SoC Estimation in Lithium-Ion Batteries with Noisy Measurements and Absence of Excitation

Author:

Martí-Florences Miquel1ORCID,Piñol Andreu Cecilia1ORCID,Clemente Alejandro12ORCID,Costa-Castelló Ramon1ORCID

Affiliation:

1. ETSEIB, ESAII, Universitat Politècnica de Catalunya, Avinguda Diagonal, 647, 08028 Barcelona, Spain

2. Institut de Recerca d’Energia de Catalunya, Jardins de les Dones de Negre 1, 08930 Sant Adrià del Besòs, Spain

Abstract

Accurate State-of-Charge estimation is crucial for applications that utilise lithium-ion batteries. In real-time scenarios, battery models tend to present significant uncertainty, making it desirable to jointly estimate both the State of Charge and relevant unknown model parameters. However, parameter estimation typically necessitates that the battery input signals induce a persistence of excitation property, a need which is often not met in practical operations. This document introduces a joint state of charge/parameter estimator that relaxes this stringent requirement. This estimator is based on the Generalized Parameter Estimation-Based Observer framework. To the best of the authors’ knowledge, this is the first time it has been applied in the context of lithium-ion batteries. Its advantages are demonstrated through simulations.

Funder

Spanish Ministry of Science and Innovation

European Union Next GenerationEU/PRTR

FI Joan Oró

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Electrochemistry,Energy Engineering and Power Technology

Reference64 articles.

1. IEA (2023, October 19). Electric Vehicles. Available online: https://www.iea.org/energy-system/transport/electric-vehicles.

2. Toyota Mirai: Powertrain Model and Assessment of the Energy Management;Carignano;IEEE Trans. Veh. Technol.,2023

3. IEA (2023, October 19). Renewables—Energy System. Available online: https://www.iea.org/energy-system/renewables.

4. Issues and challenges facing rechargeable lithium batteries;Tarascon;Nature,2001

5. Comparative Study of Energy Storage Systems (ESSs);Asri;J. Phys. Conf. Ser.,2021

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