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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.

The purpose of this paper is to present a common sense practical method for establishing and demonstrating reliability objectives. In particular, this paper will: describe an operational definition of “useful life”, describe an accelerated laboratory test procedure for demonstrating that products meet the useful life objective, and describe a method for demonstrating correlation between customer usage and laboratory testing.

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.

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.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

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.

This paper discusses the development of combination vehicle stability program (CVSP) at Visteon. It will describe why stability control is needed for combination vehicles and how the vehicle stability can be improved. We propose and evaluate controller structures and design methods for CVSP. These include driver's intent identification, combination vehicle status estimation and control, and fault detection / tolerance. In this paper, the braking and steering dynamics of car-trailer and tractor-semitrailer combinations, and the brake systems which should be used extensively to increase the stability of combination vehicles are presented. Also our development platform is introduced and the combination vehicle simulation results are presented. The definition of combination vehicles in this paper includes car-trailer and commercial tractor-semitrailer combinations since their vehicle dynamics are based on the same equations of motion.

Data design is a very critical step in the model-based software development process. This paper discusses the importance of a data dictionary in modeling, automatic code generation and in creating model dependency graphs.

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.