4.6 Article

State-of-Charge Estimation Using an EKF-Based Adaptive Observer

Journal

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 27, Issue 5, Pages 1907-1923

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2018.2842038

Keywords

Adaptive observer; electrochemical equations; Kalman filter (KF); low-order model; state-of-charge (SOC) estimation; variable solid-state diffusivity model

Funding

  1. Automotive Partnership Canada
  2. Ontario Research Fund
  3. General Motors

Ask authors/readers for more resources

Lithium-ion batteries are used to store energy in electric vehicles. State of charge (SOC) is an important quantity of the battery cells that need to be estimated using limited measurements. In this paper, SOC estimation via an electrochemical model, a physics-based model, is considered. For lithium iron phosphate cells, a variable solid-state diffusivity model provides significantly more accuracy, but this complicates the model further. A previously obtained, simplified but still a physics-based model is used in this paper. An extended Kalman filter (KF)-based adaptive observer is designed via a low-order approximation of this electrochemical model. The predictions of the estimator are compared with the experimental data in simulations. The simulations are efficient and more accurate than a standard KF.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available