This paper presents a framework for optimizing lithium-ion battery charging, subject to side reaction constraints. Such health-conscious control can improve battery performance significantly, while avoiding damage phenomena, such as lithium plating. Battery trajectory optimization problems are computationally challenging because the problems are often nonlinear, nonconvex, and high-order. We address this challenge by exploiting: (i) time-scale separation, (ii) orthogonal projection-based model reformulation, (iii) the differential flatness of solid-phase diffusion dynamics, and (iv) pseudospectral trajectory optimization. The above tools exist individually in the literature. For example, the literature examines battery model reformulation and the pseudospectral optimization of battery charging. However, this paper is the first to combine these four tools into a unified framework for battery management and also the first work to exploit differential flatness in battery trajectory optimization. A simulation study reveals that the proposed framework can be five times more computationally efficient than pseudospectral optimization alone.
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February 2016
Research-Article
A Computationally Efficient Approach for Optimizing Lithium-Ion Battery Charging
Ji Liu,
Ji Liu
Department of Mechanical
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: jxl1081@psu.edu
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: jxl1081@psu.edu
Search for other works by this author on:
Guang Li,
Guang Li
School of Engineering
and Material Sciences,
Queen Mary University of London,
Mile End Road,
London E1 4NS, UK
e-mail: g.li@qmul.ac.uk
and Material Sciences,
Queen Mary University of London,
Mile End Road,
London E1 4NS, UK
e-mail: g.li@qmul.ac.uk
Search for other works by this author on:
Hosam K. Fathy
Hosam K. Fathy
Department of Mechanical
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: hkf2@psu.edu
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: hkf2@psu.edu
Search for other works by this author on:
Ji Liu
Department of Mechanical
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: jxl1081@psu.edu
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: jxl1081@psu.edu
Guang Li
School of Engineering
and Material Sciences,
Queen Mary University of London,
Mile End Road,
London E1 4NS, UK
e-mail: g.li@qmul.ac.uk
and Material Sciences,
Queen Mary University of London,
Mile End Road,
London E1 4NS, UK
e-mail: g.li@qmul.ac.uk
Hosam K. Fathy
Department of Mechanical
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: hkf2@psu.edu
and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: hkf2@psu.edu
1Corresponding author.
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 6, 2015; final manuscript received November 17, 2015; published online December 23, 2015. Assoc. Editor: Beshah Ayalew.
J. Dyn. Sys., Meas., Control. Feb 2016, 138(2): 021009 (8 pages)
Published Online: December 23, 2015
Article history
Received:
May 6, 2015
Revised:
November 17, 2015
Citation
Liu, J., Li, G., and Fathy, H. K. (December 23, 2015). "A Computationally Efficient Approach for Optimizing Lithium-Ion Battery Charging." ASME. J. Dyn. Sys., Meas., Control. February 2016; 138(2): 021009. https://doi.org/10.1115/1.4032066
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