Lithium-ion battery packs for transportation and grid services represent a large investment that must be continuously monitored to ensure safety, to maximize performance, and to extend life to the greatest degree possible. The best available battery-management methods are model based; that is, they depend on sets of equations ("models") that describe the behaviors of the lithium-ion cells in the battery pack in order to perform their management tasks. This lecture will first derive "equivalent-circuit" models, which are presently state-of-art. It will next introduce "physics-based" models, which have potential benefits for future battery-management systems. Physics-based models are computationally complex, so a method will be presented to develop highly accurate reduced-order models suitable for battery management. Finally, a high-level overview of mechanisms of cell degradation will be given to motivate power-limits computations to be discussed in the next lecture.
Gregory Plett is Professor of Electrical and Computer Engineering at the University of Colorado Colorado Springs. He received his Ph.D. in Electrical Engineering from Stanford University in 1998 and has conducted research in battery-management topics for the past 18+ years. Prof. Plett leads a team of students who are investigating computationally efficient ways to create and implement reduced-order physics-based models of lithium-ion cells, finding methods to determine the parameter values for these cell models using simple laboratory tests, and making the models adaptive so that they capture the dynamics of the battery cell as it ages. These new methods are intended for use with controls to push the performance of a battery pack to its physical limits while slowing the rate of degradation. Prof. Plett has authored two textbooks on battery modeling and battery management, a specialization on "Algorithms for Battery Management Systems" on Coursera, 25 U.S. patents in the area of battery controls, and other publications having a total of over 6300 citations.