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Efficient NOx Sensor Failure Detection Using Frequency Spectrum Analysis Daimler Trucks Innovation Center India Pvt. Limited

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Ramesh, Prashanth Mysore, author.
Contributor:
Velichappattil, Anvar Hussain
Conference Name:
11th SAEINDIA International Mobility Conference (SIIMC 2024) (2024-12-11 : New Delhi, India)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2024
Summary:
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 proposed approach eliminates the need for fuel dosing, enhancing fuel economy and making it suitable for future On Board Diagnostics (OBD) and emission legislations with increased complexity
Notes:
Vendor supplied data
Publisher Number:
2024-28-0216
Access Restriction:
Restricted for use by site license

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