exploited to reduce the computational burden, combining both multi-rate and a reduced-order MHEs. Results show that the battery SOC and parameters can be effectively estimated. The proposed MHE observers are verified on a Simulink-based battery equivalent circuit model.
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