7.2 engine simulation on performance

7.2 engine simulation on performanceMuhammad nadiarulah (2bng)17.2.1 Type of software that can access engine performanceDyno simulation softwareEngine analyzerEngine sim 1.8 betaGt suite

7.2.1 Dyno simulation softwareThe interferance

Calculated Outputs:Horsepower CurvesTorque CurvesPeak HorsepowerPeak TorqueMaximum RPMRPM PotentialCarburetor CFMVolumetric Efficiency1/4 Mile ET and MPH1/8 Mile ET and MPHCompression Ratio

Controllable InputsCylinder BoreCrankshaft StrokeCompression RatioIntake Port cc'sCylinder Head FlowValve SizesPorting Levels

Carb Spacer HeightLifter DesignIntake DurationExhaust DurationIntake CenterlineLobe SeparationLift at CamLift at ValvesRocker Arm DesignRocker Arm RatioIntake Design

Carburetor DesignFuel Injection DesignInjector Flow RateCarburetor CFMExhaust DesignOpen HeadersMuffler DesignElectric Fuel PumpElectric Water Pump

Computer ControlTotal TimingHigh Speed RetardPulley Under DriveFuel Octane LevelNitrousTurboBlowerVehicle WeightDriver WeightSTP or SAE Results

7.1.2 engine anylayzerThe interferance

7.1.3 gt suiteCapabilityTorque and power curves, airflow, vol. efficiency, fuel consumption, emissionsSteady state or full transient analysis, under any driving scenarioTurbocharged, supercharged, turbocompound, e-boost, pneumatic assist10 SI, DI, HCCI and multi-mode combustion, multi-fuel, and multi-pulse injectionInfinitely variable valve timing and lift (VVT and VVL)Acoustic analysis of intake and exhaust systemsManifold and cylinder component thermal analysis, with included FE solverControls system modeling, via built-in controls library or Simulink couplingHow GT- suite works

The analysis

From the analysis and the result GT-suite give the best data In-Cylinder Finite Element Temperature Solution

Advanced Turbocharging Models

Analysis of Measured Cylinder Pressure

Example of the result

Exhaust AftertreatmentThe system interferance

Efficient Solvers Compatible with RT SimulationThe fast and efficient Quasi-steady (QS) flow solver is compatible with RT model requirements for system simulationUsing built-in tools, AT models can be transformed into neural network (NN) models to achieve 1-2 orders of magnitude higher computational speed for XiL applicationComplex integrated model can be virtually sectioned into separate circuits in order to achieve RT performance without sacrificing accuracy and interactions between the sub-systems

Quasi 2-D/3-D flow/heat transfer modeling to simulate multi-D behavior of AT components. Non-uniform distributions of flow rate, temperature, and all species can be supplied to the AT model.

End of lecture