Work

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

Year: 2020

Type: article

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.

Source: Journal of The Electrochemical Society

DOI: 10.1149/1945-7111/ab7bd7

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

Institutions: Texas Materials Institute, The University of Texas at Austin, Massachusetts Institute of Technology

Language: English

Topic: Advanced Battery Technologies Research

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: hybrid

Estimated APC paid: $1,950