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As a potential replacement to traditional automotive R134a direct expansion (DX) systems, a secondary-loop system allows for the usage of flammable but low-GWP refrigerants such as propane (R290). However, as the secondary-loop system has an additional layer of thermal resistance, the cycle's transient behavior and cabin thermal comfort during pull-down and various driving cycles may be different from traditional DX systems. This paper presents a Modelica-based model to simulate both steady-state and transient operation of automotive secondary-loop systems. The model includes a lumped cabin component and a secondary-loop automotive air-conditioning system component. The air-conditioning system component consists of a condenser, a compressor, an expansion device, a coolant plate type heat exchanger, a coolant to air heat exchanger and a coolant pump. The developed model was validated against both steady-state and transient experimental data for an R290 secondary-loop system.

The thermal comfort inside automotive cabin has been extensively studied for decades. Traditional CFD models provide accurate simulation results of the air temperature distributions inside cabins but at a relatively high computation cost. In order to reduce the computational cost while still providing reasonable accuracy in simulating the air temperature profile inside a mid-sized sedan cabin, this paper introduces a new simulation tool that utilizes a proper orthogonal decomposition (POD) method. The POD method, an interpolation technique, requires only one set of multiple CFD simulations to produce a set of “snapshots”. Later, any simulations that require CFD runs to solve algorithm equation sets can be simplified by using interpolation between the snapshots provided that the geometry of the cabin keeps the same. As a result, the computation time can be reduced to only a few minutes.

Complex engineering design optimization often requires multiple executions of computationally expensive simulation tools such as those based on Computational Fluid Dynamics (CFD). Some CFD simulations can take several hours to complete, thus potentially making the design optimization task infeasible. In this paper, a combination of two powerful methodologies is presented that has the potential of reducing the engineering time required for CFD based design by more than 90%. The first methodology, termed as Parallel Parameterized CFD (PPCFD) allows for speeding up multiple CFD runs to explore a given design space very efficiently. The second approach is Approximation Assisted Optimization (AAO). AAO techniques are used to reduce the time and effort involved in conducting optimization with computationally expensive simulations. The PPCFD methodology needs to be tailored or customized for an individual geometry of interest.

Computer simulation tools for modeling heat exchanger performance can be effective aids in the design, and optimization of heat exchangers. This paper presents a model that has been developed to simulate the performance of flat tube, louvered fin heat exchangers of the type used for automotive applications such as radiators and charge air coolers. Two different types of fin can be modeled-louvered plate fins and louvered corrugated fins. A segment-by-segment modeling approach is employed in which each tube is divided into multiple segments in order to account for heterogeneous fluid flow and to allow for two-dimensional air maldistribution. The energy transfer and the hydraulic equations are solved for each segment. A variety of working fluids such as air, water-glycol, and most refrigerants can be modeled. Multiple correlations are available to model heat transfer coefficients and friction factors for the fluid inside the tubes as well as for the air side.