The COM interface, developed by Microsoft®, provides a standardized interface for programs to communicate with each other.
KULI has a set of built-in COM commands, which allow other programs to run and control a KULI simulation.
The current example is a simple demonstration of KULI controlled by Microsoft EXCEL. For a certain cooling system the mechanical fan is varied and its performance regarding mass flow and power demand is output. Input and output parameters in the KULI file are defined by so-called COM objects.
The example is based on “ExTruck.scs” from the KULI installation setup.
Usable from release: KULI 8.0-1.04
The COM interface, developed by Microsoft®, provides a standardized interface for programs to communicate with each other.
KULI has a set of built-in COM commands, which allow other programs to run and control a KULI simulation. KULI “Direct Access” allows to set and get component parameters of a cooling system without defining COM-objects in the *.scs-file. Hence, using Direct Access, a KULI file does not have to be prepared to be controlled by external programs but can be accessed directly, “as it is”. For the user this leads to a remarkable advantage regarding set-up time of the KULI cooling system. The current Excel sheet enables to list all accessible components of a defined cooling system. Furthermore, a list of all possible direct access attributes is provided.
Usable from release: KULI 14
The COM interface, developed by Microsoft®, provides a standardized interface for programs to communicate with each other. KULI has a set of built-in COM commands, which allow other programs to run and control a KULI simulation.
The current example is an Excel sheet which is created for the control and simulation of one steady state operating point of a cooling system. The certain benefit of this Excel sheet is, that no Visual Basic programming knowledge of the user is required. Input and output parameters of a KULI file can simply be defined in a list, where the parameters can be chosen from an interactive menu. The sheet allows access to standard KULI COM objects but also to components directly via the KULI Direct Access interface. If optimization parameters and targets are set in the KULI *.scs-file, one can simply run the optimization from Excel by activation of the “Run Optimization” option.
Usable from release: KULI 8.0-1.04
In a real cooling package the air is not always guided through sealed shrouds, so there exist several leakages.
With KULI it is possible to model such leakages and even recirculation paths.
This example is based on the Tutorial Example ExTruck.
It shows how to model a leakage and a recirculation path such that the ratio of the air mass flow through radiator / inlet grid varies for different operating points between 70% – 130%.
The leakage is modeled via an area resistance below the main cooling package and the recirculation path is regulated via a second built in resistance.
The advantage of this modeling is that there is used the same cp-value and the same built-in-resistance for several operating points.
Usable from release: KULI 9.1-0.01
KULI advanced offers an optimization toolbox which can be used for quick parameter variation on one hand, and automatic minimization, maximization or goal seek on the other hand.
The current example is a cooling system with goal seek on two targets, and two parameters respectively. The speed of the mechanical fan and the heat rejection of the radiator are adjusted to hit the target of a given radiator top hose temperature and a given charge air exit temperature. The cooling system is based on tutorial example ExCar.scs from the KULI Setup.
Usable from release: KULI 8.0-1.04
KULI advanced offers an optimization toolbox which can be used for quick parameter variation on one hand, and automatic minimization, maximization or goal seek on the other hand. Based on those functions it is possible to perform statistical analysis as well.
This example shows the application of the Monte Carlo Method in KULI. The basic idea is that some input parameters do have a certain degree of uncertainty. In this example we assume that the charge air temperature has a temperature of 150°C, but we are not sure, so we apply a normal distribution with mean 150°C and a standard deviation of 10 K. Furthermore we assume that the built in resistance has a zeta of 400, again with some uncertainty resulting in a normal distribution with mean 400 and standard deviation of 10. And finally we assume that we don’t really know the exit cp-value; since we can’t even guess a mean value we apply a uniform distribution between -0.4 and -0.2. When we run this model we choose „Monte Carlo Simulation“ with a sample size of e.g. 500. A possible output is mean value and standard deviation of water and charge air temperatures.
Usable from release: KULI 8.0-1.04
KULI advanced offers an optimization toolbox which can be used for quick parameter variation on one hand, and automatic minimization, maximization or goal seek on the other hand.
This example shows how to simulate a component test rig preserving constant air pressure drop. Based on this method you can compare the performance of different radiators taking into account that a radiator with lower pressure drop allows more air flow such that the overall performance might be better than in the case of a radiator with better heat transfer characteristic but higher pressure drop. The optimization target is set to a given pressure difference and the fan rpm is optimized such that the demanded delta p will be achieved. Choose “Parameter Variation” after clicking the Analysis button!
Usable from release: KULI 8.0-1.04
The supercharger provides more oxygen for combustion to the engine than it is available for the naturally aspirated engine.
KULI provides the tools to create a calculation model of a supercharger by oneself. Using sensors, actuator and calculation objects the performance of the supercharger can be computed. Based on the input information like piston displacement, engine power, engine speed, the entry pressure, the entry charge air mass flow and the entry temperature into the charge air cooler is calculated. For a better overview of the complete system the model is packed into a KULI subsystem.
Usable from release: KULI 8.0-1.04
KULI advanced offers an optimization toolbox which can be used for quick parameter variation on one hand, and automatic minimization, maximization or goal seek on the other hand.
The objective of the current examples is the calibration of the simulation model to measured temperatures by adjusting the Resistance Parameter of the Built-In-Resistance. This adjustment can be done automatically using the KULI optimization toolbox. Two variants for the calibration are presented. Variant 1 shows how to set up the optimization controllers if the user wants to find the optimum parameter for each single operating point. Variant 2 shows how to set up the optimization controllers if the user wants to find one optimum parameter for all operating points. The cooling system is based on tutorial example ExCar.scs from the KULI Setup.
Usable from release: KULI 8.0-1.04
A fin and tube heat exchanger offers a complex refrigerant flow pattern. Usually starting from multiple inlet tubes the refrigerant passes the heat exchanger similar to serpentine flow but in several tube rows.
The KULI model for fin and tube heat exchangers offers a possibility to connect each single tube of the heat exchanger in accordance to the real flow configuration.
In this example a fin and tube evaporator is used instead of a plate evaporator. It is based on the example “Ex_AC.scs” from the KULI installation setup.
Usable from release: KULI 8.0-1.04