Recent imaging studies have provided a new conceptual model of the internal structure of direct injection diesel fuel jets as well as empirical correlations predicting jet development and structure. This information was used to create a diesel cycle simulation model using C language including compression, fuel injection and combustion, and expansion processes. Empirical relationships were used to create a new mixing-limited zero-dimensional model of the diesel combustion process. During fuel injection five zones were created to model the reacting fuel jet: 1) liquid phase fuel 2) vapor phase fuel 3) rich premixed products 4) diffusion flame sheath 5) surrounding bulk gas. Temperature and composition in each zone is calculated. Composition in combusting zones was calculated using an equilibrium model that includes 21 species. Sub models for ignition delay, premixed burn duration, heat release rate, and heat transfer were also included. Apparent heat release rate results of the model were compared with data from a constant volume combustion vessel and two single-cylinder direct injection diesel engines. The modeled heat release results included all basic features of diesel combustion. Expected trends were seen in the ignition delay and premixed burn model studies, but the model is not predictive. The rise in heat release rate due to the diffusion burn is over-predicted in all cases. The shape of the heat release rate for the constant volume chamber is well characterized by the model, as is the peak heat release rate. The shape produced for the diffusion burn in the engine cases is not correct. The injector in the combustion vessel has a single nozzle and greater distance to the wall reducing or eliminating wall effects and jet interaction effects. Interactions between jets and the use of a spray penetration correlation developed for non-reacting jets contribute to inaccuracies in the model.

<p>Stringent regulatory requirements and modern diesel engine technologies have engaged automotive manufacturers and researchers in accurately predicting and controlling diesel engine-out emissions. As a result, engine control systems have become more complex and opaquer, increasing the development time and costs. To address this challenge, Model-based control methods are an effective way to deal with the criticality of the system study and controls. And physics-based combustion engine modeling is a key to achieve it. This thesis focuses on development and validation of a physics-based model for both engine and emissions using model-based design tools from MATLAB & Simulink. Engine model equipped with exhaust gas circulation and variable geometry turbine is adopted from the previously done work which was then integrated with the combustion and emission model that predicts the heat release rates and NO_xemission from engine. Combustion model is designed based on the mass fraction burnt from CA10 to CA90 and then NO_xpredicted using the extended Zeldovich mechanism. The engine models are tuned for both steady state and dynamics test points to account for engine operating range from the performance data. Various engine and combustion parameters are estimated using parameter estimation toolbox from MATLAB and Simulink by applying least squared solver to minimize the error between measured and estimated variables. This model is validated against the virtual engine model developed in GT-power for Cummins 6.7L turbo diesel engine. To account the harmonization of the testing cycles to save engine development time globally, a world harmonized stationary cycle (WHSC) is used for the validation. Sub-systems are validated individually as well as in loop with a complete model for WHSC. Engine model validation showed promising accuracy of more than 88.4 percent in average for the desired parameters required for the NO_xprediction. NO_x estimation is accurate for the cycle except warm up and cool down phase. However, NO_xprediction during these phases is limited due to actual NO_xmeasured data for tuning the model for real time NO_xestimation. Results are summarized at the end to compare the trend of NO_xestimation from the developed combustion and emission model to show the accuracy of in-cylinder parameters and required for the NO_x estimation. </p>