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Models for off-road vehicles, such as farm equipment and military vehicles, require an off-road tire model in order to properly understand their dynamic behavior on off-road driving surfaces. Extensive literature can be found for on-road tire modeling, but not much can be found for off-road tire modeling. This paper presents an off-road tire model that was developed for use in vehicle handling studies. An on-road, dry asphalt tire model was first developed by performing rolling road force and moment testing. Off-road testing was then performed on dirt and gravel driving surfaces to develop scaling factors that explain how the lateral force behavior of the tire will scale from an on-road to an off-road situation. The tire models were used in vehicle simulation software to simulate vehicle behavior on various driving surfaces. The simulated vehicle response was compared to actual maximum speed before sliding vs. turning radius data for the studied vehicle to assess the tire model.

Modeling the tire forces and moments (F&M) generation, during combined slip maneuvers, which involves cornering and braking/driving at the same time, is essential for the predictive vehicle performance analysis. In this study, a new semi-empirical method is introduced to estimate the tire combined slip F&M characteristics based on flat belt testing machine measurement data. This model is intended to be used in the virtual tire design optimization process. Therefore, it should include high accuracy, ease of parameterization, and fast computational time. Regression is used to convert measured F&M into pure slip multi-dimensional interpolant functions modified by weighting functions. Accurate combined slip F&M predictions are created by modifying pure slip F&M with empirically determined shape functions. Transient effects are reproduced using standard relaxation length equations. The model calculates F&M at the center of the contact patch.

An analytical model based on “vortex sound” theory was investigated for predicting the frequency, the relative magnitude, the onset, and the offset of self-sustained interior pressure fluctuations inside a vehicle with an open sunroof. The “buffeting” phenomenon was found to be caused by the flow-excited resonance of the cavity. The model was applied to investigate the optimal sunroof length and width for a mid-size sedan. The input parameters are the cavity volume, the orifice dimensions, the flow velocity, and one coefficient characterizing vortex diffusion. The analytical predictions were compared with experimental results obtained for a system which geometry approximated the one-fifth scale model of a typical vehicle passenger compartment with a rectangular, open sunroof. Predicted and observed frequencies and relative interior pressure levels were in good agreement around the “critical” velocity, at which the cavity response is near resonance.

A feedback controller bas been developed using robust control techniques to control the sound radiated from turbulent flow driven plates. The control design methodology uses frequency domain loop shaping techniques. System uncertainty, sound pressure level reductions, and actuator constraints are included in the design process. For the wind noise problem, weighting factors have been included to distinguish between the importance of modes that radiate sound and those that do not radiate. The wind noise controller has been implemented in the quiet wind tunnel facility at the Ray W. Herrick Laboratories at Purdue University. A multiple-input, multiple-output controller using accelerometer feedback and shaker control was able to achieve control up to 1000 Hz. Sound pressure level reductions of as much as 15 dB were achieved at the frequencies of the plates modes. Overall reductions over the 100-1000 Hz band were approximately 5 dB.

Binder jetting of sand molds and cores for metal casting provides a scalable and efficient means of producing metal components with complex geometric features made possible only by Additive Manufacturing. Topology optimization software that can mathematically determine the optimum placement of material for a given set of design requirements has been available for quite some time. However, the optimized designs are often not manufacturable using standard metal casting processes due to undercuts, backdraft and other issues. With the advent of binder-based 3D printing technology, sand molds and cores can be produced to make these optimized designs as metal castings.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).

NO and soot emissions from Diesel engines are dependent on several parameters related to the engine design and operating conditions. Multidimensional models are increasingly employed to study the effect of these parameters. In this paper, a multidimensional model for flows, sprays and combustion in engines is employed to study the dependence of NO and soot formation and oxidation on injection timing, injection pressure, chamber temperature, EGR and ignition delay, and compare the computed trends with those observed in experimental studies reported in the literature. Computations are carried out in a typical heavy-duty Diesel engine and additional computations in a constant volume chamber are used to clarify the engine results when appropriate. For several parametric changes, the experimentally observed trends are reproduced. However, several limitations are identified. The structure of the computed combusting jet has differences with those suggested from recent experiments.

Human expert drivers have the unique ability to combine correlated sensory inputs with repetitive learning to build complex perceptive models of the vehicle dynamics as well as certain key aspects of the tire-ground interface. This ability offers significant advantages for navigating a vehicle through the spatial and temporal uncertainties in a given environment. Conventional traction control algorithms utilize measurements of wheel slip to help insure that the wheels do not enter into an excessive slip condition such as burnout. This approach sacrifices peak performance to ensure that the slip limits are generic enough suck that burnout is avoided on a variety of surfaces: dry pavement, wet pavement, snow, gravel, etc. In this paper, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy.

The renewed interest in electric and hybrid-electric vehicles has been prompted by the drastic rise in oil prices in 2008 and launch of new initiatives by the Federal Government. One of the key issues is to promote the incorporation of electric drivetrain in vehicles at all levels and particularly with emphasis on educational activities to prepare the workforce needed for the near future. Purdue University has been conducting a Grand Prix for over 50 years with Gas-powered Karts. In April 2010, an annual event was initiated to hold an EV Grand Prix where 17 EV Karts participated in the competition. Four of the participating teams comprised of Purdue students in a new graduate course for EV design and fabrication. Using the basic framework of the gas-powered Kart, an electric version was developed as a part of this course. Other participants were also provided with the guidelines and design parameters developed for the course and competition.

Energy budgets for future Controlled Ecological Life-Support Systems (CELSS) must balance not only with respect to primary productivity (i.e., photosynthesis) vs. utilization steps (human maintenance plus preparative and recycling processes), but also with respect to necessary and desired nonlife-support activities of crews (e.g., exploration, research). Present objectives of the NSCORT program at Purdue University include identification of critical paths for biomass conversion to desired forms with energetics and rate-constant properties that are compatible with life-support sustainability within a CELSS. Physico-chemical recycling systems working in conjunction with bioregenerative ones likely will be required to keep time constants of critical processes within reasonable limits.

A unique concept for a multi-body test rig enabling the simulation of longitudinal, steering and vertical dynamics was developed at the Institute for Mechatronic Systems (IMS) at TU Darmstadt. A prototype of this IMS test rig is currently being built. In conjunction with the IMS test rig, the Vehicle Terrain Performance Laboratory (VTPL) at Virginia Tech further developed a full car, seven degree of freedom (7 DOF) simulation model capable of accurately reproducing measured displacement, pitch, and roll of the vehicle body due to terrain excitation. The results of the 7 DOF car model were used as the reference input to the multi-body IMS test rig model. The goal of the IMS/VTPL joint effort was to determine whether or not a controller for the IMS test rig vertical actuator could accurately reproduce wheel displacements due to different measured terrain constraints.

Grazing flows over open windows or sunroofs may result in “flow buffeting,” i.e. self-sustained flow oscillations at the Helmholtz acoustic resonance frequency of the vehicle. The associated pressure fluctuations may cause passenger fatigue and discomfort. Many solutions have been proposed to solve this problem, including for example leading edge spoilers, trailing edge deflectors, and leading edge flow diffusers. Most of these control devices are “passive” i.e. they do not involve dynamic control systems. Active control methods, which do require dynamic controls, have been implemented with success for different cases of flow instabilities. Previous investigations of the control of flow-excited cavity resonance have used mainly one or more loudspeakers located within the cavity wall. In this study, oscillated spoilers hinged near the leading edge of the cavity orifice were used. Experiments were performed using a cavity installed within the test section wall of a wind tunnel.

The Porous Ceramic Tube - Nutrient Delivery System (PCT-NDS) offers means to control water availability to plants under non-standard gravities. It is hypothesized that control can be obtained by applying suction pressure within the ceramic tubes. The research objectives include verifying the presented control equation for the PCT-NDS under micro-(less than 1 g) and hyper- (greater than 1 g) gravities. Experiments were conducted on a KC-135 subjecting the system to near-zero to 2 g's and to sustained hyper-gravities upto 10 g's using a centrifuge. Results indicated that the water availability can be controlled through applied suction pressure.

The object of the work reported here was to relate the acoustic intensity level measured near the contact patch of a driven tire on a passenger vehicle with the passby noise levels measured at a sideline microphone during coast and cruise conditions. Based on those measurements it was then possible to estimate the tire noise contribution to the passby level measured when the vehicle under test was accelerating. As part of this testing program, data was collected using five vehicles at fourteen passby sites in the United States: in excess of 800 data sets were obtained.

Accurate terrain models provide the chassis designer with a powerful tool to make informed design decisions early in the design process. It is beneficial to characterize the terrain as a stochastic process, allowing limitless amounts of synthetic terrain to be created from a small number of parameters. A continuous-state Markov chain is proposed as an alternative to the traditional discrete-state chain currently used in terrain modeling practice. For discrete-state chains, the profile transitions are quantized then characterized by a transition matrix (with many values). In contrast, the transition function of a continuous-state chain represents the probability density of transitioning between any two states in the continuum of terrain heights. The transition function developed in this work uses a location-scale distribution with polynomials modeling the parameters as functions of the current state.

The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as vehicle excitation data since most of the excitation exerted on a vehicle as it traverses terrain is provided by the terrain topology. It is currently not efficient to obtain accurate terrain profile data of sufficient length to simulate the vehicle being driven over long distances. Hence, durability and ride quality evaluations of a vehicle depend mostly on data collected from physical tests. Such tests are both time consuming and expensive, and can only be performed near the end of a vehicle's design cycle. This paper covers the development of a methodology to synthesize terrain profile data based on the statistical analysis of physically measured terrain profile data.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP), HEVT is designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended-range hybrid electric vehicle. The competition requires participating teams to improve and redesign a stock Vue XE donated by GM. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an estimated all electric range of 69 km (43 miles) [1].

The pre-prototype development of a simulated rule-based hybrid energy management strategy for a 2019 Chevrolet Blazer RS converted parallel P4 full hybrid is presented. A vehicle simulation model is developed using component bench data and validated using EPA-reported dynamometer fuel economy test data. A combined Willans line model is proposed for the engine and transmission, with hybrid control rules based on efficiency-derived engine power thresholds. Algorithms are proposed for battery state of charge (SOC) management including engine loading and one pedal strategies, with battery SOC maintained within 20% to 80% safe limits and charge balanced behavior achieved. The simulated rule-based hybrid control strategy for the hybrid vehicle has an energy consumption reduction of 20% for the Hot 505, 3.6% for the HwFET, and 12% for the US06 compared to the stock vehicle.

In the case of modern day vehicle control systems employing a feedback control structure, a real-time estimate of the tire-road contact parameters is invaluable for enhancing the performance of the chassis control systems such as anti-lock braking systems (ABS) and electronic stability control (ESC) systems. However, at present, the commercially available tire monitoring systems are not equipped to sense and transmit high speed dynamic variables used for real-time active safety control systems. Consequently, under the circumstances of sudden changes to the road conditions, the driver's ability to maintain control of the vehicle maybe at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available.