Air–Fuel Ratio Imbalance Diagnostic of Spark-Ignited Engines With Modulated Sliding Discrete Fourier Transform

Autor: Avra Brahma, Yongsoon Yoon
Rok vydání: 2020
Předmět:
Zdroj: Journal of Dynamic Systems, Measurement, and Control. 142
ISSN: 1528-9028
0022-0434
DOI: 10.1115/1.4046550
Popis: This paper presents the novel on-board air–fuel ratio (AFR) imbalance diagnostic of spark-ignited (SI) engines. Because of the reciprocating nature of internal combustion engines, while this fault is present, it is known that the exhaust gas oxygen (EGO) sensor signal is accompanied by the oscillating disturbance of which frequency depends on the engine speed, such that it can be represented by the superposition of multiharmonic and DC signals. Motivated from this inherent feature, the novel diagnostic for detection and location of AFR imbalance is developed with modulated sliding discrete Fourier transform (mSDFT) and angular domain sampling. The feasibility is demonstrated with the simulated and measured AFR signals. It turns out that the developed diagnostic is able to identify fault types such as lean or rich imbalance and locate a single cylinder or multiple cylinders having abnormal AFR. It is robust to measurement noise at the expense of slow convergence rate. Spectral leakage is reduced with crank domain sampling such that accuracy in spectral analysis is improved. Finally, the diagnostic has great potential for broad reciprocating machinery.
Databáze: OpenAIRE
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