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Performance Analysis of ASR-UKFs for Supercapacitor SoC Estimation in Hybrid Energy Storage Systems

Fusco, Davide; Maroufi, Seyede Masoome 1; Porpora, Francesco; Monaco, Mauro Di; Carne, Giovanni De ORCID iD icon 1; Tomasso, Giuseppe
1 Institut für Technische Physik (ITEP), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Due to their high specific power and durability, supercapacitors are promising candidates to be formed with batteries in Hybrid Energy Storage Systems (HESS). Accurately determining the supercapacitor’s State of Charge (SoC) represents a crucial task and improves system performance and energy management. In this paper, state-of-the-art algorithms to assess the SoC of supercapacitors are initially described, and their performances have been compared in simulation and validated experimentally. To improve the estimation performance, an Adaptive Square-Root Unscented Kalman Filter method has been finally proposed in this paper. Two electric circuit models have been defined for implementing the Kalman filtering method and analyzing its performance. Numerical results demonstrated a 7% estimation error reduction in terms of absolute value with respect to the conventional methods. Moreover, an estimation error lower than 1.5% has been achieved by the proposed method in experimental tests under realistic grid power profile, validating the numerical results and demonstrating the applicability of the developed estimator for supercapacitor SoC estimation


Verlagsausgabe §
DOI: 10.5445/IR/1000173478
Veröffentlicht am 16.08.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Technische Physik (ITEP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2168-6777, 2168-6785
KITopen-ID: 1000173478
HGF-Programm 37.12.03 (POF IV, LK 01) Smart Areas and Research Platforms
Erschienen in IEEE Journal of Emerging and Selected Topics in Power Electronics
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 1
Projektinformation HGF, HGF IVF2016 TALENT, VH-NG-1613
Nachgewiesen in Dimensions
Scopus
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