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Model-based control strategies are important for meeting the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. To be implementable on the vehicle, the models should capture the essential behavior of the system, while not being computationally intensive. This paper discusses the adequacy of two different reduced order SCR catalyst models and compares their performance with a higher order model. The higher order model assumes that the catalyst has both diffusion and reaction kinetics, whereas the reduced order models contain only reaction kinetics. After describing each model, its parameter identification and model validation based on experiments on a Navistar I6 7.6L engine are presented. The adequacy of reduced order models is demonstrated by comparing the NO, NO2 and NH3 concentrations predicted by the models to their concentrations from the test data.

This paper presents the development of a computer model to simulate fuel usage and emission contributions of the past and future truck and bus population in the United States. The projected future years are beyond 1976 to 1990. The trends in vehicle population growth, yearly miles traveled and ton-miles are also calculated by the model. The model developed is flexible and brings together several technical concepts which reflect recent inputs from industry and government. The formulation of the model is based on a systems approach, in which the several submodels (the "Population," "Mileage," "Fuel Usage," and "Emission") are interrelated. The preliminary quantitative results are discussed to demonstrate the satisfactory performance of the computer model. Increased rates of dieselization are analyzed to determine their effect on reducing fuel consumption and the impact on total emission contributions. The use of the computer model to study an urban area for air quality is discussed.

A microprocessor controlled lubricating oil cooling system of truck diesel engine was designed to minimize the sump oil temperature fluctuation during start-up and nonsteady engine operations. Model reference adaptive control method is utilized in the control system design. The analysis involved in the design of the microprocessor controlled oil cooling system, and the applications of a special vehicle-engine-cooling system (VEC) computer simulation code in the implementation and testing of the model reference adaptive control strategy are described. Using the VEC simulation code, the performance of the microprocessor controlled oil cooling system and the conventionally controlled oil cooling systems were compared for the ATB, temperature disturbances, and cold weather transient tests. An explanation of each test, as well as a review of the results of comparison tests are presented.

This paper presents an approach to modeling the United States truck and bus population. A detailed model is developed that utilizes domestic factory sales figures combined with a scrappage factor as a building block for the total population. Comparison with historical data for 1958-1970 shows that the model follows trends well for intermediate parameters such as total vehicle miles per year, total fuel consumption, scrappage, etc. Fuel consumption and HC, CO, NO2, CO2 and particulate matter emissions for gasoline and diesel engines are of primary interest. The model details these parameters for the time span 1958-2000 in one-year increments. For HC and CO, truck and bus emissions could equal or exceed automobile emissions in the early 1980s, depending on the degree of control. Three population control strategies are analyzed to determine their effects on reducing fuel consumption or air pollution in later years.

In the present work a practice for conducting experiments and analyzing the fundamental descriptors of Diesel Particulate Filter (DPF) flow resistance behavior is described. The recommended practice addresses each of the following areas: definition of flow resistance descriptors, filter geometrical characteristics, experimental setup and data analysis methods. The sources of errors in each area are identified and a sensitivity analysis is performed. Finally, the recommended practice is applied to several filter materials and configurations tested in the laboratory to determine objectively a set of flow resistance descriptors (namely the filter wall permeability, inlet/outlet loss coefficient) and their error bars. It is expected that application of the recommended practice for the determination of the flow resistance descriptors of DPFs will lead to better quality control procedures and meaningful comparisons of experimental data collected at different laboratories.

As use of Particulate Filters (PFs) is growing not only for diesel but also for gasoline powered vehicles, the need for better understanding of deposit structure, growth dynamics and evolution arises. In the present paper we address a number of deposit growth and restructuring phenomena within particulate filters with the aim to improve particulate filter soot load estimation. To this end we investigate the dynamic factors that quantify the amount of particles that are stored within the wall and the restructuring of soot deposits. We demonstrate that particle accumulation inside the porous wall is dynamically controlled by the dimensionless Peclet number and provide a procedure for the estimation of parameters of interest such as the loaded filter wall permeability, the wall-stored soot mass at the onset of cake filtration.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Diesel and gasoline direct injection engines emit nucleation mode particles either under special conditions or as part of their normally emitted size distribution, respectively. Currently, European legislation excludes nucleation mode particles as particle number vehicle emission measurements are limited down to 23 nm. The rationale behind such a cut-off size is based on the avoidance of significant uncertainties inherent in the sampling and measuring of sub-23 nm solid particles. However, the sub-23 nm particles have drawn increased attention since a large fraction of particles emitted by modern vehicles lies in this size range. In this study we investigate the possibility of accurate nucleation mode particles detection by using the Advanced Half Mini Differential Mobility Analyzer (HM-DMA).

Recreational Ecological Vehicle (REV) 74 was an intercollegiate All Terrain Vehicle (ATV) design competition organized by the Milwaukee and Cincinnati Sections of SAE. Students from six colleges built ATV's to compete May 30-June 1, 1974 at Michigan Technological University's Keweenaw Research Center test course. Competing categories of noise level, destructiveness to terrain and a 25 mile race over land and water are discussed from the viewpoint of the technical rules and as to the actual course involved with the competition. Michigan Tech designed and built a 4 wheel steer-4 wheel hydrostatic drive ATV for REV-74. This paper provides a detailed design description of the Michigan Tech vehicle along with a review of several production ATV designs and their specifications. Finally, a report of the results of REV-74 is presented.

The effect of truck dieselization for three levels of diesel penetration into each of the eight classes of trucks is modeled. Diesel and total truck sales, population, mileage and yearly fuel usage data are aggregated by four truck classes representing light, medium, light-heavy and heavy-heavy classes. Four fuel economy scenario's for different technological improvements were studied. Improvement of fuel economy for light and heavy-heavy duty vehicle classes provides significant total fuel savings. Truck dieselization of light and light-heavy duty vehicle classes provides the largest improvement of fuel usage due to the fact that they have large numbers of vehicles and presently have few diesels. Total car and truck fuel usage in the 1980's shows roughly a constant demand with cars decreasing due to improved new fleet fuel economy and trucks increasing due to a larger population with better fuel economy due to dieselization and improved technology.