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The principles of an electronic nose are described briefly. It is shown how a sensor array in combination with pattern recognition software can be used for quality control and classification of car interior trim materials. Anomalies such as bad smelling leather and carpet are shown as outliers. The results are consistent with GC-MS TVOC measurements as well as with data from a human sensory panel. More needs to be done, however, regarding the sensor stability in particular before the sensor array can be used for routine classification of the trim materials.

In the early days of the automotive industry, durability and reliability were hit or miss affairs, with end-users often being the first to know about any durability problems - and in many cases forming an essential part of the development process. More recently, automotive companies have developed proving ground and laboratory test procedures that aim to simulate typical or severe customer usage. These test procedures have been used to develop the products through a series of prototypes and to prove the durability of the product prior to release in the marketplace. Now, commercial pressures and legal requirements have led to increasing reliance on CAE methods, with fatigue life prediction having a central role in the durability engineering process.

Six Sigma is a development methodology which emphasizes objective evaluations based on facts and measurements. However, for some problems the information is inherently subjective, with large individual variations. Also, in the early development phases, it may be difficult to define measurable metrics that correctly capture the important qualities. The vehicle HMI is a good example of such an application. In this paper, we present experiences of applying Design for Six Sigma methods to the early development phases of an automotive HMI. The focus of the paper is on how to handle uncertainties and vague subjective information.

The durability peak load events Driving over a curb and Skid against a curb have been simulated in Adams for a Volvo S80. Simulated responses in the front wheel suspension have been validated by comparison with measurements. Due to the extreme nature of the peak load events, the component modeling is absolutely critical for the accuracy of the simulations. All components have to be described within their full range of excitation. Key components and behaviors to model have been identified as tire with wheel strike-through, contacts between curb and tire and between curb and rim, flexibility of structural components, bump stops, bushings, shock absorbers, and camber stiffness of the suspension. Highly non-linear component responses are captured in Adams. However, since Adams only allows linear material response for flexible bodies, the proposed methods to simulate impact loads are only valid up to small, plastic strains.

The new SULEV legislation for passenger cars with gasoline powered engines, which will be introduced with the California LEV II program in the year 2003, requires a further development of the exhaust aftertreatment system. Three fundamentally different system approaches, each with very high efficiency in reducing cold start hydrocarbons, will be discussed in this paper. Vehicle test results will be presented to illustrate the potential of the respective systems towards the SULEV requirements. Durability aspects are also considered since an increased durability of 120 000 and even 150 000 miles is imposed by the legislation.

Automotive electronic systems are becoming safety related causing a need for more systematic and stringent approaches for demonstrating the functional safety. The safety case consists of an argumentation, supported by evidence, of why the system is safe to operate in a given context. It is dependent on referencing and aggregating information which is part of the EAST-ADL2, an architecture description language for automotive embedded systems. This paper explores the possibilities of integrating the safety case metamodel with the EAST-ADL2, enabling safety case development in close connection to the system model. This is done by including a safety case object in EAST-ADL2, and defining the external and internal relations.