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Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

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.

The discrete droplet model is widely used to describe two-phase flows such as high-velocity dense sprays. The interaction between the liquid and the gas phase is modeled via appropriate source terms in the gas phase equations. This approach can lead to a strong dependence of the liquid-gas coupling on the spatial resolution of the gas phase. The liquid-gas coupling requires the computation of source terms using the gas phase properties, and, subsequently, these sources are then distributed onto the gas phase mesh. In this study, a Lagrange polynomial interpolation method has been developed to evaluate the source terms and also to distribute these source terms onto the gas mesh. The focus of this investigation has been on the momentum exchange between the two phases. The Lagrange polynomial interpolation and source term distribution methods are evaluated for non-evaporating sprays using KIVA3 as a modeling platform.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

Living in the era of rising environmental sensibility and increasing gasoline prices, the development of a new environmentally friendly generation of vehicles becomes a necessity. Hybrid electric vehicles are one means of increasing propulsion system efficiency and decreasing pollutant emissions. In this paper, the series-parallel power-split configuration for Michigan Technological University's FutureTruck is analyzed. Mathematical equations that describe the hybrid power-split transmission are derived. The vehicle's differential equations of motion are developed and the system's need for a controller is shown. The engine's brake power and brake specific fuel consumption, as a function of its speed and throttle position, are experimentally determined. A control strategy is proposed to achieve fuel efficient engine operation. The developed control strategy has been implemented in a vehicle simulation and in the test vehicle.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

Non-evaporating diesel sprays have been simulated utilizing the ETAB and the WAVE atomization and breakup models and have been compared with experimental data. The experimental penetrations and widths were determined from back-lit spray images and the droplet sizes have been measured by means of a Malvern particle sizer. The model evaluation criteria include the spray penetration, the spray width and the local droplet size. The comparisons have been performed for variations of the injection pressure, the gas density and the fuel viscosity. The fuel nozzle exit velocities used in the simulations have been computed with a special code that considers the effect of in-nozzle cavitation. The simulations showed good overall agreement with experimental data. However, the capabilities of the models to predict the droplet size for different fuels could be improved.

Objective of this work is the incorporation of the flame stretch effects in an Eulerian-Lagrangian model for premixed SI combustion in order to describe ignition and flame propagation under highly inhomogeneous flow conditions. To this end, effects of energy transfer from electrical circuit and turbulent flame propagation were fully decoupled. The first ones are taken into account by Lagrangian particles whose main purpose is to generate an initial burned field in the computational domain. Turbulent flame development is instead considered only in the Eulerian gas phase for a better description of the local flow effects. To improve the model predictive capabilities, flame stretch effects were introduced in the turbulent combustion model by using formulations coming from the asymptotic theory and recently verified by means of DNS studies. Experiments carried out at Michigan Tech University in a pressurized, constant-volume vessel were used to validate the proposed approach.

This paper aims to extend the existing Volume of Fluid (VOF) model by implementing an evaporation sub-model in an open source Computational Fluid Dynamics (CFD) software, OpenFOAM. The paper applies the new model to numerically study the evaporation of spherical n-heptane droplets impinging on a hot wall at atmospheric pressure and a temperature above the Leidenfrost temperature. Volume of Fluid (VOF) method is chosen to track the liquid gas interface and the capability of VOF method implemented in interDyMFoam solver of OpenFOAM to simulate hydrodynamics during droplet-droplet interaction and droplet-film interaction is explored. Firstly, the in-built solver is used to simulate problems in isothermal conditions and the simulation results are compared qualitatively with the published results to validate the solver. A numerical method for modeling heat and mass transfer during evaporation is implemented in conjunction with the VOF.

Diesel combustion and emissions formation is largely spray and mixing controlled and hence understanding spray parameters, specifically vaporization, is key to determine the impact of fuel injector operation and nozzle design on combustion and emissions. In this study, an eight-hole common rail piezoelectric injector was tested in an optically accessible constant volume combustion vessel at charge gas conditions typical of full load boosted engine operation. Liquid penetration of the eight sprays was determined via processing of images acquired from Mie back scattering under vaporizing conditions by injecting into a charge gas at elevated temperature with 0% oxygen. Conditions investigated included a charge temperature sweep of 800 to 1300 K and injection pressure sweep of 1034 to 2000 bar at a constant charge density of 34.8 kg/m₃.

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 paper describes an experimental activity on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel at engine-like conditions. The influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio) has been studied by spraying fuel in an optically-accessible constant-volume combustion vessel. A high-speed imaging system, capable of acquiring Mie-scattering and Schlieren images in a near simultaneous fashion mode along the same line of sight, has been developed at the Michigan Technological University using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies have been performed at three injection pressures (70, 120 and 180 MPa), 23.9 kg/m3 ambient gas density and 900 K gas temperature in the vessel.

Battery State of Charge (SOC) constraints are used to prevent the battery in Hybrid Electric Vehicles (HEVs) from over-charging or over-discharging. These constraints strongly influence the power-split of the HEV. This paper presents results on how Battery State of Charge (SOC) constraints effects Lithium ion battery aging and fuel economy when using the Equivalent Consumption Minimization Strategy (ECMS). The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’ ANR26650 battery cell. Vehicle simulation uses multiple combinations of highway and city drive cycles. For each combination of drive cycles, nine SOC constraints ranges are used. Battery aging is evaluated using a semi-empirical model combined with the accumulated Ah-throughput method which uses, as an input, the battery SOC trajectory from the vehicle simulations. The simulation results provide insight into how SOC constraints effect fuel economy as well as battery aging.

The Society of Automotive Engineers' (SAE) Clean Snowmobile Challenge 2004 (CSC 2004) was held at Michigan Technological University in Houghton, Michigan, from March 15 - 20, 2004. The Clean Snowmobile Challenge has been a competition in the SAE Collegiate Design Series since 2000, and began in Jackson Hole, Wyoming, as a response to rising concerns about snowmobiling in environmentally-sensitive areas. Teams from fifteen universities competed in CSC 2004. The winning snowmobile (sled) was developed by the University of Wisconsin, Madison, and featured a four-stroke engine with electronic fuel injection (EFI), a two-stage tuned muffler, and catalytic exhaust aftertreatment. A hybrid-electric design was used to increase the snowmobile's powertrain output and improve acceleration. [8] Teams should be competitive in all events to gain enough points to win the competition.

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 used along with dilute emission data to characterize two catalyzed particulate filters (CPFs) having different catalyst loading and catalyst application processes. The model was calibrated and validated with data obtained from steady state experiments conducted using a 1995 Cummins M11-330E heavy-duty diesel engine with manual EGR with different fuels for the two different CPFs. The two different catalyzed particulate filters were CPF III (5 gms/ft3 Pt) and CPF V (50 gms/ft3 Pt). Both the CPFs had cordierite substrates with CPF III and CPF V had MEX and NEX catalyst type formulation respectively. The CPF III filter was catalyzed using a solution-impregnated process while the CPF V filter was catalyzed using a wash coat process.

This investigation is a continuation of a previous study by these authors in which a Lagrange polynomial interpolation method was developed to evaluate spray source terms and also to distribute the source terms onto the gas mesh; the method was applied to the liquid-gas momentum exchange. For this investigation, the method has been extended to the mass exchange between the liquid and gas phases due to evaporation. The Lagrange polynomial interpolation and source term distribution methods are applied to the liquid-gas mass and momentum exchange and are evaluated for evaporating sprays using KIVA3 as a modeling platform. These methods are compared with the standard “nearest neighbor” method of KIVA3, and experimental data are used to establish their validity. The evaluation criteria used include the liquid and vapor spray penetration, gas velocities and the computational stability.

The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

This paper reports an experimental and numerical investigation on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel spray under engine-like conditions. The high pressure diesel spray was investigated in an optically-accessible constant volume combustion vessel for studying the influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio). Measurements were carried out by a high-speed imaging system capable of acquiring Mie-scattering and schlieren in a nearly simultaneous fashion mode using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies were performed at three injection pressures (70, 120, and 180 MPa), 23.9 kg/m3 ambient gas density, and 900 K gas temperature in the vessel.