Model-Based Research on Ultracapacitors

The following article presents the analytical basis and research results for ultracapacitors, acquired purposely built test stand for dynamic load cycle tests. Furthermore, three methods allowing for determination of ultracapacitor model parameters were presented in the work. First was the off-line identification in time domain method, involving minimization of the mean square error of model response and element response alignment for given input. Second method was off-line identification in frequency domain, involving application of least squares method with implemented model response correction procedure. Third method was on-line identification which allowed for determination of model parameters in real time with use of Kalman filter. The methods presented can be applied in research of other types of energy storage systems, i.e.: electrochemical batteries or hybrid energy storage systems.

[1]  Xing Zhang,et al.  Cobalt sulfide nanoparticles anchored in three-dimensional carbon nanosheet networks for lithium and sodium ion batteries with enhanced electrochemical performance. , 2017, Journal of colloid and interface science.

[2]  Weimin Kang,et al.  A review on separators for lithiumsulfur battery: Progress and prospects , 2016 .

[3]  Hamid Gualous,et al.  Frequency, thermal and voltage supercapacitor characterization and modeling , 2007 .

[4]  Chien-Hsing Lee,et al.  Prediction of Equivalent-Circuit Parameters for Double-Layer Capacitors Module , 2013, IEEE Transactions on Energy Conversion.

[5]  R.W. De Doncker,et al.  Modeling the dynamic behavior of supercapacitors using impedance spectroscopy , 2001, Conference Record of the 2001 IEEE Industry Applications Conference. 36th IAS Annual Meeting (Cat. No.01CH37248).

[6]  Rik W. De Doncker,et al.  Modeling the dynamic behavior of supercapacitors using impedance-spectroskopy , 2002 .

[7]  Jihong Wang,et al.  Overview of current development in electrical energy storage technologies and the application potential in power system operation , 2015 .

[8]  A. Szumanowski,et al.  Batteries and Ultracapacitors Set in Hybrid Propulsion System , 2007, 2007 International Conference on Power Engineering, Energy and Electrical Drives.

[9]  Haoshen Zhou,et al.  Solar energy storage in the rechargeable batteries , 2017 .

[10]  Przemysław Szulim,et al.  Test bench and model research of hybrid energy storage , 2018 .

[11]  Adrian Chmielewski,et al.  Model of an electric vehicle powered by a PV cell — A case study , 2017, 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR).

[12]  J. Mączak,et al.  Aspects of balanced development of RES and distributed micro-cogeneration use in Poland: Case study of a µCHP with Stirling engine , 2016 .

[13]  Hui Wang,et al.  Progress of hydrogen storage alloys for Ni-MH rechargeable power batteries in electric vehicles: A review , 2017 .

[14]  Adrian Chmielewski,et al.  Experimental Research and Simulation Model of Electrochemical Energy Stores , 2017, AUTOMATION.

[15]  M. Armand,et al.  Modern generation of polymer electrolytes based on lithium conductive imidazole salts , 2009 .

[16]  A. H. Mohamed,et al.  Adaptive Kalman Filtering for INS/GPS , 1999 .

[17]  Meihong Wang,et al.  Energy storage technologies and real life applications – A state of the art review , 2016 .

[18]  Adrian Chmielewski,et al.  Experimental Research of Electrochemical Energy Storage , 2017, AUTOMATION.