Abstract
Mathematical model for four-stroke gasoline engines based on a cylinder-by-cylinder engine modeling method that incorporates physical formulas such as engine geometry and empirical formulas such as combustion duration are applied in this study. In-cylinder pressure and temperature can be calculated for gasoline four-cycle engine. Modeling is done by treating each step in the cylinder as a volume control, solving the conservation equations of energy with submodules for combustion, heat transfer and dynamic analysis. Calculations in cycles are performed at each crank angle, so that the correct angle of ignition, variations in velocity, amount of intake mass and fuel burning speed can be predicted. Adjustment for the combustion parameter such as burn duration and form factor of the Wiebe function to increase the model accuracy was performed. It is shown that the optimization of the Wiebe function parameters able to improve the sum squared error of the engine pressure estimation by 58.17% compared to the result from generalized parameter functions, and the parameter of form factor and burn duration are influential by around twice of (1.86 and 2.55 times, respectively) the efficiency factor.
Highlights
The application of Spark Ignition (SI) engine has been greatly evolved since its discovery, ranging from cars, motorcycles, buses, planes, ships and generators in various scales
Each of the sample simulated in the model and monitored to determine the distribution of the error which was calculated using sum squared error (SSE) formula between the measured and simulation data
SI engine simulation was performed for in-cylinder pressure and temperature prediction
Summary
The application of Spark Ignition (SI) engine has been greatly evolved since its discovery, ranging from cars, motorcycles, buses, planes, ships and generators in various scales. For the Wiebe function, these parameters are the starting angle of combustion (θs), combustion duration (θd), efficiency (a) and form factor (n)[1,2]. These parameters are generally determined either by matching the experimental pressure data in the cylinder as well as by estimation[1,2,3,5]. A modeling of SI engine is developed to predict the in-cylinder and temperature data as well as observing the correlation of each parameter in Wiebe function towards the simulation results using Monte Carlo analysis
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