However, it has to be noted that those requirements can lead to contradictory constrains to be satisfied by the control algorithms. Engines fitted with electronic control provide flexibility to adjust the engine parameters to achieve certain performance. Lately, control engineers in the automotive industry have been challenged with the task of improving fuel consumption and engine performance while simultaneously reducing pollutant emissions. Moreover, those are in reasonable agreement with the reference results while in-house developed package is possible to run simulations with changing speed for engine control purpose. Different numerical experiments have been carried out from which it can be concluded that all packages predict similar profiles of pressure and temperature in the engine cylinder. These packages are compared with an in-house developed package and with reference results available from the literature.
In the present study, two of the commercial packages, Ricardo Wave and Lotus Engine Simulation, have been tested on the capabilities for engine control purposes. Such techniques include variable valve timing, variable ignition timing, variable air to fuel ratio, and variable compression ratio. ECU computes the new set of parameters to make fine adjustments to actuators providing better engine performance. Various sensors are installed into the engine, the combustion performance is recorded, and data is sent to engine control unit (ECU). However, engine control involves different operating parameters. These parameters are required for advanced research on fluid flow and heat transfer and development of geometries of engine components. Integrated post-processing tools, including Ansys EnSight, enable the quick analysis, visualization, and communication of your Forte results.Most commonly used commercial engine simulation packages generate detailed estimation of the combustion and gas flow parameters.This gives you the ability to track soot particle nucleation, growth, agglomeration, and oxidation without a compute-time penalty to predict particle size and number.
Advanced spray models dramatically reduce grid and time-step dependency when compared to existing approaches.True multicomponent fuel-vaporization models enable a self-consistent representation of the physical spray and the kinetics for accurate prediction of fuel effects.