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The requirement of “zero defects” is rapidly finding its way as a “standard” of quality in numerous quarters. This phrase has great psychological appeal, and is often taken literally at all levels in an organization even though quality motivation may be the intention. It is common to believe that when zero defects are found in the sample, this must be the case for “all the rest” as well. In this paper the technical side of “zero defects” is examined. We look at the statistics of zero defects and show what is implied about lot or process quality when zero defects is the actual sample outcome. The focus is on attribute measurements and includes some special cases where a significant measurement error exists and cases where a Bayesian statistical analysis may be appropriate.

An integrated simulation tool has been developed, which is applicable to a wide range of design issues. A key feature introduced for the first time by this new tool is that it is truly a single code, with identical handling of engine, powertrain, vehicle, hydraulics, electrical, thermal and control elements. Further, it contains multiple levels of engine models, so that the user can select the appropriate level for the time scale of the problem (e.g. real-time operation). One possible example of such a combined simulation is the present study of engine block vibration in the mounts. The simulation involved a fully coupled model of performance, thermodynamics and combustion, with the dynamics of the cranktrain, engine block and the driveline. It demonstrated the effect of combustion irregularity on engine shaking in the mounts.

In general for Vehicle-to-Vehicle (V2V) communication, message authentication is performed on every received wireless message by conducting verification for a valid signature, and only messages that have been successfully verified are processed further. In V2V safety communication, there are a large number of vehicles and each vehicle transmits safety messages frequently; therefore the number of received messages per second would be large. Thus authentication of each and every received message, for example based on the IEEE 1609.2 standard, is computationally very expensive and can only be carried out with expensive dedicated cryptographic hardware. An interesting observation is that most of these routine safety messages do not result in driver warnings or control actions since we expect that the safety system would be designed to provide warnings or control actions only when the threat of collision is high.

”U” bolts are fixing elements and they are used to clamp an elastic joint. From the past, they still looking as an old design and unfortunately, suspension engineers are not specialists in fasteners and elastic joints. That is why we will show important assumptions and concepts to design and specifications this clamp element “U” bolt and its influence over leaf-springs. Currently, “U” bolt is used to clamp an elastic or elastic-plastic joint of heavy duty suspension, formed by leaf-spring, axle, spring pad, “U” bolt plate. This kind of suspension is typically used to trucks, buses and trailers. We are wondering, which one important assumption that an engineer must be careful when designs a new suspension changing from old designs to an updated technology. We provide a theoretical analysis and a FEA analysis to compare torque efficacy x leaf-spring reactions and what are effects this relationship can cause in a suspension.

The intersection of changing lifestyles and evolving transportation needs finds smart USA well positioned for launch in 2008 during one of the most competitive periods in U.S. automotive history. In a zero sum market with new global entrants competing for single points of share, where quality levels have been redefined and fractions of points separate the best from the challengers, lifestyle awareness, innovation and product positioning become the differentiators. Simply adding features has left some with hefty investments and confused consumers. Bigger is not always better. More is not always desirable. The real opportunity for new entrants to the US market may be defined within niche markets where changing lifestyles allow for the emergence of new segments. Today, smart USA has surfaced as a clear example of right product, right place, right time.

Understanding customer expectations is critical to satisfying customers. Holding customer clinics is one approach to set winning targets for the engineering functional measures to drive customer satisfaction. In these clinics, customers are asked to operate and interact with vehicle systems or subsystems such as doors, lift gates, shifters, and seat adjusters, and then rate their experience. From this customer evaluation data, engineers can create customer loss or preference functions. These functions let engineers set appropriate targets by balancing risks and benefits. Statistical methods such as cumulative customer loss function are regularly applied for such analyses. In this paper, a new approach based on the Taguchi method is proposed and developed. It is referred to as Taguchi Customer Loss Function (TCLF).

Software programs in non-application areas such as Board Support Packages, Hardware Abstraction Layers, signal processing and data acquisition are more or less very standard and common across many applications. These form a major part of the “platform” software, which changes very little. However, it is seen that many a time, efforts are spent resolving issues in the hardware dependent layers rather than concentrating on the application at hand, despite the fact that the software controlling the hardware has been developed many times. There are many reasons why this section of the software is rewritten many times over: different coding standards, different software architecture and layering concepts, the dreadful cut-and-paste methods, and so on. Introduction of a tool-based code configurator and generator eliminates access to the code and focuses on configuring a pre-written set of SW procedures. Advantages: Standardization, reuse and high levels of productivity.

There are many different vibration sources in a car. Engine, gears, road roughness, impacts against the wheels cause vibration and sound that can decrease the parts and the car durability as well as affect drivability, safety and passengers and community comfort. In 4×4 cars, some extra vibration sources are the parts responsible for transmitting the torque and power to the rear wheels. Each of them has their own vibration modes, excited mostly by its imbalance or by the second order engine vibration. The engine vibration is a very well known phenomena and the rear driveshaft is designed not to have any vibration mode in the range of frequencies that the engine works or its second order. The imbalance of a driveshaft is also a design requirement. That means, the acceptable imbalance of the driveshaft is limited to a maximum value.

The simulation system “Roadrunner” has the ability to compute 3-dimensional vehicle behavior during simulated ABS-stops or Traction Control (TC) operation on a PC based test rig system. This can be done in real-time mode with fast DSP (digital signal processor) boards and an ABS/TC-ECU as a ‘Hardware-in-the-loop’ device (HIL) or off-line (non-real-time), on the PC only. In the off-line-mode, the PC additionally performs the ABS/TC control algorithms. The simulated system includes model equations for chassis and wheel movement, hydraulics and road to tire interactions. A driver model enables the reproduction of standard steering maneuvers.

This paper describes the initial works related to the study of Internal Combustion Engines, as an object of mechanical design, at the Universidad Tecnológica de Pereira. It is reported a concise, complete methodology for simple model of internal combustion engine. The emphasis of the paper is placed on the use of the in-cylinder parameters (pressure and temperature) and inertial loads in the crank-slider mechanism to derive the loads that act on all the components of the crank-slider mechanism as well as the theoretical output torque for a given geometrical structure and inertial properties. These loads can then be used to estimate the preliminary dimensions of engine components in the initial stage of engine development. To obtain the pressure and temperature inside the cylinder, under different operation parameters, such as air fuel ratio and spark angle advance, a Zero dimensional model is applied. The heat transfer from the cylinder and friction are not taken into account.

A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure.

Presented in this paper is a brief review of momentum exchange theory for Jet Noise Suppression. “Experimental Results from Scale Model Tests” are included. These data exhibit peak to peak attenuation of 20 db along maximum exhaust noise azimuths at a nozzle pressure ratio of 3.1.

A multi vector design tool to accurately predict instrument panel obscuration was developed to insure that critical legal displays in vehicles are not obscured. The concept provides for a computer generated light source shaped to replicate the human eyes. The light source is then projected onto a 3D math based arrangement and the resultant shadows are visible on the instrument panel surface and its displays. Design studios require criteria for the placement of the instrument cluster gages and displays, various controls, switches, and steering column stalks before an interior theme can be completed. Therefore, instrument panel obscuration and visibility must be determined early in the design process. The obscured areas are a function of the instrument panel surface, steering wheel rim, hub, spokes, and the location of the driver's eyes. This light source method allows engineers and designers the ability to quickly determine obscured areas.

Vehicle dynamics is a discipline of mechanical engineering that benefited of significant improvements thanks to the progress of computational engineering. Vehicle dynamics engineers are using CAE for the development of a vehicle with MBS and FEA. The concurrent use of these two technologies is a standard in the automotive industry. However the current simulation process is not fully efficient because local geometrical and material nonlinearities are not accurately modeled in classical MBS software. This paper introduces a methodology for vehicle dynamics simulation integrating MBS capabilities in one single nonlinear FEA environment enabling an accurate modeling of nonlinearity in vehicles.

This paper describes the application of statistical techniques known as Design of Experiments (D.O.E.) to efficiently use the results of numerical analysis data in order to improve the configuration of automotive systems. The general framework of these techniques is presented in a format aiming at the design engineer as their end user. Besides, a case study is presented with the purpose of illustrating their practical use. The first step of the case study is to build predictive models for the behaviour of the automotive system being developed by means of the Response Surface Method (RSM), using the proper D.O.E. options. Once these predictive models are available, automatic numerical optimization algorithms are used to improve the responses of interest for given operating conditions. Finally, the automotive systems are robust designed taking into account that the operating conditions vary randomly.

The paper focuses and develops issues raised by the SAE paper ‘THE FUTURE OF VEHICLE ELECTRICAL POWER SYSTEMS AND THEIR IMPACT ON SYSTEM DESIGN’ [1] and describes the realisation of a vehicle with a 12 V architecture of flexible configuration and a power management function. The paper describes the methodology, reasoning and mission behind the creation of the vehicle, developed after collaborative exercises in Europe and the USA, and resulting in a joint programme involving a major vehicle manufacturer and a European system supplier. The electrical system is becoming the focus of activity world-wide due to rapid changes in vehicle requirements, in the areas of safety, environmental and functional demands. There are opportunities for:- (a) Improved starting (b) Integrated management of power generation and demand. (c) Higher system integrity (d) Higher efficiency (e) Improvement of the vehicle electrical environment, giving benefits in component cost.

The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases.

Driver state monitoring is a crucial technology for enhancing road safety and preventing human error-caused accidents in the era of autonomous vehicles. This paper presents CogniSafe, a comprehensive driver monitoring system that uses deep learning and computer vision methods to detect various types of driver distractions and fatigue. CogniSafe consists of four modules: Driver anomaly detection and classification: A novel two-phase network that proposes and recognizes driver anomalies, such as texting, drinking, and adjusting radios, using multimodal and multiview input. Gaze estimation: A video-based neural network that jointly learns head pose and gaze dynamics, achieving robust and efficient gaze estimation across different head poses. Eye state analysis: A multi-tasking CNN that encodes features from both eye and mouth regions, predicting the percentage of eye closure (PERCLOS) and the frequency of mouth opening (FOM).