IMPROVING THE AIR SUPPLY CONTROL OF A FUEL CELL ELECTRIC VEHICLE

Maximilian K. Eisner, Zheng Zhou, Volker Formanski, Ralph M. Kennel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In the operation of fuel cell electric vehicles, one of the main challenges is to optimise the transient behaviour of the fuel cell system. This mostly concerns the air supply control as the limiting factor of the system’s dynamic response. Most of the advanced model-based control approaches that have been proposed in the literature for this control problem require the measurement of the air supply mass flow. In this paper, a mass flow model for a compressor with an air bearing is introduced for improving the signal quality of the available mass flow sensor in a prototype fuel cell electric vehicle. By using the model value instead of the sensor signal, the amplitude of noise is decreased by up to a factor of ten. In contrast to conventional signal filters like moving average filters, the dynamic response of the system is correctly displayed. This leads to a more excelling air mass flow control with less changes in the compressor rotational speed, and thus an improved power control of the fuel cell system. Furthermore, the mechanical stress on the compressor hardware is reduced. As a result, less degradation and component failures are to be expected.

Original languageEnglish
Title of host publicationIET Conference Proceedings
PublisherInstitution of Engineering and Technology
Pages146-151
Number of pages6
Volume2022
Edition4
ISBN (Electronic)9781839537189
DOIs
StatePublished - 2022
Event11th International Conference on Power Electronics, Machines and Drives, PEMD 2022 - Newcastle, Virtual, United Kingdom
Duration: 21 Jun 202223 Jun 2022

Conference

Conference11th International Conference on Power Electronics, Machines and Drives, PEMD 2022
Country/TerritoryUnited Kingdom
CityNewcastle, Virtual
Period21/06/2223/06/22

Keywords

  • AUTOMOTIVE APPLICATIONS
  • FUEL CELLS
  • MODEL-BASED CONTROL

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