A zero-dimensional velocity-composition-frequency probability density function model for compression-ignition engine simulation 2020-01-0659
Numerical simulation of in-cylinder processes can significantly reduce the development and refinement costs of engines. While a 3D analysis offers the promise of increased accuracy, it can be impractical to evaluate more than a handful of design and operating conditions due to high computational expenses. On the other hand, a lower dimensional (0/1D) phenomenological model can provide considerable insight in terms of predicting significant sensitivities of design and operating variables on emissions and performance. In this endeavor, a combustion model for direct-injection compression-ignition (DICI) engine is developed that can approach the accuracy of higher dimensional models with significant reduction in computational cost. The proposed model uses transported probability density function (tPDF) method within a 0D framework to provide a computationally efficient solution while capturing the essential physics of in-cylinder combustion. Scalar mixing is accounted for by a modified Euclidean Minimum Spanning Tree (EMST) mixing model. A new model has been formulated to calculate the mixing timescale using the velocity-composition-frequency tPDF method. Numerical investigations are performed for a direct-injection diesel engine over a range of operating conditions encompassing a range of load and speed. A 42-species chemical mechanism including thermal NO is used to represent the gas-phase chemistry, and a semi-empirical two-equation model is used for soot. Simulated results of pressure, apparent heat-release-rate, and emission quantities are compared to the experimental measurements. The computed pressure and apparent heat release rate traces along with the emission quantities matches reasonably well with the experiment. . In summary, the proposed 0D numerical model provides a computationally less expensive alternative to a 3D numerical simulation for estimating engine performance and engine-out emission quantities in DICI engines.
Chandan Paul, Kai Jin, Navin Fogla, Kevin Roggendorf, Syed Wahiduzzaman