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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 electrical power system is the vital lifeline to most of the control systems on modern vehicles. The demands on the system are highly complex, and a detailed understanding of the system behavior is necessary both to the process of systems integration and to the economic design of a specific control system or actuator. The vehicle electric power system, which consists of two major components: a generator and a battery, has to provide numerous electrical and electronic systems with enough electrical energy. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study.

In this paper, four different levels of finite element models of a full vehicle were developed for ride comfort and brake judder dynamics analysis. The differences between the models are how elasticity of various vehicle components is modeled. The dynamic analysis was performed considering nonlinear effects for the different levels of models. The nonlinear effects were characterized by frequency and amplitude dependent stiffness and damping values of hydraulic engine mounting, suspension lower control arm bushing, tire, shock absorber, and suspension friction. At each modeling level, simulation results were compared to those of test measurements. The differences of the analysis results of these models and the effect of nonlinear characteristics were investigated. The developed models were applied to ride comfort and brake judder dynamics analysis.

A vehicle drifts due to several reasons from its intended straight path even in the case of no steering input. The multibody dynamic analysis of vehicle drift during accelerating and braking are performed. This paper focuses on modeling and evaluating effects of suspension parameters, differential friction, engine mounting and C.G. location of the vehicle under multibody dynamic simulation environment. Asymmetry of geometry and compliance between left and right side is considered cause of drift. The sensitivities of the suspension parameters are presented for each driving condition. In case of acceleration, the interaction of differential friction and driveshaft stiffness and their influence on drift are also studied. For braking condition, suspension parameters such as initial toe variation of rear coupled torsion beam axle type suspension and kingpin inclination deviation of front suspension are studied including the braking force difference.

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.

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.

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.

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 Vehicle Engine Cooling System Simulation (VECSS) computer code has been developed at the Michigan Technological University to simulate the thermal response of the cooling system of an on-highway heavy duty diesel powered truck under steady and transient operation. This code includes an engine cycle analysis program along with various components for the four main fluid circuits for cooling air, cooling water, cooling oil, and intake air, all evaluated simultaneously. The code predicts the operation of the response of the cooling circuit, oil circuit, and the engine compartment air flow when the VECSS is operated using driving cycle data of vehicle speed, engine speed, and fuel flow rate for a given ambient temperature, pressure and relative humidity.

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.

Recently, in accordance with the increased interest of consumer in fuel efficiency due to the phenomenon of high oil price, complaints against actual fuel efficiency in the road in comparison with the certified fuel efficiency have been raised frequently. Especially in case of the hybrid vehicle which is highly popular for the reason of its high fuel efficiency compared with that of existing gasoline car, deviation in the fuel efficiency will be higher compared with that of gasoline car in accordance with the driving mode (downtown/highway), driver's driving style (wild/mild) and external environmental condition (gradient/temperature/altitude). To solve them, this paper developed a method so that the SOC (State Of Charge), EV/HEV mode transition point can be controlled variably in accordance with the driving mode, driver's driving style and external environmental condition by making the most of characteristics of hybrid.

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.

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.

For the improvement of ride quality, development of vibration damping control systems and isolating methods become more important. To define basic ride vibrational modes, the effects of vehicle velocity and wheelbase on the standard road surfaces should be investigated. The different vibrational responses depending on the measurement positions of a vehicle body are presented with the bounce and the pitch motions. A methodology for the isolation of engine mount system's resonance to the road input and periodical excitations of tire/wheel nonuniformity forces are discussed. Using the computer simulation and the experimental results, a useful ride model with respect to the vehicle velocity and the stiffness of engine mount is presented.

An analysis of vehicle engine cooling airflow by means of a one-dimensional, transient, compressible flow model was carried out and revealed that similarity theory could be applied to investigate the variation of the airflow with ambient and operating conditions. It was recognized that for a given vehicle engine cooling system, the cooling airflow behavior could be explained using several dimensionless parameters that involve the vehicle speed, fan speed, heat transfer rate through the radiator, ambient temperature and pressure, and the system characteristic dimension. Using the flow resistance and fan characteristics measured from a prototype cooling system and the computer simulation for the one-dimensional compressible flow model, a quantitative correlation of non-dimensional mass flow rate to three dimensionless parameters for a prototype heavy-duty truck was established. The results are presented in charts, tables, and formulas.

The hardware and software for a prototype computer controlled cooling system for a diesel powered truck has been designed and tested. The basic requirements for this system have been defined and the control functions, previously investigated in a study using the computer simulation model, were incorporated into the software. Engine dynamometer tests on the MACK-676 engine, comparing the conventional cooling system and the computer controlled system, showed the following advantages of the computer controlled system: 1. The temperature level to which the engine warms up to at low ambient temperature, was increased. 2. The faster shutter response reduced the temperature peaks and decreased total fan activity time. 3. The faster fan response reduces fan engagement time which should improve truck fuel economy.

Off road navigation demands ground robots to traverse complex and often changing terrain. Classification and assessment of terrain can improve path planning strategies by reducing travel time and energy consumption. In this paper we introduce a terrain classification and assessment framework that relies on both exteroceptive and proprioceptive sensor modalities. The robot captures an image of the terrain it is about to traverse and records corresponding vibration data during traversal. These images are manually labelled and used to train a support vector machine (SVM) in an offline training phase. Images have been captured under different lighting conditions and across multiple locations to achieve diversity and robustness to the model. Acceleration data is used to calculate statistical features that capture the roughness of the terrain whereas angular velocities are used to calculate roll and pitch angles experienced by the robot.

The advancement in embedded systems and positional accuracy with base station GPS modules created opportunity to develop high performance autonomous ground vehicles. However, the development of vehicle model and making accurate state estimations play vital role in reducing the cross track error. The present research focus on developing Linear Quadratic Gaussian (LQG) with Kalman estimator for autonomous ground vehicle to track various routes, that are made with the series of waypoints. The model developed in the LQG controller is a kinematic bicycle model, which mimics 1/5th scale truck. Further, the cubic spline fit has been used to connect the waypoints and generate the continuous desired/target path. The testing and implementation has been done at APS labs, MTU on the mentioned vehicle to study the performance of controller. Python has been used for simulations, controller coding and interfacing the sensors with controller.

This paper aims to provide the experimental and numerical investigation of a single fuel droplet impingement on the different wall conditions to understand the detailed impinging dynamic process. The experimental work was carried out at the room temperature and pressure except for the variation of the impinged wall temperature. A high-speed camera was employed to capture the silhouette of the droplet impinging on wall process against a collimated light. Water, diesel, n-dodecane, and n-heptane were considered as four different droplets and injected from a precision syringe pump with the volume flow rate of 0.2 mL/min at various impact Weber numbers. The impingement outcomes after droplet impacting on the wall include stick, spread, rebound and splash, which depend on the controlling parameters of Weber number, Reynolds number, liquid and surface properties, etc.