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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Veröffentlicht in:	Journal of the Electrochemical Society Jg. 167; H. 6
Hauptverfasser:	Kolluri, Suryanarayana, Aduru, Sai Varun, Pathak, Manan, Braatz, Richard D., Subramanian, Venkat R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IOP Publishing 06.04.2020
Schlagworte:	advanced battery management systems lithium-ion batteries model predictive control
ISSN:	0013-4651, 1945-7111
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	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.
Bibliographie:	JESP-19-3713
ISSN:	0013-4651 1945-7111
DOI:	10.1149/1945-7111/ab7bd7