(75b) Estimation Methods for Battery State of Charge Determination
AIChE Annual Meeting
2010
2010 Annual Meeting
Computing and Systems Technology Division
Advances in Computational Methods and Numerical Analysis
Monday, November 8, 2010 - 12:50pm to 1:10pm
Battery systems do not explicitly indicate the existing state of charge. Parameters such as capacity change with time, temperature, and usage characteristics. Using available measurements along with high-fidelity models, online estimation routines can be applied to determine the state of health of the battery system.
Various methods have been used in the past to examine this problem. These methods include Moving Horizon Estimation (MHE), Extended Kalman Filter (EKF), and Unscented Kalman Filter (UKF). Past applications examined only tracking of the existing instantaneous parameter values related to the state of charge. It is proposed to examine online determination of the rate of change for various battery system parameters.