Search Results

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.

The paper addresses compressor body temperature (crankcase) importance to the vehicle AC system long-term durability. Majority of OEM vehicle test evaluation is to see if AC system can pass compressor discharge temperature and discharge pressure targets. Most OEMs adopt 130°C max compressor discharge temperature and 2350 kpag head pressure as the target. From the field, although some of the compressor failure results from a high compression ratio, and compressor discharge temperature that are caused by the poor front end airflow, etc., high percentage compressor failed systems exhibit not too high compression ratio and compressor discharge temperature, but having the trace of high temperature in the shaft area, gasket area, etc. With introducing more and more variable swash plate compressor applications, OEMs start to see more and more compressor failures that are not related to a high compressor discharge temperature but the trace of high compressor body temperature.

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].

Because combustion engine equipped vehicles must conform to stringent hydrocarbon (HC) emission requirements, many of them on the road today are equipped with an engine air intake system that utilizes a hydrocarbon adsorber. Also known as HC traps, these devices capture environmentally dangerous gasoline vapors before they can enter the atmosphere. A majority of these adsorbers use activated carbon as it is cost effective and has excellent adsorption characteristics. Many of the procedures for evaluating the adsorbtive performance of these emissions devices use mass gain as the measurand. It is well known that activated carbon also has an affinity for water vapor; therefore it is useful to understand how well humidity must be controlled in a laboratory environment. This paper outlines investigations that were conducted to study how relative humidity levels affect an activated carbon hydrocarbon adsorber.

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.

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.

Manual ‘porting” of source code is often required in order to “reuse” control software in different applications with different target hardware. This process is not cost effective. Maintaining multiple “versions” of the same software also causes problems. This paper describes a way in which multiple target source code can be generated from a single model. A custom data class is developed so that it can be used to define both signal and parameter data types necessary for data dictionary-driven models. This capability allows a single model to be used to generate code for multiple target hardware architectures. A software development process using a generic model to support multiple hardware targets is compared with the hand porting process (e.g. floating-point to/from fixed-point). Auto code generation from a sample multi-target feature model will be presented. The efficiency of the auto code will also be discussed.

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.

Water condensate retained inside an automotive evaporator has remained as one of the primary sources of unpleasant “odors”, which in turn can drive up the warranty cost for automotive manufacturers. The “wet” evaporator fin can also underperform due to the presence of condensate blocking the air passage. Moreover, condensate retention can be a potential factor of freezing up evaporators. Thus, an evaporator fin must be designed such that it can shed and drain water condensate as well as provide an excellent heat transfer capability. While the importance of water retention is well known, there seems lacking of a comprehensive way to evaluate the water retention characteristics of a particular product. In this work, attempts were made to answer four questions: (1) What is the mechanism that controls water condensate retention characteristics in an automotive evaporator? (2) Can different water retention evaluation methods reveal the same characteristics?