Considering the growing role of natural gas as an alternative fuel in stationary and automobile engines and the differences in its composition, the influence of natural gas composition on knocking combustion in spark ignition gas engines is studied both experimentally and by employing detailed chemistry. A SI single cylinder gas engine with variable compression ratio has been used for experimental observations. The chemical scheme is embedded into a zero-dimensional model which employ three-zone approach. The scheme is used to simulate the post-flame heat release and pre-flame auto-ignition. The reactions in burning zone are modeled by chemical equilibrium calculations. The simulated results are in good agreement with the experimental observations.
Mechanical and thermodynamical performance of internal combustion engines is significantly affected by the engine working temperature. In an engine test bed, the internal combustion engines are tested in different operating conditions using a dynamometer. It is required that the engine temperature be controlled precisely, particularly in transient states. This precise control can be achieved by an engine coolant conditioning system mainly consisting of a heat exchanger, a control valve, and a controller. In this study, constitutive equations of the system are derived first. These differential equations show the second-order nonlinear time-varying dynamics of the system. The model is validated with the experimental data providing satisfactory results. After presenting the dynamic equations of the system, a fuzzy controller is designed based on our prior knowledge of the system. The fuzzy rules and the membership functions are derived by a trial and error and heuristic method. Because of the nonlinear nature of the system the fuzzy rules are set to satisfy the requirements of the temperature control for different operating conditions of the engine. The performance of the fuzzy controller is compared with a PI one for different transient conditions. The results of the simulation show the better performance of the fuzzy controller. The main advantages of the fuzzy controller are the shorter settling time, smaller overshoot, and improved performance especially in the transient states of the system.
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