A Behavioral Algorithm for State of Charge Estimation

In Hybrid Electricle Vehicles (HEV), performing online energy management is an important task to be achieved to reduce emissions, fuel consumption and increase vehicle performance. For this task, estimating the State of Charge (SOC) is needed since it serves as a measure of energy that is left inside an electrochemical battery. A variety of methods to solve this estimation problem have been proposed in the literature. However, most of these methods either assume equivalent circuit models for the battery and thus lose their validity under some discharge conditions or depend heavily on the choice of parameters in the algorithm. In this paper, we use behavioral framework to avoid postulation of a specific model for a battery and develop a new and simple SOC estimation algorithm. Once the problem is formulated as the computation of a specific free response of the battery, algorithm computes this response using only terminal current and terminal voltage measurements. We demonstrate the effectiveness of the algorithm with different discharge profiles using both simulated and real data.