Modeling analysis of chrome carbide (Cr3C2) coating on parts of combustion chamber of a SI engine

In this study; piston, exhaust, and input valves of a gasoline engine were coated in 300 μm thickness with Cr3C2 by using the plasma spray coating method. The performance and emission values obtained from coated and uncoated engines were loaded on Artificial Neural Network (ANN) and estimated values were produced for every speed. Thus mathematical modeling of coated and uncoated (standard) engines was performed by using ANN. It was aimed to reduce the experiment repetitions and to decrease the experiment costs. The results obtained from the experiments were loaded on ANN and the values of the engines at all speeds were estimated. Results obtained from the tests were compared with those obtained from ANN and they were observed to be compatible. It was also observed that, with thermal barrier coating, specific fuel consumption (SFC), hydrocarbon (HC) and carbon monoxide (CO) values of the gasoline engine decreased; but NOx and exhaust gas temperature (EGT) increased. Furthermore, it was determined that results obtained through mathematical modeling reduced the number of test repetitions. Therefore, it was understood that time, fuel and labor could be saved in this way.