Constrained generalized predictive control of battery charging process based on a coupled thermoelectric model

Kailong Liu, Kang Li, Cheng Zhang

Research output: Contribution to journalArticle

41 Citations (Scopus)
365 Downloads (Pure)

Abstract

Battery temperature is a primary factor affecting the battery performance, and suitable battery temperature control in particular internal temperature control can not only guarantee battery safety but also improve its efficiency. This is however challenging as current controller designs for battery charging have no mechanisms to incorporate such information. This paper proposes a novel battery charging control strategy which applies the constrained generalized predictive control (GPC) to charge a LiFePO4 battery based on a newly developed coupled thermoelectric model. The control target primarily aims to maintain the battery cell internal temperature within a desirable range while delivering fast charging. To achieve this, the coupled thermoelectric model is firstly introduced to capture the battery behaviours in particular SOC and internal temperature which are not directly measurable in practice. Then a controlled auto-regressive integrated moving average (CARIMA) model whose parameters are identified by the recursive least squares (RLS) algorithm is developed as an online self-tuning predictive model for a GPC controller. Then the constrained generalized predictive controller is developed to control the charging current. Experiment results confirm the effectiveness of the proposed control strategy. Further, the best region of heat dissipation rate and proper internal temperature set-points are also investigated and analysed.
Original languageEnglish
Pages (from-to)145-158
Number of pages14
JournalJournal of Power Sources
Volume347
Early online date23 Feb 2017
DOIs
Publication statusPublished - 15 Apr 2017

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