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Energy efficient HVAC system is becoming increasingly important as higher Corporate Average Fuel Economy (CAFE) standards are required for future vehicle products. The present study is a preliminary attempt at designing energy efficient HVAC system by introducing localized heating/cooling concepts without compromising occupant thermal comfort. In order to achieve this goal of reduced energy consumption while maintaining thermal comfort it is imperative that we use an analytical model capable of predicting thermal comfort with reasonable accuracy in a non-homogenous enclosed thermal environment such as a vehicle's passenger cabin. This study will primarily focus on two aspects: (a) energy efficiency improvements in an HVAC system through micro-cooling/heating strategies and (b) validation of an analytical approach developed in GM that would support the above effort.

Spot, or distributed, cooling and heating is an energy efficient way of delivering comfort to an occupant in the car. This paper describes an approach to distributed cooling in the vehicle. A two passenger CFD model of an SUV cabin was developed to obtain the solar and convective thermal loads on the vehicle, characterize the interior thermal environment and accurately evaluate the fluid-thermal environment around the occupants. The present paper focuses on the design and CFD analysis of the energy efficient HVAC system with spot cooling. The CFD model was validated with wind tunnel data for its overall accuracy. A baseline system with conventional HVAC air was first analyzed at mid and high ambient conditions. The airflow and cooling delivered to the driver and the passenger was calculated. Subsequently, spot cooling was analyzed in conjunction with a much lower conventional HVAC airflow.

In today's highly competitive marketplace and ever-shrinking vehicle development cycle, automotive HVAC engineers are constantly challenged to develop systems that deliver adequate thermal comfort at lower cost and higher fuel-efficiency. However, in the absence of a reliable predictive tool that is capable of quantifying thermal comfort early in the vehicle development program, OEMs employ expensive and time-consuming human subject test rides to assess HVAC system's performance. In order to address this issue, a Computational Fluid Dynamics (CFD) model of a virtual thermal manikin in a passenger cabin is developed in this study. The model is capable of providing thermal sensations, as experienced by humans, under any arbitrary thermal environment. Additionally, the model can provide sensitivity of various critical parameters, such as solar load, A/C discharge outlet air flow-rate and temperature, A/C outlet locations, various HVAC modes etc., to thermal sensation.

The main objective of this work is to demonstrate the merits of the Adjoint method to provide comprehensive information for shape sensitivities and design directions to achieve low drag vehicle shapes. The adjoint method is applied to a simple 2D airfoil and a 3D vehicle shape. The discrete Adjoint equations in the flow solvers are used to investigate further potential shape improvements of the low drag vehicle shapes. The low drag vehicle used in this study was designed earlier using the conventional approach (i.e., extensive use of wind tunnel testing). The goal is to use the already low drag vehicle shape and reduce its drag even further using the adjoint methodology without using the time-consuming and the high cost of wind tunnel testing. In addition, the present study is intended to compare the results with the other computational techniques such as surface pressure gradients method.

The focus of this study is to validate the predictive capability of a recently developed physiology based thermal comfort modeling tool in a realistic thermal environment of a vehicle passenger compartment. Human subject test data for thermal sensation and comfort was obtained in a climatic wind tunnel for a cross-over vehicle in a relatively warm thermal environment including solar load. A CFD/thermal model that simulates the vehicle operating conditions in the tunnel, is used to provide the necessary inputs required by the stand-alone thermal comfort tool. Comparison of the local and the overall thermal sensation and comfort levels between the human subject test and the tool's predictions shows a reasonably good agreement. The next step is to use this modeling technique in designing and developing energy-efficient HVAC systems without compromising thermal comfort of the vehicle occupants.

Fuel economy and stringent emissions requirements have steered the automotive industry to invest in advanced propulsion hybrids, including Plug-in hybrid vehicles (PHEV) and Fuel cell vehicles. The choice of battery technology, its power and thermal management and the overall vehicle energy optimization during different conditions are crucial design considerations for PHEVs and battery electric vehicles (BEV). Current industry focus is on Li-Ion batteries due to their high energy density. However, extreme operating temperatures may impact battery life and performance. Different cooling strategies have been proposed for efficient thermal management of battery systems. This paper discusses the modeling and analysis strategy for a thermally managed Lithium Ion (Li-Ion) battery pack, with coolant as the conditioning medium.