Statistical modeling of OCV curves for aged battery cells
Paper in proceedings, 2017

Today it is standard to use equivalent circuit models to describe the dynamic behavior of Li-ion batteries. The parameters and the states of the model are often estimated with model-based approaches which require accurate Open Circuit Voltage (OCV) curves to relate OCV to State of Charge (SoC). However, batteries are inevitably subjected to aging with the consequence that the OCV-curve is changing with time. In this paper we propose a method for modeling the changes of the OCV-curve based on statistical information rather than from electrochemistry. The proposed model has only one free parameter to update, namely capacity based SoH. From laboratory experimental data it is demonstrated that the proposed model can significantly reduce the average deviation from an aged OCV-curve compared to keeping the OCV-curve from the beginning of life. Furthermore, the potential of the method in an estimation context is illustrated by using it together with an Extended Kalman Filter (EKF) for estimation of SoC. Both the maximum and root mean square errors are significantly reduced compared to when the OCV-curve at beginning of life is used.

Open Circuit Voltage

update

estimation

State of Health

Author

Anton Klintberg

Chalmers, Signals and Systems, Systems and control, Automatic Control

Emil Klintberg

Chalmers, Signals and Systems, Systems and control, Automatic Control

Björn Fridholm

Hannes Kuusisto

Torsten Wik

Chalmers, Signals and Systems, Systems and control, Automatic Control

IFAC 2017 World Congress, Toulouse, France

Vol. 50 1 2164-2168

Areas of Advance

Energy

Subject Categories

Control Engineering

DOI

10.1016/j.ifacol.2017.08.275

More information

Latest update

4/5/2018 7