Efficient NOx sensor failure detection using frequency spectrum analysis.

In the present times it is the responsibility of the vehicle manufacturer to reduce and monitor the emissions that their vehicle is emitting into the environment. One such vehicle emission which is very harmful for the environment is Nitrogen Oxides (NOx). All internal combustion engine operated vehicles will have NOx sensor in them to monitor the NOx getting generated by the engine. The information from this sensor is crucial in order to take the correct action by the vehicle emission control system to treat NOx before releasing it to the environment. Hence it is very important to detect the failure in NOx sensors. This paper addresses the challenges in identifying NOx sensor failures, specifically concerning complex and time-consuming diagnostic methods that require dosing of fuel for testing. The conventional approach involves NOx sensor rationality checks, heating catalysts, and comparing engine outlet NOx and vehicle outlet NOx sensor values. To overcome these limitations, this present article introduces a digital and novel method employing Fourier transform based frequency spectrum analysis to learn the behavior of NOx sensors and detect anomalies, allowing early identification of failures without compromising emissions. By analyzing frequency components in the NOx signal, the present approach eliminates the need for fuel dosing, enhancing fuel economy and making it suitable for future OBD and emission legislations with increased complexity.