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

Kolluri, Suryanarayana; Aduru, Sai Varun; Pathak, Manan; Braatz, Richard D.; Subramanian, Venkat R.

doi:10.1149/1945-7111/ab7bd7

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

Abstract

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.

Authors:

; Aduru, Sai Varun; Pathak, Manan;

;

Publication Date:: 2020-04-06

Research Org.:: Univ. of Washington, Seattle, WA (United States); Battelle Memorial Institute, Columbus, OH (United States)

Sponsoring Org.:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

OSTI Identifier:: 1608383

Alternate Identifier(s):: OSTI ID: 1798986

Grant/Contract Number:: AR0000275; AC05-76RL01830

Resource Type:: Published Article

Journal Name:: Journal of the Electrochemical Society

Additional Journal Information:: Journal Name: Journal of the Electrochemical Society Journal Volume: 167 Journal Issue: 6; Journal ID: ISSN 0013-4651

Publisher:: The Electrochemical Society

Country of Publication:: United States

Language:: English

Subject:: 36 MATERIALS SCIENCE; 25 ENERGY STORAGE; Electrochemistry; Materials Science

Citation Formats


                    Kolluri, Suryanarayana, Aduru, Sai Varun, Pathak, Manan, Braatz, Richard D., and Subramanian, Venkat R. Real-time Nonlinear Model Predictive Control (NMPC) Strategies using Physics-Based Models for Advanced Lithium-ion Battery Management System (BMS).  United States: N. p., 2020. 
Web.  doi:10.1149/1945-7111/ab7bd7.

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                    Kolluri, Suryanarayana, Aduru, Sai Varun, Pathak, Manan, Braatz, Richard D., & Subramanian, Venkat R. Real-time Nonlinear Model Predictive Control (NMPC) Strategies using Physics-Based Models for Advanced Lithium-ion Battery Management System (BMS).  United States.  https://doi.org/10.1149/1945-7111/ab7bd7

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                    Kolluri, Suryanarayana, Aduru, Sai Varun, Pathak, Manan, Braatz, Richard D., and Subramanian, Venkat R. Mon .  
"Real-time Nonlinear Model Predictive Control (NMPC) Strategies using Physics-Based Models for Advanced Lithium-ion Battery Management System (BMS)".  United States.  https://doi.org/10.1149/1945-7111/ab7bd7.

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@article{osti_1608383,

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

  author       = {Kolluri, Suryanarayana and Aduru, Sai Varun and Pathak, Manan and Braatz, Richard D. and Subramanian, Venkat R.},

  abstractNote = {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.},

  doi          = {10.1149/1945-7111/ab7bd7},

  journal      = {Journal of the Electrochemical Society},

  number       = 6,

  volume       = 167,

  place        = {United States},

  year         = {2020},

  month        = {4}

}

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

Abstract

Citation Formats

Optimal Charging of Li-Ion Batteries With Coupled Electro-Thermal-Aging Dynamics journal, September 2017

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Efficient Reformulation of Solid Phase Diffusion in Electrochemical-Mechanical Coupled Models for Lithium-Ion Batteries: Effect of Intercalation Induced Stresses journal, January 2013

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Optimal Charging of Li-Ion Batteries With Coupled Electro-Thermal-Aging Dynamics
journal, September 2017

An Extended Differential Flatness Approach for the Health-Conscious Nonlinear Model Predictive Control of Lithium-Ion Batteries
journal, September 2017

Coordinate Transformation, Orthogonal Collocation, Model Reformulation and Simulation of Electrochemical-Thermal Behavior of Lithium-Ion Battery Stacks
journal, January 2011

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conference, July 2015

A Computationally Efficient Approach for Optimizing Lithium-Ion Battery Charging
journal, December 2015

Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems
journal, January 2017

Efficient Reformulation of Solid Phase Diffusion in Electrochemical-Mechanical Coupled Models for Lithium-Ion Batteries: Effect of Intercalation Induced Stresses
journal, January 2013

An initialization subroutine for DAEs solvers: DAEIS
journal, March 2001

Optimal Health-aware Charging Protocol for Lithium-ion Batteries: A Fast Model Predictive Control Approach
journal, January 2016

Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation
journal, January 2014

(Invited) Analyzing and Minimizing Capacity Fade through Optimal Model-based Control - Theory and Experimental Validation
journal, January 2017

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journal, December 2018

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journal, January 1992

Coulson and Richardson's Chemical Engineering Volume 3 (Chemical & Biochemical Reactors, and Process Control), 3rd Edition, by J.F. Richardson and D.G. Peacock (Eds), Pergamon Press, Oxford, UK (1994). 776 pages. ISBN 0-08-041002-2.
journal, January 1995

Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell
journal, January 1993

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journal, January 1990

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journal, November 2015

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conference, June 2011

Mathematical Model Reformulation for Lithium-Ion Battery Simulations: Galvanostatic Boundary Conditions
journal, January 2009

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journal, July 2015