@inproceedings{VeettilRakshitSchopenetal.2022,
  author    = {Veettil, Yadu Krishna Morassery and Rakshit, Shantam and Schopen, Oliver and Kemper, Hans and Esch, Thomas and Shabani, Bahman},
  title     = {Automated Control System Strategies to Ensure Safety of PEM Fuel Cells Using Kalman Filters},
  series = {Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia},
  booktitle = {Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia},
  editor    = {Bin Abdollah, Mohd Fadzli and Amiruddin, Hilmi and Singh, Amrik Singh Phuman and Munir, Fudhail Abdul and Ibrahim, Asriana},
  publisher = {Springer Nature},
  address   = {Singapore},
  isbn      = {978-981-19-3178-9},
  issn      = {2195-4356},
  doi       = {10.1007/978-981-19-3179-6_55},
  pages     = {296 -- 299},
  year      = {2022},
  abstract  = {Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer. Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench.},
  language  = {en}
}
@inproceedings{SattlerAttiAlexopoulosetal.2022,
  author    = {Sattler, Johannes Christoph and Atti, Vikrama and Alexopoulos, Spiros and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf and Dutta, Siddharth and Kioutsioukis, Ioannis},
  title     = {DNI forecast tool for the smart operation of a parabolic trough collector system with concrete thermal energy storage: Theory, results and outlook},
  series = {SolarPACES 2022 conference proceedings},
  booktitle = {SolarPACES 2022 conference proceedings},
  number    = {1},
  publisher = {TIB Open Publishing},
  address   = {Hannover},
  issn      = {2751-9899 (online)},
  doi       = {10.52825/solarpaces.v1i.731},
  pages     = {9 Seiten},
  year      = {2022},
  abstract  = {This work presents a basic forecast tool for predicting direct normal irradiance (DNI) in hourly resolution, which the Solar-Institut J{\"u}lich (SIJ) is developing within a research project. The DNI forecast data shall be used for a parabolic trough collector (PTC) system with a concrete thermal energy storage (C-TES) located at the company KEAN Soft Drinks Ltd in Limassol, Cyprus. On a daily basis, 24-hour DNI prediction data in hourly resolution shall be automatically produced using free or very low-cost weather forecast data as input. The purpose of the DNI forecast tool is to automatically transfer the DNI forecast data on a daily basis to a main control unit (MCU). The MCU automatically makes a smart decision on the operation mode of the PTC system such as steam production mode and/or C-TES charging mode. The DNI forecast tool was evaluated using historical data of measured DNI from an on-site weather station, which was compared to the DNI forecast data. The DNI forecast tool was tested using data from 56 days between January and March 2022, which included days with a strong variation in DNI due to cloud passages. For the evaluation of the DNI forecast reliability, three categories were created and the forecast data was sorted accordingly. The result was that the DNI forecast tool has a reliability of 71.4 \% based on the tested days. The result fulfils SIJ's aim to achieve a reliability of around 70 \%, but SIJ aims to still improve the DNI forecast quality.},
  language  = {en}
}
@inproceedings{SchopenShabaniEschetal.2022,
  author    = {Schopen, Oliver and Shabani, Bahman and Esch, Thomas and Kemper, Hans and Shah, Neel},
  title     = {Quantitative evaluation of health management designs for fuel cell systems in transport vehicles},
  series = {2nd UNITED-SAIG International Conference Proceedings},
  booktitle = {2nd UNITED-SAIG International Conference Proceedings},
  editor    = {Rahim, S.A. and As'arry, A. and Zuhri, M.Y.M. and Harmin, M.Y. and Rezali, K.A.M. and Hairuddin, A.A.},
  pages     = {1 -- 3},
  year      = {2022},
  abstract  = {Focusing on transport vehicles, mainly with regard to aviation applications, this paper presents compilation and subsequent quantitative evaluation of methods aimed at building an optimum integrated health management solution for fuel cell systems. The methods are divided into two different main types and compiled in a related scheme. Furthermore, different methods are analysed and evaluated based on parameters specific to the aviation context of this study. Finally, the most suitable method for use in fuel cell health management systems is identified and its performance and suitability is quantified.},
  language  = {en}
}