Search Results

A multi-zone model was used to predict the operating range of homogeneous charge compression ignition (HCCI) engine, the boundaries of the operating range were determined by knock (presented by ringing intensity), partial burn (presented by combustion efficiency) and cycle-to-cycle variations (presented by the sensitivity of indicated mean effective pressure to the initial temperature). A HCCI engine fueled with iso-octane was simulated, and it was found that the knock and cycle-to-cycle variations predicted by this model showed a satisfactory agreement with measurements under different initial temperatures and equivalence ratios, and the operating range was well reproduced by the model. Furthermore, the model was applied to develop the operating range for different engine speeds by changing initial temperature and equivalence ratio. Finally, the potential to expand the operating range of HCCI engines through two strategies, i.e. variable compression ratio and boost, were investigated.

Multi-dimensional models coupled with a reduced chemical mechanism were used to investigate the effect of fuel on exergy destruction fraction and sources in a reactivity controlled compression ignition (RCCI) engine. The exergy destruction due to chemical reaction (Deschem) makes the largest contribution to the total exergy destruction. Different from the obvious low temperature heat release (LTHR) behavior in gasoline/diesel RCCI, methanol has a negative effect on the LTHR of diesel, so the exergy destruction accumulation from LTHR to high temperature heat release (HTHR) can be avoided in methanol/diesel RCCI, contributing to the reduction of Deschem. Moreover, the combustion temperature in methanol/diesel RCCI is higher compared to gasoline/diesel RCCI, which is also beneficial to the lower exergy destruction fraction. Therefore, the exergy destruction of methanol/diesel RCCI is lower than that of gasoline/diesel RCCI at the same combustion phasing.

The flow performance of intake port significantly affects engine output power, fuel economy, and exhaust emissions in gasoline engines. Thus, optimal intake port geometry is desired in gasoline engines. To optimize the flow performance of intake port, a new optimization method combining genetic algorithm (GA) and artificial neural network (ANN) was proposed. First, an automatic system for generating the geometry of the tangential intake port was constructed to create various port geometries through inputting the 18 pre-defined structural parameters. Then, the effects of four critical structural parameters were investigated through numerical simulation. On the basis of the computational results, an ANN was used to model the flow performance of the intake port, and a genetic algorithm was simultaneously employed to optimize the flow performance by optimizing the four important structural parameters. Finally, the optimization results were verified through numerical simulation.