Set-based joint state and parameter estimation of a Li-ion cell using constrained zonotopes

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Author(s):	Locatelli, Diego ; Saccani, Giacomo ; Rego, Brenner S. ; Raffo, Guilherme, V ; Raimondo, Davide M. ; IEEE Total Authors: 6
Document type:	Journal article
Source:	2022 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC); v. N/A, p. 6-pg., 2022-01-01.
Abstract
Advanced Battery Management Systems (BMSs) rely on mathematical models to increase battery safety and performance. However, in order to be effective, BMSs require accurate parameter and state estimation. This is a difficult task due to the limited number of measurable quantities available, usually current, voltage and temperature. Within this context, the use of a joint state-parameter estimation permits to improve accuracy. In particular, under the assumption of unknown-but-bounded uncertainties, the use of Constrained Zonotopes (CZs) as a set representation allows to account for the coupling between states and parameters, which may arise from the obtained measurements. This feature enables CZ-based approaches to outperform standard set-based estimation methods such as interval-based ones. The effectiveness of this scheme is demonstrated on a Li-ion cell when using an electro-thermal model. (AU)

FAPESP's process:	14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
Grantee:	Marco Henrique Terra
Support Opportunities:	Research Projects - Thematic Grants