Challenges and error propagation of PM sensor-based DPF diagnostics

Abstract

Monitoring the filtration efficiency of Diesel Particulate Filters (DPF), is a legislative requirement for minimizing PM emissions from diesel engines of passenger cars and heavy-duty vehicles. To reach this target On Board Diagnostics (OBD) implementation in real-time operation is necessary. These systems in passenger cars are often utilizing a PM sensor, models for PM emissions simulation and algorithms for diagnosis. Their performance is associated with a series of challenges related with the accuracy and effectiveness of involved models, algorithms and hardware. This paper analyzes the main influencing factors and their impact on the effectiveness of the OBD system. Error propagation analysis is being performed to quantify the error of detection. The comparison results in conclusions on the performance of the sensor based OBD model and its ability to fulfil legislative requirements