@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}
}
@article{SchopenShahEschetal.2024,
  author    = {Schopen, Oliver and Shah, Neel and Esch, Thomas and Shabani, Bahman},
  title     = {Critical quantitative evaluation of integrated health management methods for fuel cell applications},
  series = {International Journal of Hydrogen Energy},
  volume    = {70},
  journal   = {International Journal of Hydrogen Energy},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0360-3199},
  doi       = {10.1016/j.ijhydene.2024.05.156},
  pages     = {370 -- 388},
  year      = {2024},
  abstract  = {Online fault diagnostics is a crucial consideration for fuel cell systems, particularly in mobile applications, to limit downtime and degradation, and to increase lifetime. Guided by a critical literature review, in this paper an overview of Health management systems classified in a scheme is presented, introducing commonly utilised methods to diagnose FCs in various applications. In this novel scheme, various Health management system methods are summarised and structured to provide an overview of existing systems including their associated tools. These systems are classified into four categories mainly focused on model-based and non-model-based systems. The individual methods are critically discussed when used individually or combined aimed at further understanding their functionality and suitability in different applications. Additionally, a tool is introduced to evaluate methods from each category based on the scheme presented. This tool applies the technique of matrix evaluation utilising several key parameters to identify the most appropriate methods for a given application. Based on this evaluation, the most suitable methods for each specific application are combined to build an integrated Health management system.},
  language  = {en}
}