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Nitrites have long been added to heavy-duty coolant to inhibit iron cylinder liner corrosion initiated by cavitation. However, in heavy-duty use, nitrites deplete from the coolant, which then must be refortified using supplemental coolant additives (SCA's). Recently, carboxylates have also been found to provide excellent cylinder liner protection in heavy-duty application. Unlike nitrites, carboxylate inhibitors deplete slowly and thus do not require continual refortification with SCA's. In the present paper laboratory aging experiments shed light on the mechanism of cylinder liner protection by these inhibitors. The performance of carboxylates, nitrites and mixtures of the two inhibitors are compared. Results correlate well with previously published fleet data. Specifically, rapid nitrite and slow carboxylate depletion are observed. More importantly, when nitrite and carboxylates are used in combination, nitrite depletion is repressed while carboxylates deplete at a very slow rate.

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.

Catalytic converters have become a viable aftertreatment system for reducing emissions from on-highway diesel engines. This paper addresses the development and production qualification of a catalytic converter. The testing programs that were utilized to qualify the converter system for production included emissions performance, emissions durability, physical durability, and field test programs. This paper reports on the specific tests that were utilized for the emissions performance and emissions durability testing programs. An explanation on the development of an accelerated durability test program is also included. The physical durability section of the paper discusses the development and execution of laboratory bench tests to insure the catalytic converter/muffler maintains acceptable physical integrity.

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.

Fluid power systems are widely used in agricultural and construction equipment for power conversion and transmission. Solving dynamic stability problems associated with complex and inherently nonlinear fluid power systems on this equipment is very challenging. In the past ten years, a new technology named SNAS (Symbolic/Numeric Analysis/Synthesis) has been developed and implemented by the author (Jiao Zhang). SNAS has been successfully applied to fluid power engineering area for optimizing system dynamic performance. In this paper the fundamentals of SNAS will be discussed and the successful application of SNAS to solve a hydrostatic drive instability problem will be presented.

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.

A typical cab used on agriculture machines is made up of a metal frame structure with large enclosing panels of glass, plastic, and metal. Acoustic treatments such as coatings, textiles and foams are used within the cab for aesthetics but also to mediate undesired noise. To develop effective designs for the cab to combat noise, accurate tools for measurement, and predictive methods for sound transmission loss are needed. This paper focuses on Sound Transmission Loss (STL) of the rear upper panel of a cab used in agriculture machines. Results from CAE based tools such as Statistical Energy Analysis (SEA), Finite Element Analysis (FEA) and Hybrid FE-SEA methods are compared to measurements. The panel studied included features such as curvature, deep drawn beads with a glass window and a damping coating. The simulation results are refined by incorporating methods for accurate modeling of ribs stiffness, curvature effect and radiation efficiency by synthetic modal approach.

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.

The need to accurately measure and record the payload of large off-highway mining trucks was identified by The Broken Hill Proprietary Co. Ltd. (BHP). In response. Caterpillar designed and developed a system to fufill that need. The payload carried by mine haul trucks has a strong influence on production rates and costs. The system developed should enable payloads to be much better controlled than has been previously possible. The system also provides a number of mine management features. The development of the system is described from the concept stage to the production stage. Final production capabilities of the microprocessor based system are described. Payload measurement capabilities, diagnostic capabilities, data storage, and data extraction methods are discussed.

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.

Alternative compression ignition engine fuels are of interest both to reduce emissions and to reduce U.S. petroleum fuel demand. A Malaysian Fischer-Tropsch gas-to-liquid fuel was compared with California #2 diesel by characterizing emissions from over the road Class 8 tractors with Caterpillar 3176 engines, using a chassis dynamometer and full scale dilution tunnel. The 5-Mile route was employed as the test schedule, with a test weight of 42,000 lb. Levels of oxides of nitrogen (NOx) were reduced by an average of 12% and particulate matter (PM) by 25% for the Fischer-Tropsch fuel over the California diesel fuel. Another distillate fuel produced catalytically from Fischer-Tropsch products originally derived from natural gas by Mossgas was also compared with 49-state #2 diesel by characterizing emissions from Detroit Diesel 6V-92 powered transit buses, three of them equipped with catalytic converters and rebuilt engines, and three without.

Remote controlled operation of construction equipment has been state-of-the-art for some years. The availability of remote controls which have been designed and developed for general use on commercial machines is a recent development that is the subject of this paper. The John Deere teleoperated excavator represents a new capability that is now available to the construction industry for use on construction sites that preclude the on-site presence of human operators. This paper will describe the basic machine, the controls, vision system and integration of the remote control adjunct to the operational system. Much of the development of the initial capability was done with the cooperation of Vectran Corporation of Pittsburgh, Pennsylvania.

The objective of this project was to model and study the interior noise in an Off-Highway Truck cab using Statistical Energy Analysis (SEA). The analysis was performed using two different modeling techniques. In the first method, the structural members of the cab were modeled along with the panels and the interior cavity. In the second method, the structural members were not modeled and only the acoustic cavity and panels were modeled. Comparison was done between the model with structural members and without structural members to evaluate the necessity of modeling the structure. Correlation between model prediction of interior sound pressure and test data was performed for eight different load conditions. Power contribution analysis was performed to find dominant paths and 1/3rd octave band frequencies.

Smaller locomotives often use mechanical transmissions instead of diesel-electric drive systems typically used in larger locomotives. This paper discusses how Model Based Design was used to develop the complete drive train control system for a 24 ton sugar cane locomotive. A complete MATLAB Simulink machine model was built to fully test and verify the shift control logic, traction control, vehicle speed limiting, and braking control for this locomotive application before it was commissioned. The model included the engine, torque converter, planetary transmission, drive line, and steel on steel driving surface. Simulation was used to debug all control code and test and refine control strategies so that the initial field commissioning in remote Australia was executed very quickly with minimal engineering support required.

With the rapid development of artificial intelligence, autonomous driving technology will finally reshape an automotive industry. Although fully autonomous cars are not commercially available to common consumers at this stage, partially autonomous vehicles, which are defined as level 2 and level 3 autonomous vehicles by SAE J3016 standard, are widely tested by automakers and researchers. A typical Human-Machine-Interface (HMI) for a vehicle takes a form to support a human domination role. Although modern driving assistance systems allow vehicles to take over control at certain scenarios, the typical human-machine-interface has not changed dramatically for a long time. With deep learning neural network technologies penetrating into automotive applications, multi-modal communications between a driver and a vehicle can be enabled by a cost-effective solution.

Faced with competitive environments, pressure to lower development costs and aggressive timelines engineers are not only increasingly adopting numerical simulation techniques but are also embracing design optimization schemes to augment their efforts. These techniques not only provide more understanding of the trade-offs but are also capable of proactively guiding the decision making process. However, design optimization and exploration tools have struggled to find complete acceptance and are typically underutilized in many applications; especially in situations where the algorithms have to compete with existing swift decision making processes. In this paper we demonstrate how the type of setup and algorithmic choice can have an influence and make optimization more lucrative in a new product development atmosphere. We also present some results from a design exploration activity, involving linkage and structural development, of an earth moving machine application.

The U.S. Environmental Protection Agency (EPA) established an automobile fuel economy information program shortly after the oil embargo, effective for the 1974 model year. The U.S. Department of Energy (formerly the Federal Energy Administration) joined EPA soon afterward in sponsoring the information program. The program is aimed at furnishing consumers with information on estimated miles per gallon of new cars and light duty trucks. The mechanisms for distributing such information include mandatory display of fuel economy ratings on new vehicles, and copies of a printed Gas Mileage Guide for New Car Buyers required to be made available in car dealer showrooms. The program has gone through a number of changes over the years. Consumer interest in fuel economy has also increased in the past few years. Along with this increasing interest has come increased criticism of the EPA/EOE information program.

Lubricating oil affects the performance of friction materials in transmission, steering and brake systems. The TO-2 Test measured friction retention characteristics of lubricating oils used with sintered bronze friction discs. This paper introduces a new friction performance test for drive train lubricants that will be used to support Caterpillar's new transmission and drive train fluid requirements, TO-4, which measures static and dynamic friction, wear, and energy capacity for six friction materials, and replaces the TO-2 test. The new test device to be introduced is an oil cooled, single-faced clutch in the Link Engineering Co. M1158 Oil/Friction Test Machine.

A three dimensional mathematical model of a Caterpillar mining truck has been developed to simulate transient structural deformation and suspension response of a large mining truck traversing a known rough terrain course. The model incorporates compliant (finite element) representations of the truck frame, dump body, and rear axle housing into a dynamic mechanical system simulation model. Model results - frame acceleration, axle housing elastic deformation, and suspension response (strut pressures and displacements) are correlated with measured data from an instrumented truck traversing the steel speed bump portion of the rough terrain course. Results demonstrate that complex truck behavior can be simulated by combining finite element and mechanical system simulations.