CASE STUDY ON FRM MODELING USING GT POWER TOOL

Aim:-

• Build FRM Model for following configuration using FRM builder approach
• Bore 102 mm stroke 115 mm CR 17
• No of cylinder 6
• CI engine
• Twin Scroll Turbine
• GT Controller
• Run all cases
• Explore tutorial number 9 and write a detailed report

Solution1:

Build FRM Model for following configuration using FRM builder approach:-

• Bore 102 mm stroke 115 mm CR 17
• No of cylinder 6
• CI engine
• Twin Scroll Turbine
• GT Controller
• Run all cases

Solution:-

• Building of FRM Model as shown below figures
• Go to the tools and select the FRM builder

Step1:-

Step 2:- Enter values for bore,stroke and CR

• Bore = 102 mm
• Stroke = 115 mm
• CR = 17

Step 3:-

• Select Twin scroll turbine

Step 4:-

• Select 6 cylinder

Step 5:-

• Select controller and done with the finish
• Final model we Building the FRM model as shown in the below

Results:-

Conclusion:

• Building of FRM model was done.
• We get the results by using GT-Post.

2. Explore tutorial number 9 and write a detailed report

Solution:-

INTRODUCTION:-

Fast Running Engine Models are dynamic, fully-physical engine models that are designed specifically to run fast. While high-fidelity engine models are commonplace in the engine performance department, they are often too slow running to incorporate into system level models where long transient events may be simulated, or where the simulation model must respond faster than real-time, such as for HiL (Hardware-in-the-loop) simulations. When simulation speed is of priority, high fidelity GT-POWER engine models can be simplified into FRMs using a standard conversion process. It is up to the user how far to simplify the model, depending on the accuracy-vs-runtime requirement. FRMs are able to achive such fast run times by two means:

1. Increasing the simulation time step size and
2. Decreasing the number of calculations per time step.

These two means are often accomplished at the same time by lumping various flow volumes together which will reduce the total number of subvolumes and also allow for a larger time step size by increasing the effective subvolume lungth (which is responsible for the time step size). In addition to simplifying and combining flow volumes, there are additional solver options that can reduce the number of calculations per time step and thus, further decrease the run time without changing the time step size.

This tutorial covers the process of creating a Real-Time capable Fast Running Engine Model from a detailed, high-fidelity engine model. While this tutorial shows a specific set of steps, note that each engine model is unique and so the steps required to convert a detailed model will depend on the complexity of the model, as well as on the goals of the end user. For certain applications, such as vehicle thermal management where engine coolant heat rejection must be maintained, the procedure may differ slightly in order to maintain certain key results. While this FRM process will focus on preserving general engine performance results, special considerations will be noted along the way.

Building a FRM Model:-

Launch GT-ISE and open the file SI_4cyl_GDI_Turbo-WOT.gtm from ‘File’-‘Examples’-‘Engine_1D_Gas_Exchange_Combustion’-‘Gasoline-SI_4cyl_GDI_Turbo’. This is the starting model for this tutorial. Before making any changes to the model, save the model to a local directory and run the solver to generate results that will be used for calibration and comparison of the FRM. This model is a 4-cylinder 2.0L turbocharged Gasoline Direct Injection (GDI) engine. The turbine waste gate is being dynamically controlled in order to target BMEP. A full-load speed sweep is being simulated from 5000 RPM down to 1000 RPM. A semi-predictive charge air cooler is included such that the outlet temp is predicted as a function of inlet gas temp and mass flow rate, coolant temp, and CAC effectiveness.

• After run this model we can observe the simulation time it has been taken and it takes more time as compared to FRM because of this model contains number of subvolumes.
• The RLT Contour map can also be used to check the number of subvolumes for each pipe modeled. The more subvolumes are used to slower the excution time will be. The Number of subvolumes can be selected under pipes/Flowsplits-Flowcontrol-Number of subvolumes and RLT contour map as shown in the below figure.

This course will cover the creation of Fast Running Engine Models (FRMs) from their detailed equivalent, so they can be used in a variety of integrated simulations. FRMs execute much more rapidly than the typical detailed GT-POWER engine model, and are ideal for integrating with other vehicle systems where an accurate and predictive engine plant model is desired and where computational speed is critical. FRMs adapt to changing conditions (e.g. valve timing, spark/injection timing, turbo lag, external temperature, altitude, cooling system conditions, etc.) without the need to apply non-physical correction factors. Whether studying changes to ambient conditions, or simulating events that are heavily transient in nature, FRMs will maintain the predictive capabilities of a detailed engine model while allowing for the fast computational speeds that are expected when performing drive cycle analysis and other transient-focused simulations.

Some examples of applications that are ideal for FRMs are:

• ECU Modelling (including HiL) – where a fast-running and transient-capable engine model is essential for optimizing ECU strategy
• Engine + Drive train/Vehicle – where accurate torque pulsations are key for optimizing drive train design and strategy
• Vehicle Thermal Management modelling, where the engine provides the heat to the cooling system, and the cooling system behaviour feeds back into the engine performance predictions (great for simulating off-ambient conditions)
• And many more.