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In automotive infotainment systems, multiple types of digital audio signals are usually present. Some come from internal sources, such as a CD or USB stick, and some come from external sources, such as an internet stream or digital radio. These sources usually have different sample-rates, and may also be different from one or more system sample-rates. Managing and transporting these signals throughout the system over different sample-rate domains require detailed upfront architecture analysis and correct system design to ensure signal quality is maintained to the desired level. Incorrect design can add significant user-perceivable noise and distortion. This paper examines the key analysis factors, the effects of poor design and the approaches for achieving robust signal handling and ensuring desired signal quality.

The need for entertainment is a constant desire since human beans started to use vehicles for short and long distance travel. The radio, a home entertainment revolution, was the first one to be incorporated. The information and entertainment that initially brought the radio to the vehicles also started a major change on the interior and electrical systems. This revolution will require changes in vehicle design to accommodate the new concepts and features.

In this paper, an analytical procedure for prediction of shell radiated noise of air induction systems (AIS) due to engine acoustic excitation, without a prototype and physical measurement, is presented. A set of modeling and simulation techniques are introduced to address the challenges to the analytical radiated noise prediction of AIS products. A filter seal model is developed to simulate the unique nonlinear stiffness and damping properties of air cleaner boxes. A finite element model (FEM) of the AIS assembly is established by incorporating the AIS structure, the proposed filter seal model and its acoustic cavity model. The coupled acoustic-structural FEM of the AIS assembly is then employed to compute the velocity frequency response of the AIS structure with respect to the air-borne acoustic excitations.

Even though the use of LED's in automotive industry is continuously increasing, the test standards used for the thermal design of the lamps do not address the unique needs of LED based lamps. The challenge becomes more significant because LED's are semiconductor devices with lower maximum operating temperatures and photometric properties that depend on temperature. This paper presents sunload test results and lamp thermal data measured on vehicles undergoing simulated driving conditions in a lab environment. The data clearly indicates substantial differences in the measured data versus the test conditions to which the lamps are designed today. It is recommended to modify test standards that the lamps must meet to more closely emulate the field conditions.

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.

The quietness of the interior of automobiles is perceived by consumers as a measure of quality and luxury. Great strides have been achieved in isolating interiors from noise sources. As noise is reduced, in particular wind and power train noise, other noise sources become evident. Noise reduction efforts are now focused on components like power steering pumps. To understand the contribution of power steering pumps a world-class noise and vibration test stand was developed. This paper describes the development of the test stand as well as it's objective to understand and improve the sound quality of power steering pumps.

Analytical methods are used extensively in the automotive industry to validate the feasibility of component and assembly designs and their dynamic behavior. Correlation of analytical models with test data is an important step in this process. This paper discusses the Finite Element model of an innovative Slip-in-Tube Propshaft design. The Slip-in-Tube joint (slip joint) poses challenges for its dynamic simulation. This paper discusses the methods of simulating the joint and correlating it to experimental results. Also, the Noise and Vibration (NVH) characteristics of the Slip-in-Tube Propshaft design. In this paper, a Finite Element model of the proposed propshaft is developed using shell and beam element formulations. Each model is verified to optimize the feasibility of using accurate and computationally efficient elements for the dynamic analysis.

Reliable prediction of the radiated noise due to the air pressure pulsation inside air-intake manifolds (AIM) is of significant interest in the automotive industry. A practical methodology to model plastic AIMs and a prediction process to compute the radiated noise are presented in this paper. The measured pressure at the engine inlet valve of an AIM is applied as excitation on an acoustic boundary element model of the AIM in order to perform a frequency response analysis. The measured air pressure pulsation is obtained in the crank-angle domain. This pressure is read into MATLAB and transformed into the frequency domain using the fast Fourier transform. The normal modes of the structure are computed in ABAQUS and a coupled analysis in SYSNOISE is launched to couple the boundary element model and the finite element model of the structure. The computed surface vibration constitutes the excitation for an acoustic uncoupled boundary element analysis.

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.

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.

Electronics components are estimated to be between 9 to 15 % of a total vehicle cost, and this trend will remain strong for the next years. The amount of electronics content in a vehicle has grown steadily since 1970's, and as a result, development challenges such as testing and validation are a key aspect of its overall development costs. Testing costs can amount easily to US$ 500 k in medium complex automotive parts of a vehicle (e.g. instrument cluster) depending on a specific OEM customer demand, and this on top of limited regional laboratory capacity can also lead to increased testing time. The goal of this paper is to outline key aspects of electronics in vehicle components testing, including overall costs and timing, and propose a lean approach to optimize such costs & timing. The key aspects of such optimization include not only resources, but also laboratories and upfront OEM customer planning.

Identification of vibration transfer paths is critical to proper isolation of vibration excitations from becoming objectionable noise in a vehicle. Traditional transfer path methods involve comparing vibration inputs to the outputs of each joint. This method can be time consuming and inefficient due to a complexity of paths. A new statistical method was developed to improve the efficiency of testing. This method requires the measurement of the excitation vibration input at each joint of the source component and response sound measurements in the vehicle. Identification of transfer paths using regression analysis will determine the trouble paths to scrutinize.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and the improvement of a hydraulic steering pump noise, vibration, and harshness (NVH) performance in relief. DOE methods were applied to subjective ratings to examine the effect of several different factors, as well as the interactions between these factors on pump relief NVH. Specifically, the DOE was applied to the geometry of the cross ports on a hydraulic relief valve to improve “whistle” noise in the pump. Statistical methods were applied to determine which factors and interactions had a significant effect on pump whistle. These factors were used to produce a more robust cross port configuration reducing whistle noise. Lastly, the final configuration was experimentally verified on the test apparatus and subjectively confirmed in vehicle-level testing.

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.

This work demonstrates a practical method for predicting vehicle-level automotive steering system NVH performance from component-level NVH measurements of hydraulic steering pumps. For this method, in-vehicle measurements were completed to quantify vehicle noise path characteristics, including steering system structure borne, fluid borne and airborne paths. At the component level, measurements of steering pump reaction forces, sound power and dynamic hydraulic pressure were also completed. The vehicle-level measurement data was used to construct NVH transfer functions for the vehicle. These transfer functions were in turn combined with the pump component data measured on a test stand to create a prediction for steering pump order vehicle interior noise. The accuracy of these predicted values was assessed through comparison with actual vehicle interior noise measurements.

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.

Today open source software is widely used in different domains like Desktop systems, Consumer electronics (smart phones, TV, washing machines, camera, printers, smart watches), Automotive, Automation etc. With the increased involvement of the open source software in the different domains including the safety critical ones, there has been a requirement of the well-defined test strategy to test and verify such systems. Currently there are multiple open source tools and frameworks to choose from. The paper describes the various open source test strategies and tools available to qualify such systems, their features, maintenance, community support, advantages and disadvantages. Target audience would be the software engineers, program managers, using an open source stack for the product development.