Health-aware battery charging via iterative nonlinear optimal control syntheses

被引:4
|
作者
Minh Vu [1 ]
Zeng, Shen [1 ]
Fang, Huazhen [2 ]
机构
[1] Washington Univ, Dept Elect & Syst Engn, St Louis, MO 63130 USA
[2] Univ Kansas, Dept Mech Engn, Lawrence, KS 66045 USA
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
关键词
Emerging applications in battery control; computational methods; MODEL-PREDICTIVE CONTROL; ION;
D O I
10.1016/j.ifacol.2020.12.1759
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
There is an increasing recognition of the critical importance of charging for the safety and life of lithium-ion batteries. This paper proposes a computationally efficient optimal control approach for the problem of real-time charging control. By incorporating specific constraints that must be satisfied during charging, a health-aware operation is promoted. To determine the optimal charging current in the given setup, a recently proposed iterative framework for solving constrained optimal control problems is leveraged. It is found that the resulting optimal charging currents can be expressed in terms of a piecewise-affine time-invariant state feedback law, which results in a high computational efficiency for the optimal control solution. Copyright (C) 2020 The Authors.
引用
收藏
页码:12485 / 12490
页数:6
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