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Figure | (a) Hierarchy structure of the A/C model (b) Modelon A/C model layout AVIOGCION AAU TMOG! layOUr For this study, only models of the complete refrigerant system and the vehicle interior (cabin) were required to simulate the physics of interest. The plant models are Modelica-based and developed in Dymola 2015FDO01, utilizing component and refrigerant models from Modelon-supplied libraries. The structure and ayout of the A/C model package are shown in Figure 1. The Dymola package browser in the upper-left of Figure l(a) displays the package hierarchy and is shown with the A/C model selected. There are three sub-packages under the A/C model, namely, parameterized components, test benches, and A/C system model package. The parametrized components are specific, populated component models which are

Figure 1 | (a) Hierarchy structure of the A/C model (b) Modelon A/C model layout AVIOGCION AAU TMOG! layOUr For this study, only models of the complete refrigerant system and the vehicle interior (cabin) were required to simulate the physics of interest. The plant models are Modelica-based and developed in Dymola 2015FDO01, utilizing component and refrigerant models from Modelon-supplied libraries. The structure and ayout of the A/C model package are shown in Figure 1. The Dymola package browser in the upper-left of Figure l(a) displays the package hierarchy and is shown with the A/C model selected. There are three sub-packages under the A/C model, namely, parameterized components, test benches, and A/C system model package. The parametrized components are specific, populated component models which are

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The compressor control modulates the compressor speed based discharge determines temperature compressor using a PI pressure. The c speed to achieve discharge compressor speed is reduced and pressure exceeds on temperature request and refrigerant imate an appropriate target evaporator outlet profile and the compressor control sets the he target temperature control algorithm. control head If the compressor a specified limit, modulated using a PI controller to maintain a maximum allowed discharge pressure. Figure 3 Automotive air conditioning control systems
The compressor control modulates the compressor speed based discharge determines temperature compressor using a PI pressure. The c speed to achieve discharge compressor speed is reduced and pressure exceeds on temperature request and refrigerant imate an appropriate target evaporator outlet profile and the compressor control sets the he target temperature control algorithm. control head If the compressor a specified limit, modulated using a PI controller to maintain a maximum allowed discharge pressure. Figure 3 Automotive air conditioning control systems
Figure 4 Integrated A/C model as a DymolaBlock S- function in Simulink The first integration approach is using the DymolaBlock S-function interface. This Dymo option allows models developed in Dymola to b compiled as S-functions incorporated directly in Simulink, enabling the powerful physical modelin capabilities of the Modelica language to be combine with the controls orientated approach of Simulin Figure 4 depicts the A/C model integrated in Simulink as a DymolaBlock S-function. Oo 2 ag 0° on
Figure 4 Integrated A/C model as a DymolaBlock S- function in Simulink The first integration approach is using the DymolaBlock S-function interface. This Dymo option allows models developed in Dymola to b compiled as S-functions incorporated directly in Simulink, enabling the powerful physical modelin capabilities of the Modelica language to be combine with the controls orientated approach of Simulin Figure 4 depicts the A/C model integrated in Simulink as a DymolaBlock S-function. Oo 2 ag 0° on
Figure 5 Integrated A/C model FMU in Simulink In this application, we only consider the FMI for Co-Simulation option for two reasons. First, FMI for Model Exchange is very similar to utilizing an S- function function approach, like the DymolaBlock, as they both use the Simulink solver, and_ the DymolaBlock process is already incorporated into our modeling process. Second, due to the nature of the continuum behavior of the A/C system physics, and the need for a variable time step solver for the plant model, FMI for Co-Simulation allows the use of Dymola’s solver for the physics in conjunction with Simulink’s solver for the controls. Figure 5 shows an A/C model FMU in Simulink, with open loop inputs.
Figure 5 Integrated A/C model FMU in Simulink In this application, we only consider the FMI for Co-Simulation option for two reasons. First, FMI for Model Exchange is very similar to utilizing an S- function function approach, like the DymolaBlock, as they both use the Simulink solver, and_ the DymolaBlock process is already incorporated into our modeling process. Second, due to the nature of the continuum behavior of the A/C system physics, and the need for a variable time step solver for the plant model, FMI for Co-Simulation allows the use of Dymola’s solver for the physics in conjunction with Simulink’s solver for the controls. Figure 5 shows an A/C model FMU in Simulink, with open loop inputs.
The baseline performance for the A/C system model is defined as the physics-only Modelica model running the SC03 cycle open-loop in the Dymola environment, utilizing the DASSL variable time step with a solver tolerance of le-05. Baseline simulation run time was 185 seconds, about one third of the real cycle time of 600 seconds. Next, the S-functions version of the Dymola model was run open-loop in the Simulink environment. Due to the numerical stiffness of the mathematics, only the Simulink odel5s variable time solver was capable of reliable solutions, and we used a solver tolerance of le-05 to provide sufficient solution accuracy. The S-function simulation time averaged 183 seconds, essentially identical to the native-mode Dymola model. These results are shown as the first two bars in Figure 6. The actual SCO3 cycle time comparator of 600 seconds is the right-most bar in the figure. Figure 6. Comparison of the A/C system model computational performance
The baseline performance for the A/C system model is defined as the physics-only Modelica model running the SC03 cycle open-loop in the Dymola environment, utilizing the DASSL variable time step with a solver tolerance of le-05. Baseline simulation run time was 185 seconds, about one third of the real cycle time of 600 seconds. Next, the S-functions version of the Dymola model was run open-loop in the Simulink environment. Due to the numerical stiffness of the mathematics, only the Simulink odel5s variable time solver was capable of reliable solutions, and we used a solver tolerance of le-05 to provide sufficient solution accuracy. The S-function simulation time averaged 183 seconds, essentially identical to the native-mode Dymola model. These results are shown as the first two bars in Figure 6. The actual SCO3 cycle time comparator of 600 seconds is the right-most bar in the figure. Figure 6. Comparison of the A/C system model computational performance
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