Estimation of SOC Based on Subspace Model of Power Battery and Adaptive Kalman Filter Method

Abstract:

Subspace identification method was adopted to build a state-space model of the battery pack by directly using the acquisition data of current and voltage. The terminal voltage was split into four parts according to the relationship between the current and each element of the models output voltage. Then an equivalent circuit model composed of resistances and capacities was set up to simulate the relationship. Based on the battery model, a state space model with SOC as the state variable and voltage U_Cb as the output was set up. By applying a designed adaptive Kalman filter method to the model and adopting the voltage U_T1 from the subspace method as the measured output, the optimum estimation of SOC can be acquired with only calculations of one dimension.

• Periodical: Applied Mechanics and Materials (Volumes 448-453)
• Pages: 1423-1427
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.448-453.1423
• Online since: October 2013
• Authors: Min Xin Zheng*, Qing Sen Yang
• Keywords: Adaptive Kalman Filter, Equivalent Circuit Model, Power Battery, State of Charge (SOC), Subspace Identification

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