This example shows how to automatically stop a transient KULI simulation if a given signal has become stationary.
In this example a stop controller is used to check if a certain signal has converged. The convergence itself is checked with the help of a series of delay controllers and a calculation controller. So the signal value at the current time t and at the time steps t-10, t-20, t-30, t-40, and t-50 seconds are evaluated. If the difference between the maximum and the minimum of these values is smaller than the value specified in the stop controller, then the simulation is stopped. In the given example the stop criterion is 0.1 K.
The big advantage of using the stop controller is that you can specify a very long simulation time (in the simulation parameters) such that it is ensured that convergence will occur, but if the convergence occurs pretty early, then KULI stops and does not produce “unnecessary” simulation output.
The calculation of this convergence value is put into a subsystem such that it can easily be transferred to other models.Usable from release: KULI 11
With this model the porosity coefficients for the air side resistance of a radiator can be calculated. This makes it easier to use the same air side resistance of a radiator in KULI and in CFD.
In standard underhood CFD calculations the heat exchangers (radiator, charge air cooler, condenser, etc.) are modeled as porous media. If a radiator is available as a KULI file, then this KULI model can be used to obtain the required coefficients which define the resistance of the radiator in the CFD model. In StarCCM+© (from cd-adapco) the resistance is defined in the following way:
delta p / L = alpha * v^2 + beta * v
where delta p is the static air side pressure difference, L is the depth of the radiator, v is the velocity perpendicular to the radiator surface, and alpha and beta are the coefficients that need to be evaluated. The KULI model makes a parameter variation for the velocity, where the lower and upper bounds can be specified as constants (they are predefined with 1 and 10 m/s, which is a reasonable range for most applications). The velocity is converted into a volume flow with the help of the width and height of the radiator. An analysis controller is used to calculate the sum of the deviations between simulated pressure difference at the component and the pressure difference calculated with the approximation formula. The sum of all these deviations is then put into an optimization target which is set to be a minimum. The coefficients alpha and beta serve as optimization parameters. (Usually these coefficients are in a range of up to 1000 or at most 1500, so this can be taken as a range for the optimization parameters.)
The example can easily be modified to include different formulas for porosities as used by other CFD codes.Usable from release: KULI 10.1
Thermostat to control the mass flow through two different branches.
With the subsystem Thermostat it is possible to control the mass flows through two different branches. Over the temperature of the 1.PM fluid resistances are increased or decrease over 2D curves.
To adjust the behavior of the thermostat to your own thermostat the following parameters have to be adjusted:
Usable from release: KULI 9.1-0.01
This example shows how a simple steady states simulation for a steam circuit of a truck – using ethanol as working fluid – can be set up. It consists of the steam circuit itself (closed circuit), an exhaust gas circuit (as source of the heat) and an open water/glycol circuit which acts as heat sink (condenser). Two evaporators are used as heat sources – one in the EGR system and one in the main exhaust system.
The rankine circuit is – similar to the A/C circuit – a thermodynamic cycle. The principle works like this:
In a first step the feed pump provides the working fluid for the expansion device, whereby the steam valves are used for controlling this system. They can either set the exit temperature at the evaporator or a defined mass flow. In this example two valves are used: One for the exhaust gas recirculation path (EGR path) and one for the main exhaust gas path.
In a next step the evaporator transfers the energy from the hot exhaust gas to the fluid and changes the medium’s state from liquid to gaseous. This energy is converted in the expansion device (if not bypassed) to mechanical power and cooled down in the condenser (to guarantee a liquid state for the feed pump).Usable from release: KULI 10
This example shows how a simple steady states simulation for a steam circuit of a truck – using ethanol as working fluid – can be set up. It consists of the steam circuit itself (closed circuit), an exhaust gas circuit (as source of the heat) and an open water/glycol circuit which acts as heat sink (condenser).
The rankine circuit is – similar to the A/C circuit – a thermodynamic cycle. The principle works like this:
In a first step the feed pump provides the working fluid for the expansion device, whereby the steam valve is used for controlling this system. It can either set the exit temperature at the evaporator or a defined mass flow. In a next step the evaporator transfers the energy from the hot exhaust gas to the fluid and changes the medium’s state from liquid to gaseous. This energy is converted in the expansion device (if not bypassed) to mechanical power and cooled down in the condenser (to guarantee a liquid state for the feed pump).
Based on the 2 dimensional characteristic, a 3D profile can be created by rotating the symmetric profile around the central axis. Based on this Profile, the pressure distribution of the fan can be added to the cooling package. Due to the uneven flow distribution, the performance of the cooling system will be influenced.Usable from release: KULI 9.1-0.01
These Excel Input sheets can directly be used to create KULI component files for speed and stage controlled fans. Additionally exiting component files can be imported and edited without a regular KULI installation.
For the use of these templates, KULI CompInterface and KULI MediaX are required!
KULI’s hvac components like the evaporator are based on a combination of geometrical and test data. To achieve a good accuracy of the model, a successful calibration is obligatory. This virtual test bench provides a model that supports the user to find the ideal calibration factors.
The evaporator is a core part of each HVAC system. In KULI, the model of the evaporator is based on a combination of geometrical and test data. In a first step all available geometrical data is defined directly in the component. Next, the simulation model is calibrated based on these input values by the use of various fitting values. These values influence the pressure losses at the refrigerant side and at the air side. Additionally they also effect the heat transfer for the refrigerant side and the air side as well as the condensate mass flow (evaporator) . The calibration can be done automatically in the KULI component, but for getting even more accurate results (with respect on specific simulation points) this Excel-KULI Co simulation test bench can be used.Usable from release: KULI 9.1-0.01
Due to constructive and performance reasons, indirect charge air coolers are more frequently used in state of the art cooling systems. Therefore this example demonstrates how a CCFC can easily be included in a steady state simulation model, whereby a low temperature radiator is added in the frontend and the coolant cooled cross-counter flow cooler (CCFC) is mounted next to the engine.
The KULI file shows the simulation model of a passenger car, including the main cooling circuit with the heat input of the engine, a simplified oil circuit and both sides of the indirect charge air circuit.
The CCFC is based on measurement values and geometrical input, therefore the data input differs from the traditional charge air cooler. At first, the user has to set up the geometrical properties and the configuration of the layers. In a next step, the measurement data defining the heat transfer and the pressure loss must be entered. The data can be input in a single table (no need for additional cold measurements of the pressure loss). To use this data, a calibration is obligatory. For the best result, the user can choose between different calibration methods like linear, quadratic or cubic.
The calibrated CCFC is included in the charge air circuit (outer side) and in a low temperature coolant circuit, which is located in front of the main radiator.Usable from release: KULI 10
By the flow of electric current, the Peltier Element can be used for cooling/heating – similar to a traditional heat pump. Due the fact that for a good performance a high electrical conductivity but a very low thermal conductivity is required, semiconductors are usually used for such elements.
Basically this example demonstrates the use of a Peltier element in a steady state cooling system. The model consists of a cold and of a hot side, whereby electric current is used to cool down an air flow. Both sides of the element are connected by a heat conduction element with a very small lambda value. Keep in mind that due to the use in a steady state model, the point mass is only used for modeling the heat transfer, therefore the simulation ignores the thermal inertia.
Basically the amount of heat rejected / absorbed by each side is the sum of the Peltier effect (current [A] * temperature of the cold side [K] * alpha [V/K]) and half the Joule heat (0.5*current [A] * current [A] *resistance [Ohm]). Cause of the current being squared for the Joule heat, at a certain point increasing the current will lead to a reduced cooling effect (for high currents the cooling effect can even turn into a heating effect).Usable from release: KULI 9.1-0.01
In this example phase change material (PCM) is connected to a fluid circuit.
Phase change material can store a high amount of energy due to its very high thermal inertia. This energy can e.g. used for a fast engine warm-up, to provide cooling performance in the HVAC system (evaporator) while no compressor is available, …
For the modeling of the phase change material, a subsystem containing a network of controllers is included. Additionally a virtual point mass (Phase Change Point Mass, only for internal calculation) is created and directly connected to the point mass in the fluid network. The heat is set at this virtual point mass, which directly sets the temperature at the coolant side PM.
The basic idea is that the sensible heat is calculated and only this “effective temperature changing” value is set at the virtual point mass. To take care of the melting / solidification energy, the actual change of enthalpy is calculated by a continuous evaluation. If the enthalpy is below / above the hold point, the subsystem can use the cp values for these areas and calculate the temperature change.
For simplification purposes, the cp value for the solid and for the liquid phase is constant, the change of enthalpy due to the phase change is considered in the melting heat.Usable from release: KULI 9.1-0.01
Usually the pressure loss in a component placed in the air path depends on the resistance, the mass flow rate and the temperature. Anyhow it could be useful to set a constant pressure loss. This can easily be done by the combination of a calculation controller with a media controller.Usable from release: KULI 9.1-0.01
The first order lag element (PT1) is a common element of the measurement and control technology. It can be used for the damping of an input signal, like demonstrated in this example.
Beside the input signal, the constant “T”, which adjusts how quickly the output value reaches the input value after a time step, is a necessary input value. The bigger the value of T, the longer it will take.
In this example, the controller input signal for the valve position of a circuit is filtered by a first order lag element (PT1).
This element is modeled by using KULIs default calculation controllers and controlling elements. For a good overview, they are grouped in the subsystem “PT1 – Element”.
The time-discrete formula is included in the 1st calculation controller. Necessary inputs are the simulation time step, the current input value and the output signal of the former time step.
Additionally the constant T is used to adjust how quickly the output value reaches the input value after a time step.
The PID controller outside the subsystem is used to set the limits (in this example the valve opening / closing position is limited between 5 und 95 percent).Usable from release: KULI 9.1-0.01
This model demonstrates how the air path for a pusher fan can be modeled in KULI. The focus is on the high resistance of the hub, which influences the flow distribution. To take care of this effect, the air path is split in separate segments.
To model the high resistance of the hub, an equivalent area resistance located in the air path is modeled. Therefore the circular area of the hub must be converted in a rectangular area resistance. In our experience, the zeta value (dimensionless resistance) of the area resistance should be 3 times higher than the zeta value of the radiator next to the hub.
The air path is split into several segments. A part of the air mass flow passes the resistance, the rest flows by. Due to this uneven resistance characteristic, the resulting uneven air mass flow leads to a temperature distribution.Usable from release: KULI 9.1-0.01
To optimize the fuel consumption, new concepts like the Thermo Electric Generator (TEG) may show potential. To analyze the possibilities of such system, the layout can be modeled in KULI and different concepts can be compared.
The model consists of an exhaust gas system (hot side) and a water circuit (cold side), whereby the electric power is generated out of this temperature difference.
The modeling of new concept like the TEG is a challenging task for each engineer. This example shows how such a model can be easily created with KULI “on-board” components.
Therefore a combination of calculation controllers, maps and circuits is used to describe the behavior of such a component.
Basically the model consists of two circuits, whereby each of them contains a point mass (hot and cold side of the TEG). Both PM are connected by heat conduction, the area for the heat transfer is calculated by the overall number of elements, the area of such an element and the thickness.
For the calculation of the TEGs performance, the characteristic is provided by a 2D curve which is based on the temperature difference between hot and cold side.Usable from release: KULI 9.1-0.01
Due to the little loss heat of modern (diesel) engines during warm-up, PTC (Positve Temperature Coefficient) heaters are used to guarantee the fast warm up of the cabin. The inner resistance of the PTC increases for higher temperatures, therefore the heating power is automatically reduced for high temperatures (caused by high inlet temperatures, low mass flows, …).
Usually the PTC is positioned next to the conventional cabin heater and is mainly used during the warm up phase of the engine. To reduce the fuel consumption, the PTC is deactivated if the heating power of the engine is sufficient. Due to the characteristic of the inner resistance which will reduce the current and therefore also the heating power for higher temperatures, no additional emergency shut of system is required.
In this example the model of the PTC is reduced to an air-side point mass, including the thermal inertia and heat transfer coefficient. The amount of heat is calculated by the inner resistance (2D map) and a calculation controller.
Additionally the heater will be turned off if the cabin (air ducts) temperature exceeds 60 deg.Usable from release: KULI 9.1-0.01
For higher driving velocities, the fan acts like an additional resistance and reduces the effective cooling mass flow. To avoid that effect, air flaps are included in the shroud. These flaps open in case of an “overblown” fan and the cooling air flow can directly pass by this flaps.
The air flaps are modeled by area resistances, their pressure loss characteristic is defined by a velocity depended map. To adjust the mass flow distribution between the air flaps and the shroud (fan), additional Build in Resistances (BiR) were used for the lower part of the radiator. The ratio of the resistances will directly influence the mass flow distribution.
In case of a fan driven air mass flow, the air flaps are closed. Therefore the resistance of the flaps in comparison to the BiR is very high. In case of an overblown fan (usually at high driving speeds) the resistance of the BiR is very high, in contrast the resistance of the open air flaps (area resistance) is quite small.Usable from release: KULI 9.1-0.01
Due to its thermal inertia, the charge air cooler will show a special transient behavior. Especially if the volume flow or the temperature changes, this influence can lead to deviations in the temperatures, pressure losses, … The example demonstrates a possibility how the user can take care of this effect and easily include the model in an existing KULI model.
To take care of the charge air coolers (CAC) thermal inertia, point masses (PM) are included. Basically two different types of PM are used in the model:
- Point mass at the air side (mass ~ 40% of the CAC overall mass)
- Point mass in the circuit (mass ~ 60% of the CAC overall mass)
A separation of the CAC into two parts in combination with 3 point masses (inner side) and 2 point masses at the air side shows a very realistic behavior.
A separation of the inner circuits’ point mass of 10%, 70% and 20% (based on 60% of the overall mass) is recommended. The heat transfer area is calculated from the dimensions of the fins (inner side) and from the CACs’ net dimensions (air side). For the heat transfer coefficient a separation into inner and outer side is recommended.
This subsystem calculates the averaged consumption per 100 km. The input data is based on the current fuel consumption of the engine model and the track length. To convert the consumption from kg/s to a volume flow (liters per 100 km), it’s necessary to input the fuel density.
This subsystem demonstrates how easy the actual fuel consumption of the engine can be converted into fuel consumption in liters per 100 km. Therefore a PID controller containing an Integrator is used to get the overall consumption in kg. To convert the mass into a volume, the value is divided by the fuel density (user input). Also the track length – which is a necessary input for the simulation – can be calculated by integrating the driving velocity (if necessary this must be additionally added by the user).
The output of that subsystem is the overall fuel consumption [kg] and the fuel consumption per 100 km.Usable from release: KULI 9.1-0.01
This subsystem calculates the heat flows in the cabin model. The system provides the amount of heat to the outlet air, the effective cooling power and the Heat flow to the ambient.
The calculation is done in the subsystem, whereby some additional data like the heat transfer values to the ambient must be input by the user.
This subsystem demonstrates how the heat flow in a cabin can be calculated. Three different types of heat flow are calculated:
- Heat to outlet air: The amount of heat lost via the discharged air
- Effective cooling power: How much heat is effectively used for the cool down of the air flow
- Heat flow to ambient: The amount of heat exchanged between the cabin and the ambience
Due to the fact that some of the values are defined directly in the component, they are not available as sensor. Therefore external controller inputs can be used to set these values by user defined constants. All other necessary information is connected by using the sensor path.
Several calculation controllers (in combination with media components) are used to calculate the amount of exchanged heat.
In KULI the user can choose between different ways how to model a battery. They mainly differ in the necessary amount of input data, the effort for the creation of the model and also in the level of detail of the results.
This example shows in a detailed way how to model an energy storage. The battery contains cells & modules, as well as the multi-dimensional housing. The electric model is based on a cell level R-C model, which also considers the capacitive behavior.
This example demonstrates the advanced modeling concept for a thermal-electric battery model. Each of the 8 modules is housed in the battery and includes 12 cells (overall 96 li-Ion pouch cells including the cooling plates). Beside the thermal inertias of the cells themselves, also a multi-directional model of the housing is included. Each side of the housing as well as the cells can be connected by heat conduction. To simulate the electric behavior, a cell based R-C model is used. On the one hand this model describes the electric properties (like SOC, open cell voltage, ..), on the other hand the thermal behavior of the cells. Beside averaged values, each cell temperature can be accessed. For that reason the model shows excellent opportunities for battery layout design and of course also for the development of the battery cooling system.Usable from release: KULI 9.1-0.01
In KULI different ways how to model a battery exist. They mainly differ in the necessary amount of input data, the effort for the creation of the model and also in the level of detail of the results.
This example shows the most reduced way how to model a battery. Therefore all cells, modules and housings of the battery are reduced to one single lumped mass model for the use in KULIs cell model.
This example loosely describes a liquid cooled Li-Ion traction battery with around 290 cells and an overall weight of 180kg. By the reduction to a lumped mass / cell model, the whole battery is reduced to a single mass with an averaged thermal heat capacity (cp value). The heat transfer surface is the sum of all single heat transfer surfaces (each cell is in contact with a liquid cooling plate), the heat transfer coefficient is modeled as function of the flow velocity. To convert the mass flow to a flow velocity, the overall cross section must be defined in the component parameters window.
Due to simplicity, the electric properties are reduced to a constant value resistance model. The values are based on the battery characteristics.
This way of modeling a battery is very fast and effective, with the limitation of getting averaged values. Therefore it’s very useful for the estimation of the (transient) heat input in the cooling system and for simulating the influence of the batteries’ inertia, but not for designing the batteries’ inner layout.Usable from release: KULI 9.1-0.01
This example shows a quite simple way how hysteresis can be modeled. The calculation controller differs between two cases, with respect on the previous operating state. To avoid that the temperature / fan RPM is oscillating around a certain value, a function is used.
To avoid a highly oscillating fan RPMs, a hysteresis in the controlling strategy is included. This is modeled by a calculation controller. If the temperature exceeds a certain value, the fan switches to the maximum RPM mode. Additionally this high RPM mode is also used, if the temperature is between the two temperature limits and the high RPM cooling mode is already active. In case of underestimating the lower activation border or in case of an active min. RPM mode & actual temperature between the limits, minimal RPM mode is selected. To avoid a logical loop, a delay controller is used for sensing the input speed of the fan.Usable from release: KULI 9.1-0.01
One possibility to set a target temperature in the cabin is to control the RPM of the blower (fan).
This example demonstrates how a subsystem including several calculation controllers can easily be added to an existing HVAC simulation system.
By adjusting the fan RPM, the cool down (heat up) performance of the cabin is influenced. This controlling strategy is included in a subsystem which mainly consists of calculation controllers.
As a necessary input, the user has to define a required cabin temperature and the upper and lower limit for the fan RPM. The calibration coefficient is a kind of RPM offset for the controller, used in each simulation time step.
If the average cabin temperature exceeds the upper temperature limit plus the temperature tolerance, the max. fan RPM is used.
In all other cases the fan RPM is reduced or increased by the calibration coefficient. Due to the change of the fan RPM in each simulation time step, a smooth control characteristic is created.Usable from release: KULI 13.1
One possibility to set a target temperature in the cabin is to control the amount of recirculation.
This example demonstrates how a subsystem including several calculation controllers can easily be added to an existing HVAC simulation system.
By adjusting the recirculation rate, the cool down ( heat up) performance of the cabin is influenced. This controlling strategy is included in a subsystem which mainly consists of calculation controllers.
As a necessary input, the user has to define a required cabin temperature and the upper and lower limit for the recirculation rate. The calibration coefficient is a kind of recirculation offset for the controller, used in each simulation time step.
If the average cabin temperature exceeds the upper temperature limit plus the temperature tolerance, the max. recirculation rate.
In all other cases the recirculation rate is reduced or increased by the calibration coefficient. Due to the change of the recirculation in each simulation time step, a smooth control characteristic is created.Usable from release: KULI 13.1