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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.

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.

This paper presents an assessment of competing algorithms for normalizing volume levels between tracks and/or sources in an automotive infotainment system. Portable media players such as smartphones and iPod® devices are extremely popular for listening to music collections or streaming content from the Internet. The lack of normalization is a source of dissatisfaction if the user experiences significant changes in audio level between tracks. Several commercially available algorithms exist to solve this problem. This research includes a double-blind listening test comparing an audio sample processed with the different leveling algorithms to an unprocessed reference. The listener preference rating is recorded and results indicate which algorithm is preferred.

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.

A practical and low cost Blind Spot Monitoring system is proposed. By using a single camera, the range and azimuth position of a vehicle in a blind spot are measured. The algorithm is based on the proposed RWA (Range Window Algorithm). The camera is installed on the door mirror and monitoring the side and rear of the host vehicle. The algorithm processes the image and identifies range and azimuth angle of the vehicle in the adjacent lane. This algorithm is applied to real situations. The 388 images including several kinds of vehicles are analyzed. The detection rate is 86% and the range accuracy is 1.6[m]. The maximum detection range is about 30[m].

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.

Electro-pneumatic valve actuators are used to eliminate the cam shaft of a traditional internal combustion engine. They are used to control the opening timing, duration, and lift of both intake and exhaust valves. A physics based nonlinear mathematical model called the level one model was built using Newton's law, mass conservation and thermodynamic principles. A control oriented model, the level two model, was created by partially linearizing the level one model for model reference parameter identification. This model reduces computational throughput and enables real-time implementation. A model reference adaptive control system was used to identify the nonlinear parameters that were needed for generating a feedforward control signal. The closed-loop valve lift tracking, valve opening and closing timing control strategies were proposed.

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.

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.

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.

Application of Ultra Thin Wall (UTW) ceramic substrates in the catalytic converter system requires the canner and component manufacturers to better understand the root cause and physics behind substrate breakage during the canning process. For this purpose, a ceramic substrate strength study for shoebox design has been conducted within Visteon Corporation. Computer Numerical Control (CNC) machined top and bottom fixtures, with identical inner surfaces as shoebox converter upper and lower shells, were used to crush mat wrapped substrates. Thin film pressure sensor technology enables the recording of substrate surface pressure during the compression process. Shell rib, washcoat, canning speed and cell density effects on substrate failure have been experimentally investigated. The development of a mathematical model helps to identify a better indicator to evaluate the substrate strength in the canning process and establish the strength for uncoated & coated substrates.

Generalized predictive control (GPC) is a discrete time control strategy proposed by Clark et al [1]. The controller tries to predict the future output of a system or plant and then takes control action at present time based on future output error. Such a predictive control algorithm is presented in this paper for yaw stability management of an automobile. Most of the existing literature on the yaw stability management systems lacks the insight into the yaw rate error growth when the automobile is in a understeer or oversteer condition on a low friction coefficient surface in a handling maneuver. Simulation results show that the predictive feature of the proposed controller provides an effective way to control the yaw stability of a vehicle.

Rising costs continue to be a problem within the automotive industry. One way to address these rising costs is through modularity. Modular systems provide the ability to achieve product variety through the combination and standardization of components. Modular design approaches used in development of vehicle electrical, electronic, and software (EES) systems allow sharing of architectures/modules between different product lines (vehicles). This modular design approach may provide economies of scale, reduced development time, reduced order lead-time, easier product diagnostics, maintenance and repair. Other benefits of this design approach include development of a variety of EES systems through component swapping and component sharing. In this paper, new optimization algorithms and software tools are presented that allow vehicle EES system design engineers to develop modular architectures/modules that can be shared across vehicle platforms (for OEMs) and across OEMs (for suppliers).

Generalized predictive control (GPC) is a discrete time control strategy proposed by Clark et al [1]. The controller tries to predict the future output of a system or plant and then takes control action at present time based on future output error. Such a predictive control algorithm is presented in this paper for deceleration slip regulation in an automobile. Most of the existing literature on the anti-lock brake control systems lacks the effectiveness of the wheel lockup prevention when the automobile is in a skid condition (in a low friction coefficient surface with panic braking situation). Simulation results show that the predictive feature of the proposed controller provides an effective way to prevent wheel lock-up in a braking event.

The process for accurately estimating product reliability early in the development process can be a difficult and costly task. Traditional methods like Reliability Prediction Models and Life Testing Strategies yield beneficial results when relative information is known about the product that is to be analyzed. When there is minimal information known (prior failure rates…) such a new concept design these above reliability methods have limitations. For these cases a Virtual Testing Strategies have proven to yield valuable results. This paper will demonstrate a reliability analysis procedure for a new automotive concept design. This analysis procedure composes of a mathematical model, model validation, parameter diagram, design of experiment (DOE), response surface, and optimization.