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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.

Estimation and prediction of residual life and reliability are serious concerns in life cycle management for aging structures. Laboratory testing replicating fatigue loading for a typical military aircraft wing skin was undertaken. Specimens were tested until their fatigue life expended reached 100% of the component fatigue life. Then, scanning electron microscopy was used to quantify the size and location of fatigue cracks within the high stress regions of simulated fastener holes. Distributions for crack size, nearest neighbor distances, and spatial location were characterized statistically in order to estimate residual life and to provide input for life cycle management. Insights into crack initiation and growth are also provided.

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].

This paper describes two studies; each conducted concurrently in North America and Europe to assess subjective impressions and simulated driving task performance using a touch screen interface with different types of auditory and haptic feedback. The first study investigated subjective impressions of four types of touch screen feedback in a static laboratory setting. The second study investigated the influence of the same four touch screen feedback types on simulated driving task performance using the lane change test (LCT). Results of the first study revealed significant similarities and differences in subjective impressions between respondents in each of the two regions studied. Results of the second study revealed differences in task performance that suggest distinct participant strategies in each of the two regions studied.

Touch screens provide substantial benefits as a control and display system but still have some disadvantages. The availability of haptic (tactile) technology allows touch screens to function similarly to traditional mechanical controls. Two studies were undertaken to investigate the addition of haptic feedback as well as auditory feedback on user perceptions of the touch screen experience. The first study was conducted in a desktop setting and the second study was conducted with the touch screen integrated in a vehicle. In both studies, participants assessed four different types of feedback conditions: visual feedback only (V), auditory and visual feedback (AV), haptic and visual feedback (HV), and auditory, haptic, and visual feedback combined (AHV). The results of these studies support the claim that individuals strongly prefer touch screen implementations that incorporate haptic elements and also provide insights on regional differences in their perception.

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.

Software is today one of the most important components of electronic products. The capture and validation of the requirements makes a difference if the product will fulfill the customer's expectations or generate enormous frustration. The correct implementation of software validation makes the Product Development Organization more mature and reliable. Software validation is an opportunity for the product development team to identify if the requirements and customer expectations were achieved. It is also used to identify the risks and possible improvements to the product. Software testing is one element of a brooder topic that is often referred to as verification and validation (V&V). Verification refers to the set of activities that ensure that software correctly implements a specific function. Validation refers to a different set of activities that ensure that the software that has been built is traceable to customer requirements.

Plastic air induction system (AIS) has been widely used in vehicle powertrain applications for reduced weight, cost, and improved engine performance. Physical design validation (DV) tests of an AIS, as to meet durability and reliability requirements, are usually conducted by employing the frequency domain vibration tests, either sine sweep or random vibration excitations, with a temperature cycling range typically from -40°C to 120°C. It is well known that under high vibration loading and large temperature range, the plastic components of the AIS demonstrate much higher nonlinear response behaviors as compared with metal products. In order to implement a virtual test for plastic AIS products, a practical procedure to model a nonlinear system and to simulate the frequency response of the system, is crucial. The challenge is to model the plastic AIS assembly as a function of loads and temperatures, and to evaluate the dynamic response and fatigue life in frequency domain as well.

Reliability allocation of system objectives for Reliability validation purposes must account for Confidence levels. Misallocating Confidence levels can lead to unrealistic and unmanageable objectives, resulting in increased development times and associated costs. Therefore, it is necessary to correctly model both Reliability and Confidence levels. Unfortunately, modeling for anything more complex than the simplest pass/fail test criteria can become quite complex in a multi-component system. The easiest case to model is time-censored testing with no failures. But time-censored testing with no failures is just a small subset of all viable validation strategies. Given that the validation strategy for each component can be different, trying to isolate a single one-size-fits-all model is extremely difficult. For these complex scenarios, computer simulation provides the best approach to calculating true system performance.

Nowadays, ever market vehicle change affects body, suspension & steering gear systems. The purpose of this report is to quantify the methodology for evaluating and improving rattle mechanical noises in power rack & pinion steering systems. It is very important the correct process be used to adjust and approve the power steering gears in order to prevent the knock noise issue on services (warranty). This report describes how Visteon's Engineering makes efforts to achieve a reduction in warranty issues due to mechanical noise in the power steering gear, which affects its performance. We refer to this mechanical noise as “Knocking Noise” which derives from the gearing (meshing) adjustment loss. This experiment, supported by the Six Sigma methodology, led to new knowledge on how to improve the method of meshing adjust and test approval in process through of Design of Experiments (DOE).

Maximum Brake Torque (MBT) timing for an internal combustion engine is the minimum advance of spark timing for best torque. Traditionally, MBT timing is an open loop feedforward control whose values are experimentally determined by conducting spark sweeps at different speed, load points and at different environmental operating conditions. Almost every calibration point needs a spark sweep to see if the engine can be operated at the MBT timing condition. If not, a certain degree of safety margin is needed to avoid pre-ignition or knock during engine operation. Open-loop spark mapping usually requires a tremendous amount of effort and time to achieve a satisfactory calibration. This paper shows that MBT timing can be achieved by regulating a composite feedback measure derived from the in-cylinder ionization signal referenced to a top dead center crank angle position. A PI (proportional and integral) controller is used to illustrate closed-loop control of MBT timing.

One challenge facing automotive product development teams is the inclusion of the Human System Integration (HSI) community – consisting of human factors professionals, graphic and industrial designers, rapid prototyping software engineers, electronic hardware engineers, and systems engineers – in the Product Development Process (PDP). In order to achieve this integration, Visteon looked to the methods of systems engineering currently employed throughout the PDP. Overlaying the HSI process with an accepted systems engineering process description known as the N2 (N-squared) chart resulted in the outlining of expected inputs to the HSI process team, definitions of processes undertaken by the team, and expected outputs of those processes.

Traditionally fog lamps use halogen filament light sources. With the emergence of high brightness white LEDs, it is now possible to develop automotive forward lighting systems with LED light sources. Six LEDs are shown to be sufficient for the implementation of a European fog lamp using a faceted reflector optical approach. Each reflector together with the LED light source forms a modular element. The optical parameters of two different lamp designs are compared and correlation between the simulation and prototype measurements is shown. Further, additional forward lighting functions can be implemented through the use of additional elements.

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.

This paper discusses our experiences on the implementation and benefits of using the Hardware-In-the-Loop (HIL) systems for Powertrain control system software verification and validation. The Visteon HIL system integrated with several off-the-shelf diagnostics and calibration tools is briefly explained. Further, discussions on test automation sequence control and failure insertion are outlined The capabilities and advantages of using HIL for unit level software testing, open loop and closed-loop system testing, fault insertion and test automation are described. HIL also facilitates Software and Hardware Interface validation testing with low-level driver and platform software. This paper attempts to show the experiences with and capabilities of these HIL systems.

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.

Visteon has developed a CAE procedure to qualify instrument panel (IP) products under the vehicle key life test environments, by employing a set of CAE simulation and durability techniques. The virtual key life test method simulates the same structural configuration and the proving ground road loads as in the physical test. A representative dynamic road load profile model is constructed based on the vehicle proving ground field data. The dynamic stress simulation is realized by employing the finite element transient analysis. The durability evaluation is based on the dynamic stress results and the material fatigue properties of each component. The procedure has helped the IP engineering team to identify and correct potential durability problems at earlier design stage without a prototype. It has shown that the CAE virtual key life test procedure provides a way to speed up IP product development, to minimize prototypes and costs.

Same of the more enticing and productive opportunities to a useful work in product assurance are those of influencing the design of a product. The primary concern of design assurance is preventing or correcting those design errors that lead to poor product integrity. One of the tools used by the development teams in many organizations is the Design Review. The impact in cost and quality is directly affected by the correct utilization of the tool.

Occupant knee impact simulations are performed in the automotive industry as an integrated design process during the course of instrument panel (IP) development. All major automakers have different categories of dynamic testing methods as part of their design process in validating their designs against the FMVSS 208 requirement. This has given rise to a corresponding number of knee impact simulations performed at various stages of product development. This paper investigates the advantages and disadvantages of various types of these knee impact simulations. Only the knee load requirement portion of the FMVSS208 is considered in this paper.

A fixed-base driving simulator with a 14-degree of freedom vehicle dynamics model was used to compare the lane tracking performance of test subjects using a joystick steering controller to that using a conventional steering wheel. Three driving situations were studied: a) straight-line highway driving, b) winding road driving (country road), and c) evasive maneuvering - a double lane change event. In addition, three different joystick force-feedback settings were evaluated: i) linear force feedback, ii) non-linear, speed sensitive force feedback and iii) no force feedback. A conventional steering wheel with typical passenger car force feedback tuning was used for all of the driving events for comparison.