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As demand for wall-flow Diesel Particulate Filters (DPF) increases, accurate predictions of DPF behavior, and in particular their pressure drop, under a wide range of operating conditions bears significant engineering applications. In this work, validation of a model and development of a simulator for predicting the pressure drop of clean and particulate-loaded DPFs are presented. The model, based on a previously developed theory, has been validated extensively in this work. The validation range includes utilizing a large matrix of wall-flow filters varying in their size, cell density and wall thickness, each positioned downstream of light or heavy duty Diesel engines; it also covers a wide range of engine operating conditions such as engine load, flow rate, flow temperature and filter soot loading conditions. The validated model was then incorporated into a DPF pressure drop simulator.

Precise cycle-to-cycle control of combustion is the major challenge to reduce fuel consumption in Homogenous Charge Compression Ignition (HCCI) engines, while maintaining low emission levels. This paper outlines a framework for simultaneous control of HCCI combustion phasing and Indicated Mean Effective Pressure (IMEP) on a cycle-to-cycle basis. A dynamic control model is extended to predict behavior of HCCI engine by capturing main physical processes through an HCCI engine cycle. Performance of the model is validated by comparison with the experimental data from a single cylinder Ricardo engine. For 60 different steady state and transient HCCI conditions, the model predicts the combustion phasing and IMEP with average errors less than 1.4 CAD and 0.2 bar respectively. A two-input two-output controller is designed to control combustion phasing and IMEP by adjusting fuel equivalence ratio and blending ratio of two Primary Reference Fuels (PRFs).

The Vehicle Engine Cooling System Simulation (VECSS) computer code has been developed at the Michigan Technological University to simulate the thermal response of a cooling system for an on-highway heavy duty diesel powered truck under steady and transient operation. In Part 1 of this research, the code development and verification has been presented. The revised and enhanced VECSS (version 8.1) software is capable of simulating in real-time a Freightliner FLD 120 truck with a Detroit Diesel Series 60 engine, Behr McCord radiator, Allied signal / Garrett Automotive charge air cooler and turbocharger, Kysor DST variable speed fan clutch, DDC oil and coolant thermostat. Other cooling system components were run and compared with experimental data provided by Kysor Cooling Systems. The experimental data were collected using the Detroit Diesel Electronic Control's (DDEC) Electronic Control Module (ECM) and the Hewlett Packard (HP) data acquisition system.

The U.S. Bureau of Mines and Michigan Technological University are collaborating to conduct laboratory evaluations of oxidation catalytic converters (OCCs) and diesel fuels to identify combinations which minimize potentially harmful emissions. The purpose is to provide technical information concerning diesel exhaust emission control to the mining industry, regulators, and vendors of fuel and emission control devices. In this study, an Engelhard PTX 10 DVC (Ultra-10)* OCC was evaluated in the exhaust stream of an indirect injection Caterpillar 3304 PCNA mining engine using a light-duty laboratory transient cycle. This cycle was selected because it causes high emissions of particle-associated organics. Results are also reported for two different fuels with similar sulfur contents (0.03-0.04 wt pct) and a cetane number of 53, but different aromatic contents (11 vs. 20 wt pct).

A review of mine air pollutant standards and the important pollutants to control in underground mines using diesel powered equipment is presented. The underground Mine Air Quality Laboratory instrumentation is discussed. This includes the Mine Air Monitoring Laboratory (MAML) and the instrumented Load Haul Dump (LHD) vehicle. The MAML measures CO, NO2, NO, CO2, particulate and temperatures while the LHD instrumentation measures and records engine speed, rack position (fuel rate), vehicle speed, CO2 concentration, exhaust temperature and operating mode with transducers and a Sea Data Corporation data logging and reader system. The mine LHD cycle data are related to the EPA 13 mode cycle data. Engine and aftertreatment emission control methods are reviewed including recent laboratory NO, NO2, sulfate and particulate data for a monolith catalyst. Maintenance of the LHD vehicle by engine subsystems in relation to component effects on emissions is presented.

Exhaust gas recirculation (EGR) has been employed in a diesel engine to reduce NOx emissions by diluting the fresh air charge with gases composed of primarily N2, CO2, H2O, and O2 from the engines exhaust stream. The addition of EGR reduces the production of NOx by lowering the peak cylinder gas temperature and reducing the concentration of O2 molecules, both of which contribute to the NOx formation mechanism. The amount of EGR has been typically controlled using an open loop control strategy where the flow of EGR was calibrated to the engine speed and load and controlled by the combination of an EGR valve and the ratio of the boost and exhaust back pressures. When oxygenated biofuels with lower specific energy are used, the engine control unit (ECU) will demand a higher fuel rate to maintain power output, which can alter the volumetric flow rate of EGR. In addition, oxygenated biofuels affect the oxygen concentration in the intake manifold gas stream.

A study of the Corning ceramic diesel particulate trap was conducted to investigate the trap's overall effect on diesel particulate fractions (soluble organic fraction. SOF; solid fraction, SOL; and sulfate fraction. SO4) under four different engine loads at 1680 rpm. The trap was found to filter the SOL fraction most efficiently with the SOF and SO4 fraction following in respective order. The filter efficiency of all fractions increased with increasing engine load. Graphs illustrating filter efficiency versus engine load indicate the slope of the SOF filter efficiency was smaller in magnitude than the TPM and SOL and SO4, fractions, which had similar slopes. The different slope of the SOF filter efficiency indicates other influences may be involved with the reduction in the SOF through the trap. Particle size distribution measurements in diluted exhaust revealed particle formation downstream of the trap.

The objective of this research was to obtain diesel particle size distributions from a 1988 and a 1991 diesel engine using three different fuels and two exhaust control technologies (a ceramic particle trap and an oxidation catalytic converter). The particle size distributions from both engines were used to develop models to estimate the composition of the individual size particles. Nucleation theory of the H2O and H2SO4 vapor is used to predict when nuclei-mode particles will form in the dilution tunnel. Combining the theory with the experimental data, the conditions necessary in the dilution tunnel for particle formation are predicted. The paper also contains a discussion on the differences between the 1988 and 1991 engine's particle size distributions. The results indicated that nuclei mode particles (0.0075-0.046 μm) are formed in the dilution tunnel and consist of more than 80% H2O-H2SO4 particles when using the 1988 engine and 0.29 wt% sulfur fuel.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.

Diesel particulate trap regeneration is a complex process involving the interaction of phenomena at several scales. A hierarchy of models for the relevant physicochemical processes at the different scales of the problem (porous wall, filter channel, entire trap) is employed to obtain a rigorous description of the process in a multidimensional context. The final model structure is validated against experiments, resulting in a powerful tool for the computer-aided study of the regeneration behavior. In the present work we employ this tool to address the effect of various spatial non-uniformities on the regeneration characteristics of diesel particulate traps. Non-uniformities may include radial variations of flow, temperature and particulate concentration at the filter inlet, as well as variations of particulate loading. In addition, we study the influence of the distribution of catalytic activity along the filter wall.

Mercury is a high-fidelity, physics-based object-oriented software for conducting simulations of vehicle performance evaluations for requirements and engineering metrics. Integrating cutting-edge, massively parallel modeling techniques for soft, cohesive and dry granular soil that will integrate state-of-the-art soil simulation with high-fidelity multi-body dynamics and powertrain modeling to provide a comprehensive mobility simulator for ground vehicles. The Mercury implements the Chrono::Vehicle dynamics library for vehicle dynamics, which provides multi-body dynamic simulation of wheeled and tracked vehicles. The powertrain is modeled using the Powertrain Analysis Computational Environment (PACE), a behavior-based powertrain analysis based on the U.S. Department of Energy’s Autonomie software. Vehicle -terrain interaction (VTI) is simulated with the Ground Contact Element (GCE), which provides forces to the Chrono-vehicle solver.

Systems engineering is a key discipline to develop, deploy, and sustain military systems. The wide variety of product types and the tendency to leverage emerging technologies require that disciplined technical planning and management processes be used by both engineers and program managers in all phases of a product's life cycle. This paper describes requirements development, management, and architecture in military systems engineering and acquisition be it software or hardware.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

This investigation focuses on conventional powertrain technologies that provide operational synergy based on customer utilization to reduce fuel consumption for a heavy-duty, nonroad (off-road) material handler. The vehicle of interest is a Pettibone Cary-Lift 204i, with a base weight of 50,000 lbs. and a lift capacity of 20,000 lbs. The conventional powertrain consists of a US Tier 4 Final diesel engine, a non-lockup torque converter, a four-speed powershift automatic transmission, and all-wheel drive. The paper will present a base vehicle energy/fuel consumption breakdown of propulsion, hydraulic and idle distribution based on a representative end-user drive cycle. The baseline vehicle test data was then used to develop a correlated lumped parameter model of the vehicle-powertrain-hydraulic system that can be used to explore technology integration that can reduce fuel consumption.

Energy management is one of the key challenges for the development of Hybrid Electric Vehicle (HEV) due to its complex powertrain structure. Hardware-In-the-Loop (HIL) simulation provides an open software architecture which enables rapid prototyping HEV energy management system. This paper presents the investigation of the energy management system for a single shaft parallel hybrid electric vehicle using dSPACE eDrive HIL system. The parallel hybrid electric vehicle, energy management system, and low-level Electronic Control Unit (ECU) were modeled using dSPACE Automotive Simulation Models and dSPACE blocksets. Vehicle energy management is achieved by a vehicle-level controller called hybrid ECU, which controls vehicle operation mode and torque distribution among Internal Combustion Engine (ICE) and electric motor. The individual powertrain components such as ICE, electric motor, and transmission are controlled by low-level ECUs.

This paper studies model predictive control algorithm for Hybrid Electric Vehicle (HEV) energy management to improve HEV fuel economy. In this paper, Model Predictive Control (MPC), a predictive control method, is applied to improve the fuel economy of power-split HEV. A dedicated model predictive control method is developed to predict vehicle speed, battery state of charge (SOC), and engine fuel consumption. The power output from the engine, motor, and the mechanical brake will be adjusted to match driver's power request at the end of the prediction window while minimizing fuel consumption. The controller model is built on Matlab® MPC toolbox® and the simulations are based on MY04 Prius vehicle model using Autonomie®, a powertrain and fuel economy analysis software, developed by Argonne National Laboratory. The study compares the performance of MPC and conventional rule-base control methods.

The Powertrain Analysis and Computational Environment (PACE) is a forward-looking powertrain simulation tool that is ready for a High-Performance Computing (HPC) environment. The code, written in C++, is one actor in a comprehensive ground vehicle co-simulation architecture being developed by the CREATE-GV program. PACE provides an advanced behavioral modeling capability for the powertrain subsystem of a conventional or hybrid-electric vehicle that exploits the idea of reusable vehicle modeling that underpins the Autonomie modeling environment developed by the Argonne National Laboratory. PACE permits the user to define a powertrain in Autonomie, which requires a single desktop license for MATLAB/Simulink, and port it to a cluster computer where PACE runs with an open-source BSD-3 license so that it can be distributed to as many nodes as needed.

The current system requirements for the power management subsystem and ground combat vehicles for the Future Combat System require higher power and voltages for greater energy efficiency, advanced mobility, lethality and survivability. Efficient and reliable electrical power management is an essential capability within current force ground combat vehicles and will become even more important with the increased electrical power demands of future force vehicles which will exceed the capabilities of onboard power generation/storage technologies. This paper describes how to meet the aforementioned power distribution challenges through the development of a power management software interfaces standard that will provide the flexibility required by various programs and vehicles yet still provide a consistent framework for software development providing a consistent environment for all future Army programs.

A simple geometry pneumatic atomizer which could be used on internal combustion engine was tested with water as the working fluid. The pneumatic atomizer consists of a cylindrical chamber with an orifice plate at the outlet end. Liquid flows down the chamber walls and onto the nozzle orifice plate as a film. Air flows down the center of the chamber. The interaction of the air and water, which occurs at the orifice, atomizes the water. Large droplets form near the nozzle orifice and break up as they go down stream. Variations in the droplet size occurred in the spray. When geometry and flow rates were varied, changes which decreased the water film thickness or increased the air velocity at the nozzle orifice yielded smaller droplets in the spray. Droplet size data was measured by Malvern Laser Particle Sizer.

The goal of this work is to develop an efficient numerical modeling method for the vibration of hybrid electric vehicle (HEV) battery packs to support probabilistic forced response simulations and fatigue life predictions. There are two important sources of variations in HEV battery packs that affect their structural dynamic response. One source is the uncertain level of pre-stress due to bolts or welds used for joining cells within a pack. The other source is small structural variations among the cells of a battery pack. The structural dynamics of HEV battery packs are known to feature very high modal density in many frequency bands. That is because packs are composed of nominally identical cells. The high modal density combined with small, random structural variations among the cells can lead to drastic variations in the dynamic response compared with those of the ideal nominal system.