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One of the key inputs 1-D transient simulation takes is a detailed front end cooling flow map. These maps that are generated using a full vehicle Three-dimensional Computational Fluid Dynamics (3D CFD) model require expensive computational resources and time. This paper describes how an adaptive sampling of the design space allowed the reduction of computational efforts while keeping desired accuracy of the analysis. The idea of the method was to find a pattern of Design of Experiments (DOE) sampling points for 3D CFD simulations that would allow a creation of an approximation model accurate enough to predict output parameter values in the entire design space of interest. Three procedures were implemented to get the optimal sampling pattern.

Acoustic comfort of automotive cabins has progressively become one of the key attributes of passenger comfort within vehicle design. Wind noise and the heating, ventilation, and air conditioning (HVAC) system noise are two of the key contributors to noise levels heard inside the car. The increasing prevalence of hybrid technologies and electrification has an associated reduction in powertrain noise levels. As such, the industry has seen an increasing focus on understanding and minimizing HVAC noise, as it is a main source of noise in the cabin particularly when the vehicle is stationary. The complex turbulent flow path through the ducts, combined with acoustic resonances can potentially lead to significant noise generation, both broadband and tonal.

The performance of ground vehicles of all types is influenced by the cooling and ventilation of the engine compartment. An increased heat load into the engine compartment occurs after engine shut down. Heat is transferred from the hot components within the engine compartment by natural convection to the surrounding air and by radiation to the adjacent surfaces. The heat is then dissipated to the ambient mostly by convection from the exterior surfaces. The objective of this study is to develop a Computational Fluid Dynamics (CFD) simulation methodology to predict the airflow velocity and temperature distributions within the engine compartment, as well as the surface temperature of critical engine components during the after-boil condition. This study was conducted using a full-scale, simplified engine compartment of an armored combat vehicle. Steady-state simulation was performed first to predict the condition prior to engine shut down.

Thermophysical properties of materials used in the design of automotive interiors are needed for computer simulation of climate conditions inside the vehicle. These properties are required for assessment of the vehicle occupants' thermal sensation as they come in contact with the vehicle interior components, such as steering wheels, arm rests, instruments panel and seats. This paper presents the results of an investigation into the thermophysical properties of materials which are required for solving the non-linear Fourier equations with any boundary conditions and taking into account materials' specific heat, volume density, thermal conductivity, and thermal optical properties (spectral and total emissivity and absorptivity). The model and results of the computer simulation will be published in a separate paper.

The demand for seating comfort is growing - in cars as well as trucks and other commercial vehicles. This is expected as the seat is the largest surface area of the vehicle that is in contact with the occupant. While it is predominantly luxury cars that have been equipped with climate controlled seats, there is now a clear trend toward this feature becoming available in mid-range and compact cars. The main purpose of climate controlled seats is to create an agreeable microclimate that keeps the driver comfortable. It also reduces the “stickiness” feeling which is reported by perspiring occupants on leather-covered seats. As part of the seat design process, a physical test is performed to record and evaluate the life cycle and the performance at ambient and extreme temperatures for the climate controlled seats as well as their components. The test calls for occupied and unoccupied seats at several ambient temperatures.

Automotive Heating Ventilation and Air Conditioning (HVAC) system is essential in providing the thermal comfort to the cabin occupants. The HVAC noise which is typically not the main noise source in IC engine vehicles, is considered to be one of the dominant sources inside the electric vehicle cabin. As air is delivered through ducts and registers into the cabin, it will create an air-rush/broadband noise and in addition to that, any sharp edges or gaps in flow path can generate monotone/tonal noise. Noise emanating from the HVAC system can be reduced by optimizing the airflow path using virtual tools during the development stage. This paper mainly focuses on predicting the noise from the HVAC ducts and registers. In this study, noise simulations were carried-out with ducts and registers. A Finite Volume Method (FVM) based 3-dimensional (3D) Computational Fluid Dynamics (CFD) solver was used for flow as well as acoustic simulations.

Cooling airflow is an essential factor when it comes to vehicle performance and operating safety. In recent years, significant efforts have been made to maximize the flow efficiency through the heat exchangers in the under-hood compartment. Grille shutters, new fan shapes, better sealings are only some examples of innovations in this field of work. Underhood cooling airflow simulations are an integral part of the vehicle development process. Especially in the early development phase, where no test data is available to verify the cooling performance of the vehicle, computational fluid dynamics simulations (CFD) can be a valuable tool to identify the lack of fan performance and to develop the appropriate strategy to achieve airflow goals through the heat exchangers. For vehicles with heat exchangers in the underhood section the airflow through those components is of particular interest.