Development and experimental parameterization of a physics-based second-order lithium-ion battery model

Donald Docimo, Mohammad Ghanaatpishe, Hosam K. Fathy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

This paper uses the principles of electrochemistry to derive a simple second-order model of lithium-ion battery dynamics. Low-order lithium-ion battery models exist in the literature, but are typically either linear, empirical, or both. Our goal, in contrast, is to obtain a model simple enough for control design but grounded in the principles of electrochemistry. The model reduction approach used in this paper has the added advantage of leading to a novel analytic expression for the capacitance associated with voltage relaxation. A process for identifying model parameters from experiments is outlined, and experimental results are used to evaluate the validity of the model.

Original languageEnglish
Title of host publicationActive Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791846186
StatePublished - Jan 1 2014
EventASME 2014 Dynamic Systems and Control Conference, DSCC 2014 - San Antonio, United States
Duration: Oct 22 2014Oct 24 2014

Publication series

NameASME 2014 Dynamic Systems and Control Conference, DSCC 2014
Volume1

Conference

ConferenceASME 2014 Dynamic Systems and Control Conference, DSCC 2014
CountryUnited States
CitySan Antonio
Period10/22/1410/24/14

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Docimo, D., Ghanaatpishe, M., & Fathy, H. K. (2014). Development and experimental parameterization of a physics-based second-order lithium-ion battery model. In Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems (ASME 2014 Dynamic Systems and Control Conference, DSCC 2014; Vol. 1). American Society of Mechanical Engineers.