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Supercapacitors offer a wide range of applications for space flight. The aim of this activity was to pursue life tests on commercial off the shelf (COTS) supercapacitors from different manufacturers, to evaluate their performance after long term vacuum exposure and to investigate balancing designs for the use of these cells in banks of supercapacitors (BOSC). This study enabled to select the most suitable part for space applications and to confirm the design rules at unit level and deratings at component level, which need to be applied. All those complementary results have paved the way to the on-going activities related to Nesscap 10F qualification and associated modular Bank Of Supercapacitors development for space applications.

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In this paper, the system procedure for the identification of the equivalent electrical circuit diagram of electrochemical cells is being given. Due to the fact that energy storage systems (ESS) penetrate within many applications, the availability of their accurate and simple simulation models for time–domain analysis is very desirable. This paper describes the configuration of the laboratory measuring systems required for data acquisition, curation, and analysis of received measured data required for development of equivalent electrical circuit models (EECM) of electrochemical cells. Nowadays, various types of electrochemical cells are available for packaging technology. Therefore, the evaluation of presented identification methodology is validated through measurements of two different types of LiFePO4 cells. The first cell type is prismatic labeled LFP040AHA, and the second type is NPB 60 AH of the same manufacturer. The main aim of this paper is the determination of the elements of equivalent electrical circuit schematics of selected electrochemical cells. Consequently, the development of a simulation model is described, together with the evaluation of its accuracy through comparisons with experimental measurements. From achieved results, the relative error of simulation model varies at 2%, and thus the presented methodology is suitable for identification of EECM, and consequent design of accurate and fast computing simulation models of ESS systems.