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All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

Software systems on electronically controlled diesel truck engines typically provide diagnostic features to enable the engine mechanic to identify and debug system problems. As future systems become more sophisticated, so will the diagnostic requirements. The advantages of serviceability and accuracy found in todays electronic systems must not be allowed to degrade due to this increased sophistication. One method of maintaining a high level of serviceability and accuracy is to place an even greater priority on diagnostics and servicing in the initial design phase of the product than is done today. In particular, three major goals of future diagnostic systems should be separation of component failures from system failures, prognostication of failures and analysis of engine performance. This paper will discuss a system to realize these goals by dividing the diagnostic task into the Electronic System Diagnostics, Engine System Diagnostics and the Diagnostic Interface.

Off-highway machine mounting system isolation, especially the cab mounting system, significantly affects the operator comfort by providing damping to the harsh inputs and isolating the structure-borne energy from traveling into the cab. Mounting system isolation performance is decided not only by the isolation component, but also the mounting bracket structure, and should be treated as a system. This paper gives a review of how the mounting system isolates structural energy and the effect of the bracket structure stiffness to the mounting system isolation performance.

The effects of fuel composition and engine operating parameters on high-pressure, direct injection gasoline (DIG) injector plugging and deposit formation have been studied. The engine used was a conventional dual-sparkplug, 2.2-liter Nissan engine modified for direct injection using one of the spark plug holes. The engine was run under 20% rich conditions to accelerate deposit formation. A ten-fuel test matrix was designed around T90, sulfur level, and olefin levels indicated in the European gasoline specifications for year 2000. The gasolines, containing no detergents, were formulated using refinery stream blends to match the specified targets. Injector flow loss was monitored by fuel flow to the engine and monitoring oxygen sensors on each of the four cylinders. The impact of fuel composition on deposit formation and injector plugging is discussed. Injector flow loss was strongly influenced by injector tip temperature.

The application of Artificial Intelligence (AI) in the automotive industry can dramatically reshape the industry. In past decades, many Original Equipment Manufacturers (OEMs) applied neural network and pattern recognition technologies to powertrain calibration, emission prediction and virtual sensor development. The AI application is mostly focused on reducing product development and validation cost. AI technologies in these applications demonstrate certain cost-saving benefits, but are far from disruptive. A disruptive impact can be realized when AI applications finally bring cost-saving benefits directly to end users (e.g., automation of a vehicle or machine operation could dramatically improve the efficiency). However, there is still a gap between current technologies and those that can fully give a vehicle or machine intelligence, including reasoning, knowledge, planning and self-learning.

There has been an ongoing interest in replacing mineral oil with more biodegradable and/or fire-resistant hydraulic fluids in many mobile equipment applications. Although many alternative fluids may be more biodegradable, or fire-resistant, or both than mineral oil, they often suffer from other limitations such as poorer wear, oxidative stability, and yellow metal corrosion which inhibit their performance in high-pressure hydraulic systems, particularly high pressure piston pump applications. From the fluid supplier's viewpoint, the development of a definitive test, or series of tests, that provides sufficient information to determine how a given fluid would perform with various hydraulic components would be of interest because it would minimize extensive testing. This is often too slow or prohibitively expensive. Furthermore, from OEM's (original equipment manufacturer's) point of view, it would be advantageous to develop a more effective, industry accepted fluid analysis screening.

The cost of human natural language translation of Service Information, Assembly Instructions, Training Materials, Operator Manuals and other similar documents is a major expense for manufacturers. One translation avoidance method involves replacing most of a document’s text with still and/or animated graphics. While the graphics with minimum text concept has savings potential, clarity of communication must be maintained for widespread application of this technique. The necessary clarity should be achieved if standards are established for the symbols and graphical conventions used. This paper provides an example of a repair procedure documented using the graphics with minimum text paradigm, describes many of the anticipated standards and provides an update on the progress towards achieving a standard development project.

This paper describes a computer simulation of the front suspension of a 1973 Chevrolet Malibu using the ADAMS (Automatic Dynamic Analysis of Mechanical Systems) computer program. The model was proposed by the SAE Fatigue Design and Evaluation Committee for evaluating the speed, economy and accuracy of various computer simulations in predicting displacements and loads in a suspension system. A comparison between experimental and simulated results is given.

In any machinery, avoiding noise and vibration completely is a difficult task due to the structural dynamic behaviors of components. To safeguard the operator, it is important to best isolate the operator station from NVH environment. Cabin isolation is an important aspect to minimize structure borne noise and tactile vibrations to be transferred into the cabin. Isolators are selected based on the isolation system inertial properties at mounting locations in the operating frequency range interested. The most important assumption to select isolators are that the active side and passive side of the isolators are nearly rigid so impedance mismatch is created for effective isolation. This paper describes the importance of dynamic stiffness of the structures on both the active and passive side for better NVH performance.

Most of the history of systems engineering has been focused on processes for engineering a single complex system. However, most large enterprises design, manufacture, operate, sell, or support not one product but multiple product lines of related but varying systems. They seek to optimize time to market, costs of development and production, leverage of intellectual assets, best use of talented human resources, overall competitiveness, overall profitability and productivity. Optimizing globally across multiple product lines does not follow from treating each system family member as an independently engineered system or product. Traditional systems engineering principles can be generalized to apply to families. This article includes a multi-year case study of the actual use of a generic model-based systems engineering methodology for families, Systematica™, across the embedded electronic systems products of one of the world's largest manufacturers of heavy equipment.

Two gasolines may have the same Research octane number, the same Motor octane number, and the same over-all hydrocarbon composition yet differ significantly in road antiknock performance. This paper concludes that such variation can be related to the placement of hydrocarbon types in the boiling range of the gasolines. Specifically, studies show that the low-boiling olefins provided better road performance than did the high-boiling olefins. Also, low-boiling aromatics gave better road ratings than the high-boiling aromatics. The magnitude of these effects varied with vehicle engine speed. For this study, twenty fuels of nominal 100 Research octane number were designed on a statistical basis. Realistic gasoline components were used. Comprehensive laboratory inspections of the fuels and fractions included more than 700 laboratory antiknock ratings, 400 hydrocarbon type analyses, and complete volatility data.

Light-weight 3-D models offer improved communication and visualization for advertising, marketing, service technicians, suppliers and other business partners. These models also may be a ready source of geometry and a window into a company's intellectual property for miscreants seeking to pirate designs and to produce counterfeit or will-fit parts. What approaches and tools are available to help protect a company's intellectual property while enabling it and its business partners to benefit from widespread distribution of 3-D animations and models? How should they be applied to effectively protect intellectual property? This paper provides a general survey of techniques available for protecting intellectual property in 3-D models when sending these files outside of a company and into broad distribution.

Engineering new technology and products challenges managers to balance design innovation and program risk. To do this, managers need methods to judge future results to avoid program and product disasters. Besides the traditional prediction tools of schedule, simulations and “iron tests”, process control standards (with measurements) can also be applied to the development programs to mitigate risks. This paper briefly discusses the theory and case history behind some new process control methods and standards currently in place at Caterpillar's Electrical & Electronics department. Process standards reviewed in this paper include process mapping, ISO9001, process controls, and process improvement models (e.g. SEI's CMMs.)

To improve overall customer experience, it is imperative to minimize the noise levels inside agricultural equipment cab. Up-front prediction of acoustic performance in product development is critical to implement the noise control strategies optimally. This paper discusses the methodology used for virtual modeling of a cab on agricultural equipment for prediction of interior noise. The Statistical Energy Analysis (SEA) approach is suitable to predict high frequency interior noise and sound quality parameters such as articulation index and loudness. The cab SEA model is developed using a commercial software. The structural and acoustic excitations are measured through physical testing in various operating conditions. The interior noise levels predicted by the virtual model are compared with the operator ear noise levels measured in the test unit. The resultant SPL spectrum from SEA correlates well with the test.

Pass-by/exterior noise of earth moving machines (EMM) and forestry machines is becoming a focus at early product development stages. ISO 6395 (2) or EC/2000/14 (1) standards defines exterior noise test procedure for EMM. However, these standards do not provide insights for diagnosing any noise issues which may arise. The analysis challenges are posed by the moving machine and acoustic sources with respect to the stationary hemisphere target microphone on the ground and changing operating condition of sources as function of time. There is need to develop a seamless methodology to identify acoustic sources, quantify respective source strengths and rank partial contributions from each source to the total target microphone response in order to overcome the aforementioned challenges.

The OBD II and EOBD legislation have significantly increased the number of system components that have to be monitored in order to avoid emissions degradation. Consequently, the algorithm design and the related calibration effort is becoming more and more challenging. Because of decreasing OBD thresholds, the monitoring strategy accuracy, which is tightly related with the components tolerances and the calibration quality, has to be improved. A model-based offline simulation of the monitoring strategies allows consideration of component and sensor tolerances as well as a first calibration optimization in the early development phase. AVL applied and improved a methodology that takes into account this information, which would require a big effort using testbed or vehicle measurements. In many cases a component influence analysis is possible before hardware is available for testbed measurements.

The cost of fuel for commercial trucks is second only to labor in the total vehicle operating costs. Therefore, technologies that reduce fuel consumption can have a significant impact on the bottom line for both trucking fleets and owner/operators. Quantifying the fuel savings associated with different technologies, however, is complicated by many factors, and short-term testing often cannot adequately quantify small changes in fuel consumption that, over time, can add up to substantial cost savings on a vehicle. For example, fuel economy gains of less than one percent may not be reliably measurable using fuel tests, and variable environmental and use factors can cast some doubt on the appropriateness of short-term testing.