Refine Your Search

Search Results

Viewing 1 to 6 of 6
Technical Paper

Integrated, Feed-Forward Hybrid Electric Vehicle Simulation in SIMULINK and its Use for Power Management Studies

2001-03-05
2001-01-1334
A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.
Technical Paper

Fuel Cell APU for Silent Watch and Mild Electrification of a Medium Tactical Truck

2004-03-08
2004-01-1477
This paper investigates the opportunities for improving truck fuel economy through the use of a Fuel Cell Auxiliary Power Unit (FC APU) for silent watch, as well as for powering electrified engine accessories during driving. The particular vehicle selected as the platform for this study is a prototype of the Family of Medium Tactical Vehicles (FMTV) capable of carrying a 5 ton payload. Peak stand-by power requirements for on-board power are determined from the projected future digitized battlefield vehicle requirements. Strategic selection of electrified engine accessories enables engine shutdowns when the vehicle is stopped, thus providing additional fuel savings. Proton Exchange Membrane (PEM) fuel cell is integrated with a partial oxidation reformer in order to allow the use of the same fuel (JP8) as for the propulsion diesel engine.
Technical Paper

Experimental and Simulated Results Detailing the Sensitivity of Natural Gas HCCI Engines to Fuel Composition

2001-09-24
2001-01-3609
Natural gas quality, in terms of the volume fraction of higher hydrocarbons, strongly affects the auto-ignition characteristics of the air-fuel mixture, the engine performance and its controllability. The influence of natural gas composition on engine operation has been investigated both experimentally and through chemical kinetic based cycle simulation. A range of two component gas mixtures has been tested with methane as the base fuel. The equivalence ratio (0.3), the compression ratio (19.8), and the engine speed (1000 rpm) were held constant in order to isolate the impact of fuel autoignition chemistry. For each fuel mixture, the start of combustion was phased near top dead center (TDC) and then the inlet mixture temperature was reduced. These experimental results have been utilized as a source of data for the validation of a chemical kinetic based full-cycle simulation.
Technical Paper

Compression Ratio Influence on Maximum Load of a Natural Gas Fueled HCCI Engine

2002-03-04
2002-01-0111
This paper discusses the compression ratio influence on maximum load of a Natural Gas HCCI engine. A modified Volvo TD100 truck engine is controlled in a closed-loop fashion by enriching the Natural Gas mixture with Hydrogen. The first section of the paper illustrates and discusses the potential of using hydrogen enrichment of natural gas to control combustion timing. Cylinder pressure is used as the feedback and the 50 percent burn angle is the controlled parameter. Full-cycle simulation is compared to some of the experimental data and then used to enhance some of the experimental observations dealing with ignition timing, thermal boundary conditions, emissions and how they affect engine stability and performance. High load issues common to HCCI are discussed in light of the inherent performance and emissions tradeoff and the disappearance of feasible operating space at high engine loads.
Technical Paper

System Efficiency Issues for Natural Gas Fueled HCCI Engines in Heavy-Duty Stationary Applications

2002-03-04
2002-01-0417
Homogeneous Charge Compression Ignition (HCCI) has been proposed for natural gas engines in heavy duty stationary power generation applications. A number of researchers have demonstrated, through simulation and experiment, the feasibility of obtaining high gross indicated thermal efficiencies and very low NOx emissions at reasonable load levels. With a goal of eventual commercialization of these engines, this paper sets forth some of the primary challenges in obtaining high brake thermal efficiency from production feasible engines. Experimental results, in conjunction with simulation and analysis, are used to compare HCCI operation with traditional lean burn spark ignition performance. Current HCCI technology is characterized by low power density, very dilute mixtures, and low combustion efficiency. The quantitative adverse effect of each of these traits is demonstrated with respect to the brake thermal efficiency that can be expected in real world applications.
Technical Paper

Design Under Uncertainty and Assessment of Performance Reliability of a Dual-Use Medium Truck with Hydraulic-Hybrid Powertrain and Fuel Cell Auxiliary Power Unit

2005-04-11
2005-01-1396
Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliability-based optimization problems and quantify tradeoffs between optimality and reliability.
X