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Technical Paper

An Improved Battery Modeling Method Based on Recursive Least Square Algorithm Employing an Optimized Objective Function

2017-03-28
2017-01-1205
To monitor and guarantee batteries of electric vehicles in normal operation, battery models should be established primarily for the further application in battery management system such as parameter identification and state estimation including state of charge (SOC), state of health (SOH) and so on. In this paper, an improved battery modeling method is proposed which is based on the recursive least square (RLS) algorithm employing an optimized objective function. The proposed modified objective function not only includes the normal sum of voltage error squares between measured voltage and model output voltage but also introduces a new variable representing the sum of first order difference error squares for both kinds of voltages. This specialty can undoubtedly guarantee better agreement for the measured output and the model output. The battery model used in this paper is selected to be the conventional second order equivalent circuit model.
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