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.
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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...
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