A study of signal noise reduction of the mass air flow sensor using the flow conditioner on the air induction system of heavy-duty truck

Abstract

The mass air flow meter is a critical sensor that works based on thermal hot wire technology, used to determine the fuel to be injected into the cylinder and calculate the fuel-air ratio. In order to measure the airflow rate accurately, the flow should be uniform and smooth upstream of the sensor. The flow disturbance with a short straight length upstream of the flow meter results in the noise of the sensor signal. This noise causes unstable mass flow measurement on the system. Flow conditioners can be used to smooth the velocity profile of the flow. In this study, experimental and numerical methods were used to characterize the performance and operating accuracy of the mass flow meter used in heavy-duty truck applications. The flow conditioners were implemented to smooth the velocity profile around the mass flow meter that was disrupted by bends. The flow structures with and without flow conditioner were examined using Particle Image Velocimetry (PIV) to measure the time-averaged velocity. As well as the validated computational fluid dynamics (CFD) model provides data to understand the flow uniformity effect of the conditioner on the mass airflow (MAF) sensor. The optimization study was performed using a full factorial design of experiment (DOE) for flow conditioner design. A robust methodology was developed for the flow conditioner characteristics and mass airflow sensor implementation on the air induction system.