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The new simulation tool consists of an iterative loop of a 3-D code in parallel to a 1-D code that is employed to simulate transient engine cycles. The 1-D code yields the basic pattern of initial and boundary conditions and the 3-D simulations at several typical engine operating points are used to crosscheck the performance as well as aid in the model calibration. A flexible regression model of the fuel burn rate and the associated ROHR has been developed in conjunction with the 3-D simulations using a combination of three added Vibe functions. The emissions at the end of the expansion stroke are also predicted. The parameters of the Vibe functions and emissions are found via nonlinear regression based on state parameters such as engine speed, relative A/F ratio, EGR/rest gas contents, injection timings, etc. Additional 3-D simulations that are made at specific engine operating points complement this compact burn rate parameter library.

The paper deals with investigation of flow characteristics of turbocharger turbine under real operating conditions on engine by means of combination of experimental data and advanced 1-D code for combustion engine simulation. Coupling simulations tools with the results of measurements provides the engineers with data which are difficult or impossible to measure. For instance by means of a three pressure analysis (TPA) applicable on engine cylinder the engineers can obtain burn rate, valve flow and residual gas compound from measured pressure traces in cylinder and at inlet and outlet ports. A method for turbocharger turbine on engine identification similar in principle to the three pressure analysis has been applied on radial turbine with variable geometry. A new computational module has been developed to allow identification of instantaneous flow and efficiency characteristics of the turbine.

Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

The objective of this study is the development of a computationally efficient CFD-based tool for finding optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses, the duration of each pulse, the duration of the dwell, the exhaust gas recirculation rate and the boost pressure.