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Flow noise from automotive HVAC (Heating, Ventilating and Air Conditioning) systems is one of the major considerations of occupant comfort. The noise generated at high blower speed is a major contributor to the vehicle interior noise. This paper reviews automotive HVAC air rush noise prediction models for estimating register, buck (air handling subsystem) and vehicle noise levels. The vehicle noise prediction method correlates well with measured noise levels at driver right ear location: with a standard deviation of 1.31 dB where standard deviation is the difference between measured and predicted noise levels for a sample size of 10 vehicles.

Customer clinics and surveys have revealed the increased importance to the customer of good defrost and demist performance in their vehicle. Achieving this level of performance, within the time and cost constraints of a modern vehicle development program, places increased reliance on computational (CAE) techniques. However, this paper describes how the optimum development process should be to combine this reliance upon CAE methods with a newly developed experimental technique. This new laser Doppler velocimetry (LDV) based methodology is employed at all stages of the development process and complements the CAE techniques perfectly. The end result is optimized airflow management within the vehicle cabin – essential if good defrost and demist performance is to be achieved in a vehicle.

GENPAD® is a knowledge-based, three-dimensional modeling computer tool developed by Visteon to create occupant-friendly interiors. GENPAD quickly and easily produces zones to evaluate ergonomic aspects of vehicle interiors such as reach, clearance, vision, and reflection. These zones are produced from automated design studies based on experience and engineering standards accepted by the automotive industry. Without GENPAD, a single study requires an experienced engineer 4-6 hours to complete. Multiple studies require several engineers weeks to perform. The methods used are also error-prone due to complex instructions. To overcome these challenges, GENPAD provides over 50 ergonomic packaging studies that produce accurate results in minutes, not weeks, every time.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and optimization of a hydraulic steering pump for NVH performance. DOE methods were applied to RPM-domain data to examine the effect of several different factors, as well as the interactions between these factors, on pump NVH. Whereas most DOE analyses typically consider only a single response variable, the present work considered multiple response variables. Specifically, pump NVH performance curves for several pump rotational orders over a range of shaft speeds were analyzed. Thus, it was possible to determine the effect of the factors in question over the entire speed range of pump operation, rather than a single speed or setting. Statistical methods were applied to determine which factors and interactions had a significant effect on pump NVH. These factors were used to construct an empirical mathematical prediction model for NVH performance.

Induction noise, which radiates from the open end of the engine air induction system, can be of significant importance in reducing vehicle interior noise and tuning the interior sound to meet customer expectations. This makes understanding the source noise critical to the development of the air induction system and the vehicle interior sound quality. Given the ever-decreasing development times, it is highly desirable to use computer-aided engineering (CAE) tools to accelerate this process. Many tools are available to simulate induction noise or, more generally, duct acoustics. The tools vary in degrees of complexity and inherent assumptions. Three-dimensional tools will account for the most general of geometries. However, it is also possible to model the duct acoustics with quasi-three-dimensional or one-dimensional tools, which may be faster as well.

In an effort to understand steering systems performance and properties at the microscopic level, we developed Multibody simulations that include multiple three-dimensional gear surfaces that are in a dynamic state of contact and separation. These validated simulations capture the dynamics of high-speed impact of gears traveling small distances of 50 microns in less than 10 milliseconds. We exploited newly developed analytic, numeric, and computer tools to gain insight into steering gear forces, specifically, the mechanism behind the inception of mechanical knock in steering gear. The results provided a three dimensional geometric view of the sequence of events, in terms of gear surfaces in motion, their sudden contact, and subsequent force generation that lead to steering gear mechanical knock. First we briefly present results that show the sequence of events that lead to knock.

An algorithm, which determines the range of a preceding vehicle by a single image, had been proposed. It uses a “Range-Window Algorithm”. Here in order to realize higher robustness and stability, the pattern matching is incorporated into the algorithm. A single camera system using this algorithm has an advantage over the high cost of stereo cameras, millimeter wave radar and non-robust mechanical scanning in some laser radars. And it also provides lateral position of the vehicle. The algorithm uses several portions of a captured image, namely windows. Each window is corresponding to a predetermined range and has the fixed physical width and height. In each window, the size and position of objects in the image are estimated through the ratio between the widths of the objects and the window, and a score is given to each object. The object having the highest score is determined as the best object. The range of the window corresponding to the best object becomes an estimated range.

Virtual design validation of an air induction system (AIS) requires a proper finite element (FE) assembly model for various simulation based design tasks. The effect of the urethane air filter seal within an AIS assembly, however, still poses a technical challenge to the modeling of structural dynamic behaviors of the AIS product. In this paper, a filter seal model and its modeling approach for AIS assemblies are introduced, by utilizing the feature finite elements and empiric test data. A bushing element is used to model the unique nonlinear stiffness and damping properties of the urethane seal, as a function of seal orientation, preloading, temperature and excitation frequency, which are quantified based on the test data and empiric formula. Point mobility is used to character dynamic behaviors of an AIS structure under given loadings, as a transfer function in frequency domain.

Engine air induction noise can play a significant role in the reduction of vehicle interior noise levels and tuning interior sound quality. Given the need to reduce prototyping and testing costs, it is important to gain an understanding of the level and frequency structure of the noise radiating from the open inlet of the air induction system. Engine simulation used independently can predict inlet noise; however, its utility is limited to systems that are largely one-dimensional. Systems that exhibit a three-dimensional nature, such as the wave dynamics in an engine air cleaner, require a more intensive approach. Boundary Element Analysis (BEA) has been demonstrated to be a tool that can be used to predict the frequency response of ducted systems and is particularly useful in highly three-dimensional systems.

A dynamic computer model of automotive air conditioning systems was developed. The model uses simulation software for the coding of 1-D heat transfer, thermodynamics, fluid flow, and control valves. The same software is used to model 3-D solid dynamics associated with mechanical mechanisms of the compressor. The dynamics of the entire AC system is thus simulated within the same software environment. The results will show the models potential applications in component and system design, calibration and control.

The era of the vehicle as a standalone non-connected entity is rapidly drawing to a close. The “Box” on four wheels is being opened to multiple communication channels based on consumer demand and expectations of the latest features, functions and content. Concurrently, automotive planners, marketers, engineers, and system architects are subject to increased complexity as a result of the rapidly evolving consumer electronics industry. This paper will discuss many of the limitations of existing automotive business models in attempting to successfully implement and meet consumer expectations. It will also propose a structural framework for automotive planners, marketers, engineers, and system architects to be able to better understand and predict consumer acceptance of electronics, multimedia features, and in-vehicle content access.