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@ARTICLE{Zou:890001,
      author       = {Zou, Wei and Froning, Dieter and Shi, Yan and Lehnert,
                      Werner},
      title        = {{A} least-squares support vector machine method for
                      modeling transient voltage in polymer electrolyte fuel
                      cells},
      journal      = {Applied energy},
      volume       = {271},
      issn         = {0306-2619},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2021-00595},
      pages        = {115092 -},
      year         = {2020},
      abstract     = {An investigation into the credibility and suitability of a
                      transient voltage model that characterizes the dynamic
                      behavior of polymer electrolyte fuel cells was carried out
                      by means of quantitative and qualitative validations. The
                      least squares support vector machine method was then used to
                      construct a transient voltage model of a fuel cell in the
                      first phase, including a validation based on experimental
                      data obtained from a test rig. In the second phase, a
                      thorough discussion of the effect of the fuel cell’s
                      operating conditions and the exterior load changes on the
                      model’s performance was implemented. For this phase, the
                      influences of the sampling interval and ramp ratio are
                      discussed and determined following a large number of tests
                      under a variety of operating conditions. The results show
                      that sampling with short time intervals is an effective way
                      to improve the model’s performance, and a smoother change
                      to the exterior load is more likely to be approximated by
                      the least squares support vector machine model. Moreover,
                      the voltage model is sensitive to the ramp value by
                      comparison to the ramp time. Suggestions for future
                      applications of the transient voltage models are also
                      provided. For a given combination of load changes, the
                      sampling interval should be managed within a range to reach
                      the demand data that satisfies the voltage accuracy. On the
                      other hand, for a determinate sampling interval, the dynamic
                      change of the load should be restricted within a limit to
                      ensure that the model error is lower than the demand value.},
      cin          = {IEK-14},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IEK-14-20191129},
      pnm          = {135 - Fuel Cells (POF3-135)},
      pid          = {G:(DE-HGF)POF3-135},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000540436500005},
      doi          = {10.1016/j.apenergy.2020.115092},
      url          = {https://juser.fz-juelich.de/record/890001},
}