Ride Vibration Measurements of Agricultural Tractor and Trailer Combinations

Tractor ride vibration levels have been measured when operating with and without a two wheel (2W) unbalanced and a four wheel (4W) balanced trailer. Measurements were made in the vertical, pitch, longitudinal and roll directions with the trailers unladen and laden over four typical farm surfaces

The results showed that tractor ride vibration levels were usually increased in all directions-particularly the longitudinal direction- when operating with the laden trailers. But for the unladen trailers, they were increased only in the longitudinal direction. Predominant tractor frequencies tended to be lower with the trailers attached, and coupling between the tractor longitudinal, vertical, roll and pitch co-ordinates was generally increased

Comparisons of the results with the trends predicted by a simplified theoretical model of a tractor and 2W trailer, suggested that the model should be extended to include, (a) the roll direction, (b) more realistic ground inputs, and (c) a 4W trailer     

Tractor Handling during Control Loss on Sloping Ground

Tractor behaviour on sloping ground following a control loss due to rear wheel locking is examined. A mathematical model to predict the tractor trajectory is presented and the results obtained from this model are compared with those obtained from experiments with a remotely controlled tractor.

Reasonable agreement is reached between measured and predicted results - the discrepancies arise from limited tyre data or local random variations in slope, ground roughness or tyre/ground frictional values.

Within these limitations, the model is used to examine possible driver strategies following a control loss. Applying and maintaining full lock for this particular type of accident appears to improve safety; it certainly tends to avoid the worst situation in which the tractor accelerates backwards down the slope and reaches dangerously high speeds although inevitably it increases the likelihood of a low speed overturn.     

Steering and Dynamic Stability of Railway Vehicles

For railway vehicles having coned wheels mounted on solid axles there is a conflict between dynamic stability and steering ability

It is shown that the stiffness and kinematic properties of all possible interwheelset connections are characterised by two properties describing the distortional characteristics of the vehicle in plan. Within this framework, the various possibilities for steered wheelsets are considered, and several past and current proposals are reviewed. Using the linear approach to dynamic stabibty and curve negotation the performance of existing and newly proposed configurations is discussed

For any symmetric, two-axle vehicle it is shown that for perfect steering on a curve there should be zero bending stiffness between the wheelsets. It is further shown that if the bending stiffness is zero, the vehicle lacks dynamic stability as the critical speed of instability, is zero. In this case, the vehicle undergoes a steering oscillation which occurs at the kinematic frequency of a single wheelset and which is a motion in which pure rolling occurs

Similar results are obtained with vehicles with three or more axles if adjacent axles are connected by shear structures. However, it is shown that it is possible to satisfy both the requirements of perfect steering and a non-zero critical speed if the vehicle has zero bending stiffness and if, in addition to adjacent wheelsets being connected in shear, at least one pair of non-adjacent axles are connected by a shear structure.     

Analysis of wheel speed vibrations for road friction classification

ABSTRACT

With higher level of vehicle automation, it becomes increasingly important to know the maximum possible tyre forces during normal driving. An interesting method in this respect is estimating the tyre–road friction from the resonance peak in the wheel speed signal, excited by road roughness. A simulation environment using the MF-Swift tyre model is proposed, which gives insight in the correctness and functioning of this method. From implementing the estimation algorithm and considering the tyre torsional vibration system, it is concluded that frequencies and damping ratios can be estimated with reasonable accuracy and that the trends observed with changing road friction are consistent. Furthermore, the proposed simulation environment gives opportunity to investigate other issues like robustness of the estimation method to road roughness. Additionally, the tyre modelling aspect of the estimation method is analysed and improvements are proposed.     

Optimal tyre usage for a Formula One car

Variations in track temperature, surface conditions and layout have led tyre manufacturers to produce a range of rubber compounds for race events. Each compound has unique friction and durability characteristics. Efficient tyre management over a full race distance is a crucial component of a competitive race strategy. A minimum lap time optimal control calculation and a thermodynamic tyre wear model are used to establish optimal tyre warming and tyre usage strategies. Lap time sensitivities demonstrate that relatively small changes in control strategy can lead to significant reductions in the associated wear metrics. The illustrated methodology shows how vehicle setup parameters can be optimised for minimum tyre usage.     

Effect of injection timing,injector opening pressure,injector nozzle geometry,and swirl on the performance of a direct injection,compression-ignition engine fuelled with honge oil methyl ester (HOME)

Increasing petroleum prices, increasing threat to the environment from exhaust emissions and global warming have generated intense international interest in developing renewable and alternative non-petroleum fuels for engines. Evolving feasible technology and recurring energy crisis necessitated a continued investigation into the search for sustainable and clean-burning renewable fuels. In this investigation, Honge oil methyl ester (HOME) was used in a four stroke, single cylinder diesel engine. Tests were carried out to study the effect of fuel injection timing, fuel injector opening pressure (IOP) and injector nozzle geometry on the performance and combustion of CI engine fuelled with HOME. Injection timing was varied from 19°bTDC (before top dead centre) to 27°bTDC in incremental steps of 4°bTDC; injector opening pressure was varied from 210 bar to 240 bar in steps of 10 bar. Nozzle injectors of 3, 4 and 5 holes, each of 0.2, 0.25 and 0.3 mm size were selected for the study. It was concluded that retarded injection timing of 19°bTDC, increased injector opening pressure of 230 bar and 4 hole nozzle injector of 0.2 mm size resulted in overall better engine performance with increased brake thermal efficiency (BTE) and reduced HC, CO, smoke emissions. Further air-fuel mixing was improved using swirl induced techniques which enhanced the engine performance as well.     

Novel large scale simulation process to support dot’s cafe modeling system

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.     

Identifying peer states for transportation system evaluation &; policy analyses

The majority of comparisons between state transportation systems do not control for characteristics that may vary greatly between states (e.g., vehicle miles traveled). A shortcoming of such analyses is that a state’s individual characteristics can be highly influential in determining how transportation policy is set and funds are spent. The purpose of this paper is to extend previous efforts to create groups of similar peer states by developing a new methodological framework that incorporates demographic, temporal, and locational variability into the peer group delineations. We collected historical data for 42 variables on transportation infrastructure, population, economy, growth, topography and weather. To examine trends before and after the passage of ISTEA we gathered data over two time periods: 1985 through 1990 and 1995 through 2000. Using principal components analysis (PCA) we reduced variables into seven components, and then statistically clustered states into peer groups for each time period based on the components and the remaining variables. We identified a range of cluster solutions and demonstrate how cluster statistics help to describe the contextual basis behind the peer grouping. The results of this study are to provide government agencies, researchers and the public with a systematic methodological framework for identifying peer states that reflect similar attributes contributing to the development and maintenance of state transportation systems.