Real-time Nonlinear Model Predictive Control (NMPC) Strategies using Physics-Based Models for Advanced Lithium-ion Battery Management System (BMS)
Suryanarayana Kolluri, Sai Varun Aduru, Manan Pathak, Richard D. Braatz, Venkat R. Subramanian
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.
Topics & Concepts
Model predictive controlNonlinear systemBattery (electricity)Nonlinear modelControl theory (sociology)Lithium-ion batteryComputer scienceControl engineeringEngineeringControl (management)Artificial intelligencePhysicsPower (physics)Quantum mechanicsAdvanced Battery Technologies ResearchFuel Cells and Related MaterialsAdvancements in Battery Materials