A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models

Henry Miniguano, Andrés Barrado, Cristina Fernández, Pablo Zumel and Antonio Lázaro
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Henry Miniguano: Power Electronics Systems Group; Universidad Carlos III de Madrid, 28911 Leganés, Spain
Andrés Barrado: Power Electronics Systems Group; Universidad Carlos III de Madrid, 28911 Leganés, Spain
Cristina Fernández: Power Electronics Systems Group; Universidad Carlos III de Madrid, 28911 Leganés, Spain
Pablo Zumel: Power Electronics Systems Group; Universidad Carlos III de Madrid, 28911 Leganés, Spain
Antonio Lázaro: Power Electronics Systems Group; Universidad Carlos III de Madrid, 28911 Leganés, Spain

Energies, 2019, vol. 12, issue 9, 1-20

Abstract: Supercapacitors with characteristics such as high power density, long cycling life, fast charge, and discharge response are used in different applications like hybrid and electric vehicles, grid integration of renewable energies, or medical equipment. The parametric identification and the supercapacitor model selection are two complex processes, which have a critical impact on the system design process. This paper shows a comparison of the six commonly used supercapacitor models, as well as a general and straightforward identification parameter procedure based on Simulink or Simscape and the Optimization Toolbox of Matlab ® . The proposed procedure allows for estimating the different parameters of every model using a different identification current profile. Once the parameters have been obtained, the performance of each supercapacitor model is evaluated through two current profiles applied to hybrid electric vehicles, the urban driving cycle (ECE-15 or UDC) and the hybrid pulse power characterization (HPPC). The experimental results show that the model accuracy depends on the identification profile, as well as the robustness of each supercapacitor model. Finally, some model and identification current profile recommendations are detailed.

Keywords: supercapacitor models; parameter estimation; ECE15; HPPC; Simulink; Simscape; Matlab; Identification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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