Battery state of health and charge estimation using Polynomial Chaos theory

Saeid Bashash, Hosam Kadry Fathy

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

9 Scopus citations

Abstract

In this effort, we use the generalized Polynomial Chaos theory (gPC) for the real-time state and parameter estimation of electrochemical batteries. We use an equivalent circuit battery model, comprising two states and five parameters, and formulate the online parameter estimation problem using battery current and voltage measurements. Using a combination of the conventional recursive gradient-based search algorithm and gPC framework, we propose a novel battery parameter estimation strategy capable of estimating both battery state-of-charge (SOC) and parameters related to battery health, e.g., battery charge capacity, internal resistance, and relaxation time constant. Using a combination of experimental tests and numerical simulations, we examine and demonstrate the effectiveness of the proposed battery estimation method.

Original languageEnglish (US)
Title of host publicationAerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;
PublisherAmerican Society of Mechanical Engineers (ASME)
Volume1
ISBN (Print)9780791856123
DOIs
StatePublished - Jan 1 2013
EventASME 2013 Dynamic Systems and Control Conference, DSCC 2013 - Palo Alto, CA, United States
Duration: Oct 21 2013Oct 23 2013

Other

OtherASME 2013 Dynamic Systems and Control Conference, DSCC 2013
CountryUnited States
CityPalo Alto, CA
Period10/21/1310/23/13

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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