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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.

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.

In the last years the number of electronic controllers of vehicle dynamics applied to chassis components has increased dramatically. They use lookup table of the primary order vehicle global parameters as yaw rate, lateral acceleration, steering angle, car velocity, that define the ideal behavior of the vehicle. They are usually based on PID controllers which compare the actual behavior of every measured real vehicle data to the desired behavior, from look up table. The controller attempts to keep the measured quantities the same as the tabled quantities by using ESP, TC (brakes and throttle), CDC (control shocks absorbers), EDIFF(active differential) and 4WS (rear wheels active toe). The performances of these controls are good but not perfect. The improvement can be achieved by replacement of the lookup tables with a fast vehicle model running in parallel to the real vehicle.

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.

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.

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.

When a manual transmission (MT) powertrain is subjected to high speeds and high torques, the vehicle driveshaft, and other components experience an increase in stored potential energy. When the engine and driveshaft are decoupled during an up or down shift, the potential energy is released causing clunk during the shift event. The customer desires a smooth shift thus reduction of clunk will improve experience and satisfaction. In this study, a six-speed MT, rear-wheel-drive (RWD) passenger vehicle was used to experimentally capture acoustic and vibration data during the clunk event. To replicate the in-situ results, additional data was collected and analyzed for powertrain component roll and pitch. A lumped parameter model of key powertrain components was created to replicate the clunk event and correlate with test data. The lumped parameter model was used to modify clutch tip-out parameters, which resulted in reduced prop shaft oscillations.

The paper investigates the dynamics of the tire and brake during hard braking or wheel locking, from the view point of a brake manufacturer. A new test rig, named BRAD (BRembo Automotive Dynamometer) is presented which measures the forces acting both at the brake and at the tire-ground interface. Lateral forces are not measured. In the test rig, the ground is represented by a drum. The features of the test rig are presented. The measurement accuracy is declared. The first result is that, near wheel locking, a substantial part of the braking power is generated by the tire and not by the brake. The test rig quantifies such a partitioning of brake power, which is important for current and future electric motorsport activities. Some 30% of the braking power is due to tire during hard braking. The second result is that, due to such important braking power at the tire, the tire is heated up, which increases considerably the maximum friction.

A practical approach for evaluating and validating global system designs for Squeak and Rattle performance is proposed. Using simple slip and rattle models, actual sound and vibration data, and the fundamentals of audiological perception, analysis tools adapted from Chaos Theory are used to establish threshold levels of performance and identify system characteristics which are significant contributors to Squeak and Rattle. Focus on system design is maintained by using a simple rattle noise indicator and relating rattle events to levels of dynamic motion (acceleration, velocity, etc.). The threshold level is defined as the level of acceleration at which the system moves from a non-rattling state to a rattling state. The approach is demonstrated with a simple analytical model applied to an experimental structure under dynamic load.

The influence of the inertia properties (mass, centre of gravity location, and inertia tensor) on the dynamic behaviour of the engine-gearbox system of a car is studied in this paper, devoting particular attention to drivability and comfort. The vibration amplitudes and the natural frequencies of the engine-gearbox system have been considered. Additionally, the loads transmitted to the car body have been taken into account. Both the experimental and the theoretical simulations confirmed that the engine-gearbox vibrations in the range 10 - 15 Hz are particularly sensitive to slight variation of the inertia properties. The effects on engine-gearbox vibrations due to half-axles, exhaust system, pipes and inner engine-gearbox fluids have been highlighted.

A comprehensive research is presented aiming at assessing the ride comfort of subjects seated into road or off-road vehicles. Although many papers and books have appeared in the literature, many issues on ride comfort are still to be understood, in particular, the paper investigates the mutual effects of the posture and the vibration caused mostly from road unevenness. The paper is divided into two parts. In the first part, a mathematical model of a seated subject is validated by means of actual measurements on human subjects riding on a car. Such measurements refer to the accelerations acting at the subject/seat interface (vertical acceleration at the seat cushion and horizontal acceleration at the seat back). A proper dummy is used to derive the seat stiffness and damping.

The traditional method of dynamic characterization of elastomers used in industry has largely been based on sinusoidal input excitation. Discrete frequency sine wave signals at specified amplitudes are used to excite the elastomer in a step-sine sweep fashion. This paper will examine new methods of characterization using various broadband input excitations. These different inputs include continuous sine sweep (chirp), shaped random, and acquired road profile data. Use of these broadband data types is expected to provide a more accurate representation of conditions seen in the field, while helping to eliminate much of the interpolation that is inherent with the classic discrete step-sine technique. Results of the various input types are compared in this paper with those found using the classic discrete step-sine input.

Transient and steady-state kinetic data are herein presented to analyze the inhibiting effect of ammonia on the NH₃-SCR of NO at low temperatures over a Fe-zeolite commercial catalyst for vehicles. It is shown that in SCR converter models a rate expression accounting for NH₃ inhibition of the Standard SCR reaction is needed in order to predict the specific dynamics observed both in lab-scale and in engine test bench runs upon switching on and off the ammonia feed. Two redox, dual site kinetic models are developed which ascribe such inhibition to the spill-over of ammonia from its adsorption sites, associated with the zeolite, to the redox sites, associated with the Fe promoter. Better agreement both with lab-scale intrinsic kinetic runs and with engine test-bench data, particularly during transients associated with dosing of ammonia to the SCR catalyst, is obtained assuming slow migration of NH₃ between the two sites.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

Active regeneration of a catalyzed particulate filter (CPF) is affected by a number of parameters specifically particulate matter loading and inlet temperature. The MTU 1-D 2-Layer CPF model [1] was used to analyze these effects on the pressure drop, oxidation and filtration characteristics of a CPF during active regeneration. In addition, modeling results for post loading experiments were analyzed to understand the difference between loading a clean filter as compared to a partially regenerated filter. Experimental data obtained with a production Cummins regenerative particulate filter for loading, active regenerations and post loading experiments were used to calibrate the MTU 1-D 2-Layer CPF model. The model predicted results are compared with the experimental data and were analyzed to understand the CPF characteristics during active regeneration at 1.1, 2.2 and 4.1 g/L particulate matter (PM) loading and CPF inlet temperatures of 525, 550 and 600°C.

A 1-D 2-layer model developed previously at MTU was used in this research to predict the pressure drop, filtration characteristics and various properties of the particulate filter and the particulate deposit layer. The model was calibrated and validated for this CPF with data obtained from steady state experiments conducted using a 1995 Cummins M11-330E heavy-duty diesel engine with manual EGR and using ULSF. The CPF used is a NGK filter having a cordierite substrate with NEX catalyst type formulation (54% porosity, 15.0 μm mean pore diameter and 50 gms/ft3 Pt). The filter was catalyzed using a wash coat process. The model was used to predict the pressure drop, particulate mass retained inside the CPF, particulate mass filtration efficiency and concentration downstream of the CPF with agreement between the experimental and simulated data.

Physical, chemical, and biological characterization data for the particulate emissions from a Caterpillar 3208 diesel engine with and without Corning porous ceramic particulate traps are presented. Measurements made at EPA modes 3,4,5,9,lO and 11 include total hydrocarbon, oxides of nitrogen and total particulate matter emissions including the solid fraction (SOL), soluble organic fraction (SOF) and sulfate fraction (SO4), Chemical character was defined by fractionation of the SOF while biological character was defined by analysis of Ames Salmonella/ microsome bioassay data. The trap produced a wide range of total particulate reduction efficiencies (0-97%) depending on the character of the particulate. The chemical character of the SOF was significantly changed through the trap as was the biological character. The mutagenic specific activity of the SOF was generally increased through the trap but this was offset by a decrease in SOF mass emissions.