---
_id: '9879'
abstract:
- lang: eng
  text: Application of prognostics and health management (PHM) in the field of Proton
    Exchange Membrane (PEM) fuel cells is emerging as an important tool in increasing
    the reliability and availability of these systems. Though a lot of work is currently
    being conducted to develop PHM systems for fuel cells, various challenges have
    been encountered including the self-healing effect after characterization as well
    as accelerated degradation due to dynamic loading, all which make RUL predictions
    a difficult task. In this study, a prognostic approach based on adaptive particle
    filter algorithm is proposed. The novelty of the proposed method lies in the introduction
    of a self-healing factor after each characterization and the adaption of the degradation
    model parameters to fit to the changing degradation trend. An ensemble of five
    different state models based on weighted mean is then developed. The results show
    that the method is effective in estimating the remaining useful life of PEM fuel
    cells, with majority of the predictions falling within 5\% error. The method was
    employed in the IEEE 2014 PHM Data Challenge and led to our team emerging the
    winner of the RUL category of the challenge.
author:
- first_name: 'James Kuria '
  full_name: 'Kimotho, James Kuria '
  last_name: Kimotho
- first_name: Tobias
  full_name: Meyer, Tobias
  last_name: Meyer
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: 'Kimotho JK, Meyer T, Sextro W. PEM fuel cell prognostics using particle filter
    with model parameter adaptation. In: <i>Prognostics and Health Management (PHM),
    2014 IEEE Conference On</i>. ; 2014:1-6. doi:<a href="https://doi.org/10.1109/ICPHM.2014.7036406">10.1109/ICPHM.2014.7036406</a>'
  apa: Kimotho, J. K., Meyer, T., &#38; Sextro, W. (2014). PEM fuel cell prognostics
    using particle filter with model parameter adaptation. In <i>Prognostics and Health
    Management (PHM), 2014 IEEE Conference on</i> (pp. 1–6). <a href="https://doi.org/10.1109/ICPHM.2014.7036406">https://doi.org/10.1109/ICPHM.2014.7036406</a>
  bibtex: '@inproceedings{Kimotho_Meyer_Sextro_2014, title={PEM fuel cell prognostics
    using particle filter with model parameter adaptation}, DOI={<a href="https://doi.org/10.1109/ICPHM.2014.7036406">10.1109/ICPHM.2014.7036406</a>},
    booktitle={Prognostics and Health Management (PHM), 2014 IEEE Conference on},
    author={Kimotho, James Kuria  and Meyer, Tobias and Sextro, Walter}, year={2014},
    pages={1–6} }'
  chicago: Kimotho, James Kuria , Tobias Meyer, and Walter Sextro. “PEM Fuel Cell
    Prognostics Using Particle Filter with Model Parameter Adaptation.” In <i>Prognostics
    and Health Management (PHM), 2014 IEEE Conference On</i>, 1–6, 2014. <a href="https://doi.org/10.1109/ICPHM.2014.7036406">https://doi.org/10.1109/ICPHM.2014.7036406</a>.
  ieee: J. K. Kimotho, T. Meyer, and W. Sextro, “PEM fuel cell prognostics using particle
    filter with model parameter adaptation,” in <i>Prognostics and Health Management
    (PHM), 2014 IEEE Conference on</i>, 2014, pp. 1–6.
  mla: Kimotho, James Kuria, et al. “PEM Fuel Cell Prognostics Using Particle Filter
    with Model Parameter Adaptation.” <i>Prognostics and Health Management (PHM),
    2014 IEEE Conference On</i>, 2014, pp. 1–6, doi:<a href="https://doi.org/10.1109/ICPHM.2014.7036406">10.1109/ICPHM.2014.7036406</a>.
  short: 'J.K. Kimotho, T. Meyer, W. Sextro, in: Prognostics and Health Management
    (PHM), 2014 IEEE Conference On, 2014, pp. 1–6.'
date_created: 2019-05-20T13:11:02Z
date_updated: 2019-05-20T13:12:27Z
department:
- _id: '151'
doi: 10.1109/ICPHM.2014.7036406
keyword:
- ageing
- particle filtering (numerical methods)
- proton exchange membrane fuel cells
- remaining life assessment
- PEM fuel cell prognostics
- PHM
- RUL predictions
- accelerated degradation
- adaptive particle filter algorithm
- dynamic loading
- model parameter adaptation
- prognostics and health management
- proton exchange membrane fuel cells
- remaining useful life estimation
- self-healing effect
- Adaptation models
- Data models
- Degradation
- Estimation
- Fuel cells
- Mathematical model
- Prognostics and health management
language:
- iso: eng
page: 1-6
publication: Prognostics and Health Management (PHM), 2014 IEEE Conference on
status: public
title: PEM fuel cell prognostics using particle filter with model parameter adaptation
type: conference
user_id: '55222'
year: '2014'
...