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The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

Valvetrain dynamics modeling and engine combustion modeling are often carried out independently. As a result, the interaction between these two physical responses may not be accurately assessed. The objective of this work is to understand the impact that robust valve timing simulations, implemented using a fully coupled valve train dynamics and engine performance model, have on engine performance prediction. The integrated simulation and detailed technical approach are discussed through the presentation of an example implementation. An I4 engine model is developed in which engine performance and valvetrain dynamics modeling are coupled. A benefit of this multi-physics approach is that it reduces reliance on empirically derived estimates of valve lash in favor of physical modeling of engine valvetrain dynamics that predicts lash during engine performance modeling.

Rapid Compression Machines (RCM) offer the ability to easily change the compression ratio and the pressure/mixture composition/temperature to gather ignition delay data at various engine relevant conditions. Therefore, RCMs with optical access to the combustion chamber can provide an effective way to analyze macroscopic spray characteristics needed to understand the spray injection process and for spray model development, validation and calibration at conditions that are suitable for engines. Fuel surrogates can help control fuel parameters, develop models for spray and combustion, and perform laser diagnostics with known fluorescence characteristics. This study quantifies and evaluates the macroscopic spray characteristics of multicomponent gasoline surrogates in comparison to their gasoline counterparts, under gasoline direct injection (GDI) engine conditions.