Real-time Battery State of Charge and parameters estimation through Multi-Rate Moving Horizon Estimator

Tushar Desai*, Federico Oliva, Riccardo M.G. Ferrari*, Daniele Carnevale

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

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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.

Original languageEnglish
Pages (from-to)6124-6129
Number of pages6
JournalIFAC-PapersOnLine
Volume56
Issue number2
DOIs
Publication statusPublished - 2023
Event22nd IFAC World Congress - Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023

Keywords

  • Battery Management
  • Energy systems
  • Moving Horizon Estimation
  • Observer Design
  • Parameter-varying systems
  • Robust Estimation

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