نشریه تحقیقات موتور
پیاپی 31 (تابستان 1392)

Homogeneous charge compression ignition (HCCI) combustion engines are the new generation of internal combustion engines that are like compression ignition engines utilize the auto-ignition and similar to spark ignited engines use the homogenous air-fuel mixture. The HCCI combustion is highly diluted with the air or exhaust gas recirculation (EGR) and produces near-zero NOx and soot emissions. Unlike SI engines, the HCCI combustion engines exhibit low combustion cyclic variations. However, due to extreme sensitivity of the combustion to the temperature history, small cyclic variation can potentially lead to the combustion instability. This is important for a robust design of the engine control system. In this study, the operation of the HCCI combustion engine has been examined in a wide range of operating conditions. Cyclic variations were characterized by cylinder pressure data. Results showed that the stability of the HCCI combustion increased with the increase of low temperature heat release rate.

Piston scuffing is one of destructive faults in internal combustion (IC) engines. There are different causes to make this fault that the lack of the lubricant is the most important one among them. Due to its destruction power, its detection has always been noticed by engine producers. In this paper, with the purpose of this fault detection, a method based on Fuzzy logic and the use of engine performance parameters has been proposed. For this reason, 4 parameters including the rotational speed, the torque, the engine power and the blow-by flow rate were measured. Afterward, the Fuzzy logic system was developed for the piston scuffing fault detection. Experimental results showed that the piston scuffing fault caused the rotational speed, the torque and the engine power reduced more than 100 rpm, 25 Nm and 16 kW, respectively. In addition, a great and instant increase occurred in the blow-by flow rate. Results also demonstrated that the use of the changing pattern in engine performance parameters and applying them in the Fuzzy logic system made an appropriate procedure for the piston scuffing fault detection.

Decline in petroleum reserves, increasing production costs and the sale of the gasoline, increasing greenhouse gases and global warming has led to methods for improving the performance of gasoline engines is proposed. The hybrid cars with low consumption and performance close to conventional vehicles are highly regarded. The selection process for a combustion engine of hybrid cars with the parallel powertrain is studied in this paper. In this study, the default target and the mission for the hybrid vehicle design to be examined. Furthermore, with the review of the domestic market, limits of the design and the construction would be determined. In this section, the performance of hybrid car engines with selected electric motors and each of combustion engines was simulated by the ADVISOR software, which could simulate the conventional cars or hybrid and hybrid-electric vehicles. After identifying the performance of the vehicle with any of engines, most important parameters for vehicle designing were selected, and by the Expert Choice software, the combustion engine for desired vehicle would be selected. The engine performance map, in order to plan for its compatibility with other components, were also prepared. Then, in the accordance with the mission, the proper electric motor was introduced. Finally, using the sensitivity in the engineering choosing process was expressed by calculating the sensitivity of important parameters in the design.

The Timing belt is one of important parts of modern cars. "Heat extreme" and "overloading" are two common faults of these belts, which cause fatigue, erosion, sudden failures, and consequently damages to the engine. The present article introduces an intelligent method to diagnose these two major faults of belts, using vibration signals. The method presented in this research was designed based on a combination of experimental analyses, data mining of time domain signals and the artificial neural network (ANN) classifier. To do so, firstly, vibration signals of the belt were measured by a laser sensor in three conditions: (1) normal condition, (2) belt overloading and (3) heat extreme. In the data mining stage, five statistical features including mean, standard deviation, root mean square (RMS), kurtosis and impulse factors were extracted from vibration signals. Extracted features were used as ANN inputs to the fault diagnosis and the classification of different defects of the belt. Finally, the ANN, with the average accuracy of 76%, could diagnose and classify relevant faults in the timing belt of an engine. Results showed that intelligent methods could be used to diagnose faults of belts and therefore, to protect engines from serious damages, caused by their failures.

In the present study, the influence of the backpressure and the ambient temperature on non-reacting and non-evaporating characteristics of heavy fuel oil (HFO)/n-butanol blend at the injection pressure of 600 (bar) is numerically studied. Three different backpressures of 1, 14 and 28 bar and two different ambient temperatures of 298 K and 498 K have been considered in the combustion chamber of the medium speed engine. For the simulation of the liquid phase of the fuel interaction with the continuous air phase, an Eulerian-Lagrangian multiphase scheme was implemented. The open-source CFD toolbox of OpenFOAM was used for the present study. Due to the lack of experimental data in the context for HFO/n-butanol characteristics, the mesh resolution sensitivity analysis of C14H30 as a HFO at the injection pressure of 600 (bar) was carried out. Consequently, numerical results of the spray penetration length and the spray cone angle were validated by available experimental data with RMS of 3.34 and 0.905, respectively. Based on computational results, an increase in the backpressure from 1 to 14 (bar) decreased the spray penetration length, enhanced the spray cone angle, while reduced the SMD. Furthermore, due to the increase in the ambient temperature, the spray penetration length increased, while the SMD decreased.

Nowadays, considering vast natural gas reserves in the world and also the general approach to reduce environmental contaminants, the use of the natural gas as the clean fuel has been increased in many countries. Various schemes have been offered to use the natural gas in internal combustion engines. Blending the natural gas with other fuels in order to profit their different advantages is one of plans. Due to their unique characteristics, one of blends is hydrogen and methane. In this paper, a semi-dimensional, two-zone model has been used to study the performance of the hydrogen-methane fueled spark ignition engine. The in-cylinder mixture chemical composition included 11 chemical species, which were determined by the chemical equilibrium assumption. The extended Zeldovich mechanism was used to model the nitrogen oxides concentration. In addition, in order to predict the carbon monoxide concentration, a two-stage chemical kinetic mechanism was utilized. The model validation was done by comparing the results with literature experimental studies. A good agreement between results showed that the model had a good accuracy in predicting the performance of the engine. Engine emissions were compared and thoroughly discussed in different hydrogen-methane compositions and also equivalence ratios.