Experimental study of monitoring fuel quality using three type of sensors and the comparison of their performance

The European Union (EU) Commission has proposed ambitious targets to reduce greenhouse gas (GHG) emissions by more than 55% by 2030 and achieve climate neutrality by 2050. The transport sector, responsible for a significant portion of EU emissions, needs to reduce its emissions by 90%. Considering that Heavy-duty vehicles (HDVs) contribute about 25% of road transport emissions in the EU, European countries have introduced GHG reduction targets for transport fuels. Some countries have implemented lower taxes on biodiesel blends above a certain proportion to incentivize their use. Additionally, many regions have established low or zero carbon zones in urban areas, which forbids the HDVs that do not meet the emission regulations to operate in these zones. For instance, in France, vehicles operating in low emissions zones must display the Crit’Air label certifying their emissions meet standards, with only Crit’Air 1-labeled vehicles permitted in most urban areas. According to this background, a method to determine the biofuel content thus is keen desired for the heavy duty transport industry. This study provides insights into the performance and capabilities of different sensors in determining FAME (Fatty Acid Methyl Ester)/HVO (Hydrotreated Vegetable Oil) levels in fuel blends, as well as their responses to water and soft particle contamination. The study focuses on testing three sensors, which are based on multiple properties measurement, tuning fork technology, and near infrared technology (NIR) respectively. As results, Sensor A is capable of detecting FAME content in fuel blends with high accuracy in the higher FAME range (>B85) and a temperature range of 10°C to 90°C but fails to detect HVO/DF content. Sensor B can detect FAME content with accuracy using regression and classification models. Sensor C exhibits relatively low average errors in detecting FAME content but shows more fluctuation in its measurements. Water contamination affects the functionality of both Sensor B and C, while soft particles have minimal impact. These findings contribute to the ongoing efforts to reduce emissions in the transport sector and promote cleaner and more sustainable fuels.