Signal Response Based On Speed And Reaction Of Otto Cycle Engine - Mohamed Pauzi, Muhammad Zaim (2016)
Over the decade, the Otto Cycle engine has become popular since the modern technology has replaced the old steam engine system that caused more pollution due to coal burning to generate steam gas. Recently, a transport journal reported that the statistics of vehicles production has been increasing annually due to the increasing populations and country development. Therefore, it has further increased gas emission produced by the engine combustion. Currently, the Otto cycle type of engine is still being investigated for its efficiency improvement. Exhaust emission is a major aspect that needs to be given attention because it emits harmful gases and influences the surrounding environment. In fact, numerous inventions have been generated to reduce harmful gases from the exhaust emission of an engine. Moreover, the effect of engine misfire had been found to reduce the performances of engine by increasing fuel consumption, exerting low output power, and imposing risk to catalytic converter to damage due to inefficient combustion. Thus, engine misfire detection (EMD) is important to compensate or to reduce the problem. Moreover, in order to adhere to the vehicles regulation and safety, diagnostic tools or on board diagnostic (OBD) is used to automatically detect faulty of the vehicles by using computer system. For this reason, a signal of engine misfire needs to be detected for the OBD system to recognize the problem. Various sensors could be used for EMD, but the performances in terms of signal response and speed are varied. In this research, narrowband oxygen sensor was applied instead of wideband set due to its advantages in terms of low maintenance and cost which is 70% cheaper. In addition, the capability of the narrowband oxygen sensor was tested via mathematical modelling and experiments using a model of single cylinder four-stroke engine with fuel injection system. From the experiment, engine misfire occurred due to a number of factors; either mechanical problems or environmental condition that affected the fuel mixture combustion. In general, the most common misfire had been found to occur because of unbalanced air to fuel ratio (AFR). Therefore, in order to determine the optimal parameters and condition, an artificial engine misfire was developed by exerting unbalanced AFR for the combustion using a microcontroller. Moreover, various digital signal filtering had been employed for signal conditioning to clarify the output signal transmitted by the narrowband oxygen sensor for EMD. Later, Discrete Fourier Transform was chosen to analyse the AFR signal which include misfire. For analysis purpose, the Digital Butterworth filter parameters were set based on the analyst signal. In addition, in order to verify the results, Discrete Wavelet Transform was implemented, as well as to evaluate misfire signal. Here, various mother wavelets were used to clarify the signal in order to verify misfire signal using various method of signal pre-processing at different engine conditions. Through the experimental and simulations, the results displayed a good agreement of signal features pattern while average EMD accuracy are 91.67% using Butterworth filter and 86.67% using DWT on experimental signal output.