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Michigan Technological University has established a broad-based university-wide research initiative, termed Wood-to-Wheels (W2W), to develop and evaluate improved technologies for growing, harvesting, converting, and using woody biomass in renewable transportation fuel applications. The W2W program bridges the entire biomass development-production-consumption life cycle with research in areas including forest resources, bioprocessing, engine/vehicle systems, and sustainable decisions. The W2W chain establishes a closed cycle of carbon between the atmosphere, woody biomass, fuels, and vehicular systems that can reduce the accumulation of CO2 in the atmosphere. This paper will summarize the activities associated with the Wood-to-Wheels initiative and describe challenges and the potential benefits that are achievable.

In this paper, two correlations, Windowed Selected Moving Autocorrelation (WSMA) and Tri-Correlation (TriC), are introduced and discussed. The WSMA is simpler than the conventional autocorrelation. WSMA uses less data points to obtain useful signal content at desired frequencies. The computational requirement is therefore reduced compared to the conventional autocorrelation. The simplified TriC provides improved signal to noise separation capability than WSMA does while still requiring reduced computational effort compared to the standard autocorrelation. Very often, computation resource limitation exists for real-time applications. Therefore, the WSMA and TriC offer more opportunities for real-time monitor and feedback control applications in the frequency domain due to their high efficiencies. As an example, applications in internal combustion (IC) engine misfire detection are presented. Simulation and vehicle test results are also presented in this paper.

The introduction of a thin fluid layer between two layers of sheet metal offers a highly effective and economical alternative to the use of constrained viscoelastic damping layers in sheet metal structures. A diesel engine gear cover, which is constructed of two sheet metal sections spot welded together, takes advantage of fluid layer damping to produce superior vibration and sound radiation performance. In this paper, the bending of a double layered plate coupled through a thin fluid layer is modeled using a traveling wave approach which results in a impedance function that can be used to assess the vibration and sound radiation performance of practical double layered plate structures. Guided by this model, the influence of fluid layer thickness and inside-to-outside sheet thickness is studied.

Heavy-duty diesel engine particulate matter (PM) emissions must be reduced from 0.1 to 0.01 grams per brake horsepower-hour by 2007 due to EPA regulations [1]. A catalyzed particulate filter (CPF) is used to capture PM in the exhaust stream, but as PM accumulates in the CPF, exhaust flow is restricted resulting in reduced horsepower and increased fuel consumption. PM must therefore be burned off, referred to as CPF regeneration. Unfortunately, nominal exhaust temperatures are not always high enough to cause stable self-regeneration when needed. One promising method for active CPF regeneration is to inject fuel into the exhaust stream upstream of an oxidation catalytic converter (OCC). The chemical energy released during the oxidation of the fuel in the OCC raises the exhaust temperature and allows regeneration.

A generalized re-normalization group (RNG) turbulence model based on the local "dimensionality" of the flow field is proposed. In this modeling approach the model coefficients C₁, C₂, and C₃ are all constructed as functions of flow strain rate. In order to further validate the proposed turbulence model, the generalized RNG closure model was applied to model the backward facing step flow (a classic test case for turbulence models). The results indicated that the modeling of C₂ in the generalized RNG closure model is reasonable, and furthermore, the predictions of the generalized RNG model were in better agreement with experimental data than the standard RNG turbulence model. As a second step, the performance of the generalized RNG closure was investigated for a complex engine flow.

The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gas-phase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode.

Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner.

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

Numerical modeling of fuel injection in internal combustion engines in a Lagrangian framework requires the use of a spray-wall interaction sub-model to correctly assess the effects associated with spray impingement. The spray impingement dynamics may influence the air-fuel mixing and result in increased hydrocarbon and particulate matter emissions. One component of a spray-wall interaction model is the splashed mass fraction, i.e. the amount of mass that is ejected upon impingement. Many existing models are based on relatively large droplets (mm size), while diesel and gasoline sprays are expected to be of micron size before splashing under high pressure conditions. It is challenging to experimentally distinguish pre- from post-impinged spray droplets, leading to difficulty in model validation.

This paper reviews the engine modeling program in the Powertrain Control Research Laboratory at the University of Wisconsin-Madison, focuses on simulation results obtained from a complete modular turbocharged diesel engine dynamic model developed in this lab, and suggests ways that dynamic engine system models can be used in the design process. It examines the dynamic responses and interactions between various components in the engine system, looks at how these components affect the overall performance of the system in transient and steady state operation.

Reactivity-controlled compression ignition (RCCI) has been shown to be capable of providing improved engine efficiencies coupled with the benefit of low emissions via in-cylinder fuel blending. Much of the previous body of work has studied the benefits of RCCI operation using high injection pressures (e.g., 500 bar or greater) with common rail injection (CRI) hardware. However, low-pressure fueling technology is capable of providing significant cost savings. Due to the broad market adoption of gasoline direct injection (GDI) fueling systems, a market-type prototype GDI injector was selected for this study. Single-cylinder light-duty engine experiments were undertaken to examine the performance and emissions characteristics of the RCCI combustion strategy with low-pressure GDI technology and compared against high injection pressure RCCI operation. Gasoline and diesel were used as the low-reactivity and high-reactivity fuels, respectively.

Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.

The Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

The properties of aluminum alloys reinforced by ceramic nanoparticles (less than 100nm) would be enhanced considerably while the ductility is retained over that of the native alloy. The potential of bulk Al-based metal matrix nano-composites (Al MMNCs) cannot be fully developed for industrial applications unless complex structural Al MMNC components can be fabricated cost effectively, such as by casting. Reliable bulk Al MMNCs cannot be cast unless the nanoparticles can be dispersed and distributed uniformly in molten Al alloys. This paper investigates a high volume production method for high performance aluminum matrix nanocomposites, in particular, the application of high intensity ultrasonic cavitation in mixing and dispersing nano-sized ceramic particles in Al melts to cast bulk Al MMNCs for complex automobile structures. Nano-sized SiC particles have been dispersed in molten aluminum alloy A356 for casting.

Two-Color imaging optics were developed and used to observe soot emission processes in a modern heavy-duty diesel engine. The engine was equipped with a common rail, electronically-controlled, high-pressure fuel injection system that is capable of up to four injection pulses per engine cycle. The engine was instrumented with an endoscope system for optical access for the combustion visualization. Multidimensional combustion and soot modeling results were used for comparisons to enhance the understanding and interpretation of the experimental data. Good agreement between computed and measured cylinder pressures, heat release and soot and NOx emissions was achieved. In addition, good qualitative agreement was found between in-cylinder soot concentration (KL) and temperature fields obtained from the endoscope images and those obtained from the multidimensional modeling.

An experimental study of luminous combustion in a modern diesel engine was performed to investigate the effect of injection parameters on NOX and soot formation via flame temperature and soot KL factor measurements. The two-color technique was applied to 2-D soot luminosity images and area-averaged soot radiation signals to obtain spatially and temporally resolved flame temperature and soot KL factor. The imaging system used for this study was based on a wide-angle endoscope that was mounted in the cylinder head and allowed different views of the combustion chamber. The experiments were carried out on a single-cylinder 2.4 liter D.I. diesel engine equipped with an electronically controlled common-rail injection system. Operating conditions were 1600 rpm and 75% load. The two-color results confirm that retarding the injection timing causes lower flame temperatures and NOX emissions but increased soot formation, independent of injection strategy.

This paper describes the transient spray characteristics of a high pressure, single fluid injector, intended for use in a direct-injection spark-ignited (DISI) engine. The injector was a single hole, pintle type injector and was electronically controlled. A variety of measurement diagnostics, including full-field imaging and line-of-sight diffraction based particle sizing were employed for spray characterization. Transient patternator measurements were also performed to obtain temporally resolved average mass flux distributions. Particle size and obscuration measurements were performed at three locations in the spray and at three injection pressures: 3.45 MPa (500 psi), 4.83 Mpa (700 psi), and 6.21 MPa (900 psi). Results of the spray imaging experiments indicated that the spray shapes varied with time after the start of injection and contained a leading mass, or slug along the center line of the spray.

This paper presents a Short Time Fourier Transform based algorithm to identify unknown parameters in fuel dynamics system during engine cold start and warm-up. A first order system is used to model the fuel dynamics in a port fuel injection engine. The feed forward transient fuel compensation controller is designed based on the identified model. Experiments are designed and implemented to verify the proposed algorithm. Different experiment settings are compared.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.