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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.

Over the last ten years there has been a steady growth in the market share of light-duty diesel engines, especially in Europe. At the same time, a general trend in petrol engine development has been seen, in which normal aspirated engines are being replaced by downsized turbocharged engines. Therefore, NVH engineers have to deal with new challenges. Turbochargers produce an aerodynamic noise in the frequency range above 1000Hz, which might influence the exterior and interior noise level. As a result, the additional requirement for acoustical components to reduce this flow noise is going to pose an increasing challenge for air intake system suppliers. This paper describes a new design of well-known wide band silencer first mentioned by A. Selamet, N.S.Dickey and J.M.Novak [1,2]. The silencer works according to the interference principle. The sound is guided into two or more parallel pipes of different lengths.

The requirement for crew resource management (CRM), or aircrew coordination training (ACT) in military parlance, has been well documented and attested to. In addition, aircraft systems training has become more intense and more in-depth in the new aircraft designs, especially in multi-crew and complex aircraft such as the MV-22 Osprey Tiltrotor. (see Figure 1) Former training systems detailed training procedures that called for classroom training and simulation/simulator training followed by flight training. Improvements in aircraft flight skills training provide increased flying training capability coupled with reduced training time by integrating a mixed simulation/flight training syllabus, e.g. two to three simulation periods followed by one or two flight training periods covering the same material/skills. In addition, the simulation training will introduce new skills; the following flight periods will further refine/hone those skills.

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.

Plug-in Hybrid Electric Vehicles (PHEVs) use electric energy from the grid rather than fuel energy for most short trips, therefore drastically reducing fuel consumption. Different configurations can be used for PHEVs. In this study, the parallel pre-transmission, series, and power-split configurations were compared by using global optimization. The latter allows a fair comparison among different powertrains. Each vehicle was operated optimally to ensure that the results would not be biased by non-optimally tuned or designed controllers. All vehicles were sized to have a similar all-electric range (AER), performance, and towing capacity. Several driving cycles and distances were used. The advantages of each powertrain are discussed.

Quality assurance (QA) in motor vehicle emissions inspection/maintenance (I/M) programs is a continuing concern, especially in decentralized programs with hundreds or even thousands of licensed stations. The emissions analyzers used in such stations are an important focus of governmental QA efforts because of the central role of analyzers in determining which vehicles need to be repaired. Therefore, the In-use performance of I/M emission analyzers has a large impact on the quality of 1/M programs as a whole. This paper reports on the results of an investigation in California designed to determine in-use performance of emission analyzers in the field. The investigation was designed to evaluate both drift rates and the ability of analyzer systems with automatic gas calibration capability to correct analyzer responses outside of accepted tolerances.

The Focke-Wulf Fw 190 was one of the truly outstanding fighter aircraft of the Second World War. It distinguished itself over all fronts on which the Luftwaffe fought in conditions ranging from arctic wastes to the deserts of North Africa. The Fw 190 represented the epitome of conventional piston-engine fighter design on the threshold of the jet age. Conceived nearly sixty years ago, flying for the first time on the eve of the war in 1939 and acknowledged as “the best all-around fighter in the world” in the mid-war years, derivatives of the Fw 190 were still pushing the ultimate capability boundary for this class of aircraft at war's end in 1945 (reaching maximum level true airspeeds of 470 mph [about Mach 0.7] at altitudes of well over 40,000 feet). This paper assesses the design attributes and technology approaches, including innovative use of advanced electrical systems, that were used to make the Fw 190 one of the great all-around fighters in aviation history.

This paper is an extension of our previous work on the CHASE (Classification by Holistic Analysis of Scene Environment) algorithm, that automatically classifies the driving complexity of a road scene image during day-time conditions and assigns it an ‘Ease of Driving’ (EoD) score. At night, apart from traffic variations and road type conditions, illumination changes are a major predominant factor that affect the road visibility and the driving easiness. In order to resolve the problem of analyzing the driving complexity of roads at night, a brightness detection module is incorporated in our end-to-end nighttime EoD system, which computes the ‘brightness factor’ (bright or dark) for that given night-time road scene. The brightness factor along with a multi-level machine learning classifier is then used to classify the EoD score for a night-time road scene. Our end-to-end ‘Night-time EoD system’ is a real-time onboard system implemented and tested on road scene data collected in Japan.

Design of a Cabin Tilting System of heavy trucks, a multi degree of freedom mechanism, is a challenge. Factors like adequate tilting angle, cabin styling, packaging, non interference of tilting system with ride comfort, forces in the system, specifications of the hydraulic system, are all very important for designing the system. Numerous considerations make the design process highly iterative hence longer design time. This paper primarily focuses on Kinematics and Dynamic analysis of the system in ADAMS and validation of system with real time testing results. Intention of this work is to make a parametric ADAMS model and link it to a Knowledge Based Engineering application to facilitate designer to quickly carry out design iterations for reducing development time. The Knowledge Based Engineering software is made using object oriented language called ‘Object Definition Language’ which has been developed using C and C++ software languages.

Due to the rising costs of fuel and increasingly stringent regulations, auto makers are in need of technology to enable more fuel-efficient powertrain technologies to be introduced to the marketplace. Such powertrains must not sacrifice performance, safety or driver comfort. Today's engine and powertrain manufacturers must, therefore, do more with less by achieving acceptable vehicle performance while reducing fuel consumption. One effective method to achieve this is the extreme downsizing of current direct injection spark ignited (DISI) engines through the use of high levels of boosting and cooled exhaust gas recirculation (EGR). Key challenges to highly downsized gasoline engines are retarded combustion to prevent engine knocking and the necessity to operate at air/fuel ratios that are significantly richer than the stoichiometric ratio.

“Digital Prototype” simulations have been used at DaimlerChrysler to achieve vehicle level NVH objectives. The effectiveness of these simulations to guide the design when faced with vehicle parameter uncertainties is discussed. These uncertainties include, but are not limited to, material properties, material gauges, damping, structural geometry, loads, boundary conditions and weld integrity. Manufacturing and assembly processes introduce variations in the nominal values of these parameters resulting in a scatter of vehicle level NVH simulation responses. An example of a high frequency NVH concern will be studied and modified to arrive at robust design guidance when faced with uncertainty. The validity of a “deterministic digital prototype” simulation model and its relevant role as a “trend predictor” rather than “absolute predictor” tool in guiding the design is also discussed.

The Boeing Company in Mesa, Arizona, has been conducting a concept design study of a roadable helicopter called the “Converticar” to assess its feasibility. This is a twin-engine vehicle with twin retractable coaxial counter-rotating rotors. The purpose of the study is to describe a vehicle that carries four passengers in the equivalent of a luxury car that also can fly like a helicopter, and can be priced like a luxury car. To come near this cost goal, the production rate must be on the order of 500,000 units a year. At that rate there is no chance of training a comparable number of pilots each year. So the machine must fly and navigate autonomously, with the pilot just dialing in where he/she wants to go. Technologically, the concept appears to be feasible. Modern design processes, new materials, and improved manufacturing process should allow the Converticar to be built at the prescribed rate when the proper infrastructure for manufacturing it is made available.

The objective of the development of the aerodynamic drag predictive tool CDaero was for use as a module for the Automobile Design Support System (AutoDSS). CDaero is an empirically based drag coefficient predictive tool based initially on the MIRA (Motor Industry Research Association) algorithm. The development philosophy was to be able to predict the aerodynamic drag coefficient of an automobile with knowledge of the features of the surface geometry control curves. These are the curves that control the 3-dimensional geometry as seen in the profile, plan and front and rear views. CDaero has been developed in a computing environment using the equation solver TKSolver™. Fifty-one input feature values are first determined from the automobile geometry and then entered into the program. CDaero models the drag coefficient with thirteen different components covering the basic body, as well as additional components such as the wheels, mud flaps, etc.

In one of the fatigue tests for wet friction materials, “bump test”, an inertia-type rig equipped with a multi-disk assembly is used. One of the steel disks in the assembly has radial bumps for the purpose of creating high local contact pressure and high temperature. Due to the severe contact conditions, a comparative testing for different friction materials can be conducted within a relatively small number of cycles. In the paper, a design of a “bump” assembly used for automotive wet friction materials is described. Based on both experimental tests and advanced contact modeling, non-uniform contact pressure generated by the bumps and resulting temperature are estimated. The computational model is used then to study the influence of the modulus of elasticity of the friction material and reaction plate thickness on the contact conditions. The bump fatigue tests lead ultimately to material failure.

In today’s Automotive world, there is NO need to advocate “Light weighting”. Government policies for carbon footprint reduction combined with high safety standards are driving OEMs to adopt advanced manufacturing technologies. Steel hot forming is selected as most preferred way to reduce weight as it is easy to adopt and commercially known. It had many advantages compare to conventional cold stamping of standard and high tensile steel. The process consists of heating blank to nearly 1000 °C and quenching it in tool to for martensitic structure. Higher strength up to 2000 MPa can be achieved by this process. There are many examples where part weight is reduced by 15 to 20 % by this method. But Steel hot forming has limitation as specific density of steel is still high. Thus, there is limitation to its weight reduction capability. For further reduction, OEMs have started exploring Aluminium hot forming.

Problems of bore distortion, combustion blowby and gasket fatigue in lightweight engine blocks are ultimately related to the gasket sealing pressure distribution. For both conventional embossed steel gaskets and composite ones this distribution can be modified by suitable local changes in gasket stiffness. Current methods of gasket optimization concentrate on large scale iterative finite element analysis of the head/gasket/block system, with major computational costs. We present a more economical alternative in which condensed compliance matrices are obtained either from elementary NASTRAN runs or by experimental means. The algorithm enables the gasket engineer to ‘tune’ the gasket to the desired sealing pressure profile with acceptable stiffness variations.

‘Emotional controlling’ is a very efficient way to realize autonomous behaviour of digital human models by closed loop controls. In particular this is an emotional optimization procedure based upon the ‘Hedonic principle’ and thus following closely the human original. Emotional controlling will be outlined and illustrated by an example demonstrating the specific way force and posture induced discomfort is shaping our movements.

This paper presents a new design method for solving the vehicle vibration problem induced by engine drive, by using a μ-synthesis. We have tried the active control of engine mounts to insulate the vibration of engine. We experimented on the effects by using computer simulation and vibration simulator. Computer simulation results show that resonance peak can be effectively reduced. We have also confirmed the effect of vibration simulator, which shall be reported in this paper.