Abstract
Recently a great deal of attention has been given to supercapacitors (SC) due to their outstanding power densities and long cycling life. Their behavior has been extensively analyzed and tested through several modeling approaches. One common technique for modeling the dynamic operation of SCs is through an electrical circuit model (ECM). This article presents a new approach to identifying ECM parameters by applying subspace system identification (SSID) algorithms and incorporating coulombic efficiency. This novel application of SSID improves model accuracy by almost 50% in some cases compared to the literature procedures. This was done without manual tuning of the parameters, risk of non-convergence or any prior knowledge. The approach was validated at three different temperatures and with experimental data from an electric motorcycle. The resulting models are ready to be used as building blocks in a wide range of applications such as energy management systems, renewable power generation, electric vehicles, and microgrids.
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