Multiphysics-Constrained Fast Charging of Lithium-Ion Battery With Active Set Predictive Control

Hao Zhong, Shujuan Meng, Xinan Zhang, Zhongbao Wei, Caizhi Zhang, Liang Du

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

Fast charging of lithium-ion batteries (LIBs) is critical for the further popularity of electric vehicles (EVs). However, overlooking physical limits of LIBs may cause quick health degradation or even catastrophic safety issues. Motivated by this, this paper proposes a hybrid multi-physics-constrained charging strategy for LIBs combining an active set method (ASM)-based model predictive control (MPC) and a rule-based method. A general form of the optimal charging problem is constructed as a constrained quadratic program (QP) to balance the charging rapidity, thermal safety, and battery degradation. Enabled by this formulation, the cost-efficient ASM is proposed to solve the optimization problem, which virtually gives a safety-and health-aware fast charging strategy. Comparative results suggest that the proposed strategy outperforms the traditional MPC solutions remarkably in terms of the computational tractability. Long-term cycling experiments validate the superiority of the proposed strategy in the optimal balance among the charging rapidity, thermal safety, and life extension.

源语言英语
页(从-至)1-11
页数11
期刊IEEE Transactions on Intelligent Transportation Systems
DOI
出版状态已接受/待刊 - 2024

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