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Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

A 2-D computational model was developed to describe the flow and filtration processes, in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state trap loading, as well as the transient behavior of the flow and filtration processes. The theoretical model includes the effect of a copper fuel additive on trap loading and transient operation. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations. The filtration theory incorporated in the time dependent numerical code included the diffusion, inertia, and direct interception mechanisms. Based on a measured upstream particle size distribution, using the filtration theory, the downstream particle size distribution was calculated. The theoretical filtration efficiency, based on particle size distribution, agreed very well (within 1%) with experimental data for a number of different cases.

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.

A further development of the ETAB atomization and drop breakup model for high pressure-driven liquid fuel jets, has been developed, tuned and validated. As in the ETAB model, this breakup model reflects a cascade of drop breakups, where the breakup criterion is determined by the Taylor drop oscillator and each breakup event resembles experimentally observed breakup mechanisms. A fragmented liquid core due to inner-nozzle disturbances is achieved by injecting large droplets subject to this breakup cascade. These large droplets are equipped with appropriate initial deformation velocities in order to obtain experimentally observed breakup lengths. In contrast to the ETAB model which consideres only the bag breakup or the stripping breakup mechanism, the new model has been extended to include the catastrophic breakup regime. In addition, a continuity condition on the breakup parameters has lead to the reduction of one model constant.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

High fidelity engine simulation requires realistic fuel models. Although typical automotive fuels consist of more than few hundreds of hydrocarbon species, researches show that the physical and chemical properties of the real fuels could be represented by appropriate surrogate fuel models. It is desirable to represent the fuel using the same set of physical and chemical surrogate components. However, when the reaction mechanisms for a certain physical surrogate component is not available, the chemistry of the unmatched physical component is described using that of a similar chemical surrogate component at the expense of accuracy. In order to reduce the prediction error while maintaining the computational efficiency, a method of on-the-fly reactivity adjustment (ReAd) of chemical reaction mechanism along with fuel re-distribution based on reactivity is presented and tested in this study.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

For an automotive application of a fuel cell power system, it is important to maximize the fuel conversion efficiency, while also providing the required peak power levels for vehicle performance. This paper first compares the fuel conversion efficiency and power density of a state-of-the-art direct-methanol fuel cell (DMFC) with the equivalent parameters of a state-of-the-art direct-hydrogen fuel cell (DHFC). The cell level comparison is then extended to the system level for a potential ZEV automotive application. It is concluded that a DMFC-powered vehicle can become directly competitive with a DHFC-powered ZEV (Zero Emission Vehicle) in any localities or market niches where ZEVs are “a condition of doing business” as a vehicle manufacturer. Following a brief outline of the experimental conditions used to generate the DMFC data reported and analyzed in this paper, a technique for optimizing the conversion efficiency of a DMFC is briefly reviewed.

Damping measurements on vehicle subsystems are rarely straightforward due to the complexity of the dynamic interaction of system joints, trim, and geometry. Various experimental techniques can be used for damping estimation, such as frequency domain modal analysis curve-fitting methods, time domain decay-rate methods, and other methods based on energy and wave propagation. Each method has its own set of advantages and drawbacks. This paper describes an analytical and an experimental comparison between two, widely used loss factor estimation techniques frequently used in Statistical Energy Analysis (SEA). The single subsystem Power Injection Method (PIM) and the Impulse Response Decay Method (IRDM) were compared using analytical models of a variety of simulated simple spring-mass-damper systems. Frequency averaged loss factor values were estimated from both methods for comparison.

Time-averaged temperatures at critical locations on the piston of a direct-fuel injected, two-stroke, 388 cm3, research engine were measured using an infrared telemetry device. The piston temperatures were compared to data [7] of a carbureted version of the two-stroke engine, that was operated at comparable conditions. All temperatures were obtained at wide open throttle, and varying engine speeds (2000-4500 rpm, at 500 rpm intervals). The temperatures were measured in a configuration that allowed for axial heat flux to be determined through the piston. The heat flux was compared to carbureted data [8] obtained using measured piston temperatures as boundary conditions for a computer model, and solving for the heat flux. The direct-fuel-injected piston temperatures and heat fluxes were significantly higher than the carbureted piston. On the exhaust side of the piston, the direct-fuel injected piston temperatures ranged from 33-73 °C higher than the conventional carbureted piston.

Biofuels, such as ethanol and butanol, have been the subject of significant political and scientific attention, owing to concerns about climate change, global energy security, and the decline of world oil resources that is aggravated by the continuous increase in the demand for fossil fuels. This study evaluated the potential emissions impacts of different alcohol blends on a fleet of modern gasoline vehicles. Testing was conducted on a fleet of nine vehicles with different combinations of ten fuel blends over the Federal Test Procedure and Unified Cycle. The vehicles ranged in model year from 2007-2014 and included four vehicles with port fuel injection (PFI) fueling and five vehicles with direct injection (DI) fueling. The ten fuel blends included ethanol blends at concentrations of 10%, 15%, 20%, 51%, and 83% by volume and iso-butanol blends at concentrations of 16%, 24%, 32%, and 55% by volume, and an alcohol mixture giving 10% ethanol and 8% iso-butanol in the final blend.

This paper describes the results of experiments that were performed using a Ground Research Vehicle (GRV) at the National Aeronautics and Space Administration's (NASA) Dryden Flight Research Center in Edwards, CA and a comparison with computational results. The GRV is a modified 1984 General Motors (GMC) van and measures 40 feet long and 9 feet high, with a base area of 83 by 83, and it weighs 10260 lbs and holds a crew of up to three. Air data is measured from a nose-boom, 2 global positioning (GPS) units, and an absolute Honeywell Pressure Transducer with 4 Electronic Signal Processor (ESP) scanners and 64 surface pressure ports. This allows for detailed measurements of the surface pressure profiles around the vehicle. The total vehicle drag is estimated from coast-down tests, while the pressure component of the drag force may be calculated by integrating the pressure profiles on the front and base of the vehicle.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

In order to comply with 2002 EPA emissions regulations, cooled exhaust gas recirculation (EGR) will be used by heavy duty (HD) diesel engine manufacturers as the primary means to reduce emissions of nitrogen oxides (NOx). A feedforward controlled EGR cooling system with a secondary electric water pump and proportional-integral-derivative (PID) feedback has been designed to cool the recirculated exhaust gas in order to better realize the benefits of EGR without overcooling the exhaust gas since overcooling leads to the fouling of the EGR cooler with acidic residues. A system without a variable controlled coolant flow rate is not able to achieve these goals because the exhaust temperature and the EGR schedule vary significantly, especially under transient and warm-up operating conditions. Simulation results presented in this paper have been determined using the Vehicle Engine Cooling System Simulation (VECSS) software, which has been developed and validated using actual engine data.

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.

For automotive applications, it is necessary to maximize the fuel conversion efficiency of a PEM direct-methanol fuel cell (DMFC) over the broadest possible dynamic range of power. The research reported here critically examines the efficiency of the DMFC stack when operated over a broad power range. This research establishes a basis for a control strategy that simultaneously: optimizes DMFC fuel conversion efficiency versus power level, leads into a system level optimization of efficiency vs. power, and provides an operational strategy for controlling a direct-methanol fuel cell for maximum fuel efficiency from minimum to maximum power demand. First, there is an explanation of the experimental conditions used to obtain the DMFC experimental data that is reported and analyzed. Next the DMFC methanol crossover phenomenon is discussed and characterized. Then the conceptual framework for the optimization of fuel conversion efficiency is presented.

For studying the effects of injection system properties and combustion chamber conditions on the penetration lengths of both the liquid and the vapor phase of fuel injectors in Diesel engines, a holistic injection model was developed, combining hydraulic and spray modeling into one integrated simulation tool. The hydraulic system is modeled by using ISIS (Interactive Simulation of Interdisciplinary Systems), a one dimensional in–house code simulating the fuel flow through hydraulic systems. The computed outflow conditions at the nozzle exit, e.g. the dynamic flow rate and the corresponding fuel pressure, are used to link the hydraulic model to a quasi–dimensional spray model. The quasi–dimensional spray model uses semi–empirical 1D correlation functions to calculate spray angle, droplet history and droplet motion as well as penetration lengths of the liquid and the vapor phases. For incorporating droplet vaporization, a single droplet approach has been used.

A methodology to estimate the mass of particulate retained in a catalyzed particulate filter as a function of measured total pressure drop, volumetric flow rate, exhaust temperature, exhaust gas viscosity and cake and wall permeability applicable to real-time computation is discussed. This methodology is discussed from the view point of using it to indicate when to initiate active regeneration and as an On-Board Diagnostic tool to detect filter failures. Steady-state loading characterization experiments were conducted on a catalyzed diesel particulate filter (CPF) in a Johnson Matthey CCRT® (catalyzed continuously regenerating trap) system. The experiments were performed using a 10.8 L 2002 Cummins ISM heavy-duty diesel engine. Experiments were conducted at 20, 60 and 75% of full engine load (1120 Nm) and rated speed (2100 rpm) to measure the pressure drop, transient filtration efficiency, particulate mass balance, and gaseous emissions.

Monitoring of the wear rate of a diesel engine will yield valuable information regarding the wear mechanism within a diesel engine and ultimately will improve the predictions of failing engines and/or their components to allow preventive maintenance which will prolong the life of the engine. A mathematical model was developed that describes the wear particle concentration as a function of time in a diesel engine. This model contains engine and lubrication system parameters that determine the concentration of wear particles in the engine sump. These variables are the oil system volume, oil flow rate, particle generation rate, filtering efficiency and the initial particle concentration. The model has been employed to study the wear particle concentrations in the sump and the mass of particles in the filter for the Cummins VT-903 diesel engine.

In order to further characterize and optimize the performance of Selective Catalytic Reduction (SCR) aftertreatment systems used on heavy-duty diesel engines, an accurately calibrated high-fidelity multi-step global kinetic SCR model and a reduced order estimator for on-board diagnostic (OBD) and control are desirable. In this study, a Cu-zeolite SCR catalyst from a 2010 Cummins ISB engine was experimentally studied in a flow reactor using carefully designed protocols. A 2-site SCR model describing mass transfer and the SCR chemical reaction mechanisms is described in the paper. The model was calibrated to the reactor test data sets collected under temperatures from 200 to 425 °C and SCR space velocities of 60000, 90000, and 120000 hr-1. The model parameters were calibrated using an optimization code to minimize the error between measured and simulated NO, NO₂, N₂O, and NH₃ gas concentration time histories.