Real-time Nonlinear Model Predictive Control (NMPC) Strategies using Physics-Based Models for Advanced Lithium-ion Battery Management System (BMS)

Optimal operation of lithium-ion batteries requires robust battery models for advanced battery management systems (ABMS). A nonlinear model predictive control strategy is proposed that directly employs the pseudo-two-dimensional (P2D) model for making predictions. Using robust and efficient model si...

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Bibliographic Details
Published in:Journal of the Electrochemical Society 2020-04, Vol.167 (6), p.63505
Main Authors: Kolluri, Suryanarayana, Aduru, Sai Varun, Pathak, Manan, Braatz, Richard D., Subramanian, Venkat R.
Format: Article
Language:English
Subjects:
advanced battery management systems
Electrochemistry
ENERGY STORAGE
lithium-ion batteries
MATERIALS SCIENCE
model predictive control
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Summary:Optimal operation of lithium-ion batteries requires robust battery models for advanced battery management systems (ABMS). A nonlinear model predictive control strategy is proposed that directly employs the pseudo-two-dimensional (P2D) model for making predictions. Using robust and efficient model simulation algorithms developed previously, the computational time of the nonlinear model predictive control algorithm is quantified, and the ability to use such models for nonlinear model predictive control for ABMS is established.
ISSN:0013-4651
1945-7111
DOI:10.1149/1945-7111/ab7bd7