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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.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

Acoustics comfort is a key point for the ground transportation market and in particular in the automotive area. A significant contributor to the noise levels in the cabin in the range 200Hz to 3000Hz is the HVAC (Heating, Ventilating, and Air Conditioning) system, consisting of sub-systems such as the air intake duct, thermal mixing unit, blower, ducts, and outlet vents. The noise produced by an HVAC system is mainly due to aeroacoustics mechanisms related to the flow fluctuations induced by the blower rotation. The structure borne noise related to the surface induced vibrations and to the noise transmission through the dash or plastic panels may also contribute but is not considered in this study. This study presents a digital approach for HVAC aeroacoustics noise predictions related to the ducts and outlet vents. In order to validate the numerical method flow and acoustics measurements are performed on production HVAC systems placed in an anechoic room.

Nowadays vehicle quality is rated for noise and vibration and the interior sound levels have become a major target of automotive companies. Strides have been made in reducing power train, tire and external wind noise over the years. However, HVAC and blower fan flow-induced noise reaches the interior cabin without any sound isolation and can strongly impact customer comfort. In the early stage of vehicle design, it is experimentally difficult to get an estimate of the flow pattern and sound levels. The goal of this study is to develop and validate a numerical noise prediction tool for complete HVAC systems noise, defined as the arrangement of sub-systems such as air intake duct, thermal mixing unit, blower, ducts and outlet vents. This tool can then be used during the development of vehicles to evaluate and optimize the aeroacoustics performances of the system without additional or belated experiments.

Design of HVAC system plays an important role in acoustic comfort for passengers. With automotive world moving towards electrical vehicles where powertrain noise is low, designing low noise HVAC system is becoming more important. For an automobile manufacturer, ability to predict the production vehicle cabin noise at the early design stage is important as it allows more freedom for design changes, which can be incorporated in the vehicle at lower cost. Although HVAC prototype and system level testing at early design stage is possible for noise estimation but flow field is not visible in test that makes difficult to improve design. CFD simulation can provide detailed information on flow field, noise source strength and location. But in such a simulation, accurate prediction has been a challenge due to the inability of CFD tools to model acoustic absorptive characteristics of interior walls of cabin.

The demand for low noise level in vehicle cabin continues to rise lately. In particular, noise generated by eco-friendly cars such as hybrid and electric ones tends to become lower and lower. In this market environment, the noise contributions caused by HVAC systems are also increasing. Therefore, it becomes increasingly important to accurately predict noise generated by HVAC systems and analyze the noise sources and resolve the noise issue. In this study, direct acoustics prediction approach based on Lattice Boltzmann Method is applied to predict the flow-induced noise from HVAC systems including blower and ducts and find noise sources. In order to validate the simulation result, acoustics measurements are performed on HVAC systems in an anechoic room and the results are compared to each other. A new technique is applied to finding a noise source for a specific frequency and shows improved noise level through modifying the geometry related to noise sources detected by the simulation.

With the rise of electric autonomous vehicles, it has become clear that the cabin of tomorrow will drastically evolve to both improve ride experience and reduce energy consumption. In addition, autonomy will change the transportation paradigm, leading to a reinvention of the cabin seating layout which will offer the opportunity to climate systems team to design quiet and even more energy efficient systems. Consequently, Heat and Ventilation Air Conditioning (HVAC) systems designers have to deliver products which perform acoustically better than before, but often with less development time. To success under such constraints, designers need access to methods providing both assessment of the system (or subsystems) acoustic performance, and identification of where the designs need to be improved to reduce noise levels. Such methods are often needed before a physical prototype is requested, and thus can only be achieved in a timely manner through digital testing.