107. ACCURATE LITHIUM-ION BATTERY PARAMETER ESTIMATION WITH CONTINUOUS TIME SYSTEM IDENTIFICATION METHODS

Department: Electrical & Computer Engineering
Faculty Advisor(s): Chris Mi | Raymond A. De Callafon | Truong Nguyen

Primary Student
Name: Bing Xia
Email: bixia@ucsd.edu
Phone: 734-834-1208
Grad Year: 2018

Abstract
This research adopts continuous time system identification methods to estimate the parameters of equivalent circuit models for lithium ion batteries. Compared with discrete time identification methods, the continuous time estimation provides more accurate fit to both fast and slow dynamics in battery systems and is less sensitive to perturbations. A case of a second order equivalent circuit model is studied and shows that the continuous time estimations are more robust to high sampling rates and measurement noises. In addition, the continuous time least square estimation is further improved by introducing the instrumental variable method. Simulation and experiment results validate the analysis and demonstrate the superiority of the continuous time modeling methods in battery application.

Industry Application Area(s)
Control Systems | Energy/Clean technology

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