Lexicographic model predictive control strategy in ageing-aware optimal charging procedure for lithium-ion batteries. (July 2022)

• Record Type: Journal Article
• Authors: Pozzi, Andrea; Toti, Daniele
• Is Part Of: Computers & chemical engineering. Volume 163(2022)
• Publication Date: 2022-07
• Subjects: Lithium batteries -- Battery management systems -- Predictive control -- Systems modelling -- Multi-objective optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2022.107847
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Lithium-ion batteries require suitable model-based management systems to maintain high performance over time and mitigate ageing phenomena. A multi-objective optimization framework is required to achieve ageing minimization and fast charging. Most of the works in the literature simply increase charging time to reduce ageing. We propose a lexicographic model predictive control to deal with competing objective according to priority preferences. The results highlight the effectiveness of the proposed algorithm, which is demonstrated on a realistic simulator with the states reconstructed through an extended Kalman filter. Abstract: A proper battery management system has to find the optimal trade-off between fast charging and ageing effects minimization while satisfying safety constraints. Such a task can be formulated as a constrained multi-objective optimization problem with competitive goals, where a mathematical model is exploited in the description of the battery behaviour. In this paper, for the first time in the lithium-ion batteries context, a priority-based model predictive control that relies on a modified lexicographic approach is proposed, which is suitable for strictly convex objective functions. In particular, the considered objectives in order of priority are fast charging and ageing reduction. Moreover, a shrinking-horizon termination strategy is presented, thus enhancing a finite-time reaching phase of the state of charge reference. The effectiveness of the presented algorithm, coupled with a state observer, is tested on a numerical implementation of the well-known Pseudo-Two-Dimensional model and the results are compared with a conventional model predictive control procedure.