Model-based electrochemical estimation of lithium-ion batteries

Kandler A. Smith; Christopher D. Rahn; Chao Yang Wang

doi:10.1109/CCA.2008.4629589

Model-based electrochemical estimation of lithium-ion batteries

Kandler A. Smith
, Christopher D. Rahn
, Chao Yang Wang

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

85 Scopus citations

Abstract

A linear Kalman filter based on a reduced order electrochemical model is designed to estimate internal battery potentials, concentration gradients, and state of charge (SOC) from external current and voltage measurements. The estimates are compared with results from an experimentally validated one-dimensional nonlinear finite volume model of a 6 Ah hybrid electric vehicle battery. The linear filter gives, to within ∼2%, performance in the 30%-70% SOC range, except in the case of severe current pulses that draw electrode surface concentrations to near saturation and depletion; however, the estimates recover as concentration gradients relax. With 4 to 7 states, the filter has low order comparable to empirical equivalent circuit models but provides estimates of the battery's internal electrochemical state.

Original language	English (US)
Title of host publication	17th IEEE International Conference on Control Applications, CCA
Pages	714-719
Number of pages	6
DOIs	https://doi.org/10.1109/CCA.2008.4629589
State	Published - 2008
Event	17th IEEE International Conference on Control Applications, CCA - San Antonio, TX, United States Duration: Sep 3 2008 → Sep 5 2008

Publication series

Name	Proceedings of the IEEE International Conference on Control Applications

Other

Other	17th IEEE International Conference on Control Applications, CCA
Country/Territory	United States
City	San Antonio, TX
Period	9/3/08 → 9/5/08

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Computer Science Applications
General Mathematics

Access to Document

10.1109/CCA.2008.4629589

Cite this

@inproceedings{e95f99f212ee498e8ef8207c694d7752,

title = "Model-based electrochemical estimation of lithium-ion batteries",

abstract = "A linear Kalman filter based on a reduced order electrochemical model is designed to estimate internal battery potentials, concentration gradients, and state of charge (SOC) from external current and voltage measurements. The estimates are compared with results from an experimentally validated one-dimensional nonlinear finite volume model of a 6 Ah hybrid electric vehicle battery. The linear filter gives, to within ∼2\%, performance in the 30\%-70\% SOC range, except in the case of severe current pulses that draw electrode surface concentrations to near saturation and depletion; however, the estimates recover as concentration gradients relax. With 4 to 7 states, the filter has low order comparable to empirical equivalent circuit models but provides estimates of the battery's internal electrochemical state.",

author = "Smith, \{Kandler A.\} and Rahn, \{Christopher D.\} and Wang, \{Chao Yang\}",

year = "2008",

doi = "10.1109/CCA.2008.4629589",

language = "English (US)",

isbn = "9781424422234",

series = "Proceedings of the IEEE International Conference on Control Applications",

pages = "714--719",

booktitle = "17th IEEE International Conference on Control Applications, CCA",

note = "17th IEEE International Conference on Control Applications, CCA ; Conference date: 03-09-2008 Through 05-09-2008",

}

Smith, KA, Rahn, CD & Wang, CY 2008, Model-based electrochemical estimation of lithium-ion batteries. in 17th IEEE International Conference on Control Applications, CCA., 4629589, Proceedings of the IEEE International Conference on Control Applications, pp. 714-719, 17th IEEE International Conference on Control Applications, CCA, San Antonio, TX, United States, 9/3/08. https://doi.org/10.1109/CCA.2008.4629589

Model-based electrochemical estimation of lithium-ion batteries. / Smith, Kandler A.; Rahn, Christopher D.; Wang, Chao Yang.
17th IEEE International Conference on Control Applications, CCA. 2008. p. 714-719 4629589 (Proceedings of the IEEE International Conference on Control Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Model-based electrochemical estimation of lithium-ion batteries

AU - Smith, Kandler A.

AU - Rahn, Christopher D.

AU - Wang, Chao Yang

PY - 2008

Y1 - 2008

N2 - A linear Kalman filter based on a reduced order electrochemical model is designed to estimate internal battery potentials, concentration gradients, and state of charge (SOC) from external current and voltage measurements. The estimates are compared with results from an experimentally validated one-dimensional nonlinear finite volume model of a 6 Ah hybrid electric vehicle battery. The linear filter gives, to within ∼2%, performance in the 30%-70% SOC range, except in the case of severe current pulses that draw electrode surface concentrations to near saturation and depletion; however, the estimates recover as concentration gradients relax. With 4 to 7 states, the filter has low order comparable to empirical equivalent circuit models but provides estimates of the battery's internal electrochemical state.

AB - A linear Kalman filter based on a reduced order electrochemical model is designed to estimate internal battery potentials, concentration gradients, and state of charge (SOC) from external current and voltage measurements. The estimates are compared with results from an experimentally validated one-dimensional nonlinear finite volume model of a 6 Ah hybrid electric vehicle battery. The linear filter gives, to within ∼2%, performance in the 30%-70% SOC range, except in the case of severe current pulses that draw electrode surface concentrations to near saturation and depletion; however, the estimates recover as concentration gradients relax. With 4 to 7 states, the filter has low order comparable to empirical equivalent circuit models but provides estimates of the battery's internal electrochemical state.

UR - https://www.scopus.com/pages/publications/53349090465

UR - https://www.scopus.com/pages/publications/53349090465#tab=citedBy

U2 - 10.1109/CCA.2008.4629589

DO - 10.1109/CCA.2008.4629589

M3 - Conference contribution

AN - SCOPUS:53349090465

SN - 9781424422234

T3 - Proceedings of the IEEE International Conference on Control Applications

SP - 714

EP - 719

BT - 17th IEEE International Conference on Control Applications, CCA

T2 - 17th IEEE International Conference on Control Applications, CCA

Y2 - 3 September 2008 through 5 September 2008

ER -

Model-based electrochemical estimation of lithium-ion batteries

Abstract

Publication series

Other

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this