An MAF-Sensor (mass air flow) determines the mass of air flowing into a vehicle's fuel injection intake system and is essential to prevent inefficient burning. Therefore the main goal of the sensor is to provide a correct fuel-to-air ratio to ensure at suitable combustion at specific working conditions. Due to the very limited package space for the installation of the air intake system the available space provides the basis for the sensor position decision. As a consequence there is a mismatch between the optimal position and the geometric needs which results in faulty values delivered by the sensor. The incorrect data lead to a bad fuel-to-air ratio for the particular condition followed by e. g. engine stall or at least lower performance. To compensate this negative effect, especially in space limited environments, investigations towards a correction factor for this sensor are carried out. Due to the fact that invasive techniques disturb the flow especially on small diameters to a great extend in downstream direction optical measurement methods are used. Therefore stereoscopic 2D/3C-PIV and 2D-LDV measurements are realized for the validation of the flow field in the zone of influence in front of an MAF-Sensor. Additionally numeric simulations are carried out due to comparison purpose and for further geometry benchmarking.
Figure 1: LDA/PIV comparison (left), PIV/CFD comparison with uniformity index (right)
The results show a good agreement between the 2D/3C-PIV measurements and LDV-measurements, see Figure 1. Especially for diameters smaller than -0.5 < x/xmax < 0.5 the PIV data represents the LDV in the area of interest with good agreement. In spite of the fact that for the LDV measurements an optical refraction correction is used, the data in the range of -0.5 < x/xmax > 0.5 should be examined with caution. The strong optical refraction is mainly responsible for the deviation between the measurement techniques. As a result it can be shown that the PIV measurement can deliver reasonable data for the problem in the desired area and can be used for CFD data validation. Moreover the PIV data is used as a basis for creating a uniformity index to describe the flow in front of the MAF-sensor.
 Raffel M “Particle Image Velocimetry: A practical guide” 2nd Edition Springer Heidelberg (2007)
 Westerweel J and Elsigna GE and Adrian RJ “Particle Image Velocimetry for Complex and Turbulent Flows” Annu. Rev. Fluid Mech. 45 (2013) pp.409-436