PERFORMANCE ANALYSIS OF THREE TYPES OF INTERNAL COMBUSTION ENGINES USING NEURAL NETWORK PREDICTORS

Nowadays, the use of LPG for internal combustion engines has been increased. For that reason, it is necesarry to investigate internal combustion engines to predict the performence of such systems. In this paper, three types of engine temparatures were analysed using proposed neural network predictors. Firstly, three types engine block temparatures were measured with laser measurement instrument during different engine speeds. However, one engine type was diesel engine, the others were LPG+Petrol engines. Secondly, two types of neural networks were used to predict temperature variations of three types engines. Finally, the results of neural predictors were improved that this kind of predictors will be employed to predict in real time applications