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Life Cycle Analysis (LCA) considers the key environmental impacts for the entire life cycle of alternative products or processes in order to select the best alternative. An ideal LCA would be an expensive and time consuming process because any product or process typically involves many interacting systems and a considerable amount of data must be analysed for each system. Practical LCA methods approximate the results of an ideal analysis by setting limited analysis boundaries and by accepting some uncertainty in the data values for the systems considered. However, there is no consensus in the LCA field on the correct method of selecting boundaries or on the treatment of data set uncertainty. This paper demonstrates a new method of selecting system boundaries for LCA studies and presents a brief discussion on applying Monte Carlo Analysis to treat the uncertainty questions in LCA.

In order to evaluate the potential of several powertrain configurations, a well-to-wheel analysis is performed. Specifically, downsizing / supercharging and variable valve timing is examined and compared against other alternative vehicle concepts. In order to have a fair comparison, each powertrain configuration was added to a base vehicle, such that each vehicle had the same range, the same physical characteristics and similar performance. Upstream energy use and greenhouse gases were calculated with GREET 1.5a and the downstream energy use and greenhouse gases with ADVISOR 3.2. By downsizing / supercharging and adding variable valve timing, a spark ignition internal combustion engine can have comparable downstream overall efficiency, energy use, and greenhouse gas emissions, to a Diesel internal combustion engine.

Life Cycle Assessment (LCA) is commonly used to measure the environmental and economic impacts of engineering projects and/or products. However, there is some uncertainty associated with any LCA study. The LCA inventory analysis generally relies on imperfect data in addition to further uncertainties created by the assessment process itself. It is necessary to measure the effects that data and process uncertainty have on the LCA result and to communicate the level of uncertainty to those making decisions based on the LCA. To accomplish this, a systematic and rigorous means to assess the overall uncertainty in LCA results is required. This paper demonstrates the use of Monte Carlo Analysis to track and measure the propagation of uncertainty in LCA studies. The Monte Carlo technique basically consists of running repeated assessments using random input values chosen from a specified probable range.

The 2003 University of Alberta FutureTruck team is converting a 2002 Ford Explorer to be a pre-transmission, parallel Hybrid Electric Vehicle (HEV). The goals for the FutureTruck competition are to achieve increased fuel economy, while reducing emissions and maintaining the functionality of the stock SUV. The University of Alberta design places a 2.0L Zetec engine, running on E85, in parallel with a Unique Mobility brushless DC motor. In the Explorer the engine and motor will have peak power outputs of 110 kW and 60 kW. The motor will draw electricity from a nominal 200V lithium ion battery pack that is in parallel with ultracapacitor banks. Further modifications integrate this drive train into the vehicle and use control logic to provide a seamless, customer friendly package.

Biodiesels are promising alternatives to diesel fuel since they are biodegradable, non-toxic and reduce air pollution. This study presents analytical comparisons of atomization characteristics of 3 types of biodiesels and 6 blends with Diesel No. 2. Results showed that the smallest and largest drop sizes were associated with coconut and peanut biodiesel blends, respectively. Using unblended biodiesels increases drop size by 40%, which indicates either custom nozzles should be used in such applications or blending is required to reduce surface tension and viscosity to enhance atomization. Knowledge of atomization of pure biodiesel and its blends as alternative fuels in diesel engines can lead to better design of diesel engine injectors to meet regulatory emission guidelines and engine performance.

Gasoline particulate filters (GPFs) are an important aftertreatment system that enables gasoline direct injection (GDI) engines to meet current emission standardsn note of GPFs may need to improonont accumulates on the GPF during engine operation. GPFs are often ‘pa during vehicle operation when the exhaust is sufficiently hot and it contains sufficient oxygen. This paper explores the effect that engine-out soot emissions and the frequency of GPF regeneration have on GPF filtration efficiency. Two GPF technologies were tested on two engine dynamometers as well as two production vehicles on a chassis dynamometer. The engines span a wide range of engine-out particle emissions (a range of almost one order of magnitude). The filtration efficiency of the GPFs were measured with a regulation-compliant particle number system (non-volatile particles > 23 nm), as well as with a particle counter with a lower cutoff of 2.5 nm, and with a differential mobility spectrometer.

Homogeneous Charge Compression Ignition (HCCI) engines offer high fuel efficiency and some emissions benefits. However, it is difficult to control and stabilize combustion over a sufficient operating range because the critical compression ratio and intake temperature at which HCCI combustion can be achieved varies with operating conditions such as speed and load as well as with fuel octane number. Replacing part of the base fuel with reformer gas, (which can be produced from the base hydrocarbon fuel), alters HCCI combustion characteristics in varying ways depending on the replacement fraction and the base fuel auto-ignition characteristics. Injecting a blend of reformer gas and base fuel offers a potential HCCI combustion control mechanism because fuel injection quantities and ratios can be altered on a cycle-by-cycle basis.

Homogeneous Charge Compression Ignition (HCCI) combustion offers high fuel efficiency and some emissions benefits. However, it is difficult to control and stabilize combustion over a significant operating range because the critical compression ratio and intake temperature at which HCCI combustion can be achieved vary with operating conditions such as speed and load as well as with fuel octane number. Replacing part of the base fuel with reformer gas, (which can be produced from the base hydrocarbon fuel), alters HCCI combustion characteristics in varying ways depending on the replacement fraction and the base fuel auto-ignition characteristics. Because fuel injection quantities and ratios can be altered on a cycle-by-cycle basis during operation, injecting a variable blend of reformer gas and base fuel offers a potential HCCI combustion control mechanism.

Despite progressive implementation of stringent emission regulations, vehicle tailpipe emissions remain the major source of air pollution problems in most urban areas. To control and reduce tailpipe pollutants, it is critical to understand in-use emissions as a basis for any future emission controls. At present, emission factors are mainly studied by chassis dynamometer methods. However, concerns have been raised about the extent to which emissions produced by on-road vehicles can be predicted using emission factors developed based on standardized dynamometer test procedures. This paper describes an on-board, in-use vehicle emissions measurement system which measures tailpipe emission rates while the vehicle is in real service experiencing complex traffic conditions, driver behavior and weather.

Energy supply and environmental concerns have led to interest in alternative transportation fuels and power-trains. Already, there are significant changes in mainstream gasoline and Diesel formulation to accommodate tighter emissions standards. Some alternative fuels are being promoted as “cleaner” replacements for gasoline and Diesel fuel. There are many research papers which present data on these different alternative fuels, yet it is difficult to compare the fuels with any confidence. The majority of published studies do not use consistent methodology and make many assumptions (which may or may not be reported). Based on an extensive literature review, this study presents emissions results drawn from a smaller number of papers which provide alternative fuel and conventional emissions data in a comparable manner. Both light-duty and heavy-duty vehicles are considered.

Motorized transport has become an essential part of our world economic system with an ever-increasing number of vehicles on the road. However, considering the depletion of energy resources and the aggravation of greenhouse gas issues, it is critical to improve vehicle fuel consumption. These demands are moving us toward advanced engine and powertrain technologies. However, understanding our progress also requires improvements in the way we measure and certify vehicle emissions and fuel economy performance. This paper describes the use of an on-board fuel consumption and emissions measurement system to develop on-road fuel consumption functions that can be used to quantify the fuel economy impact of vehicle, road and traffic control changes. The system uses an ECM OBD-II scanner, a Mass Air Flow meter and an emissions analyzer to monitor fuel consumption and exhaust CO2 emission rates (in g/s) as well as vehicle speed and other parameters.

This paper presents an investigation of a reverse flow catalytic converter attached to a diesel/natural gas dual fuel engine. Experimental data were obtained in a ceramic monolith catalytic converter with a palladium based catalyst. A variety of flow reversal cycle times were explored experimentally when the engine load was changed from a high load to a low load. A single channel numerical model was developed for the data set and the effect of reverse flow cycle time was studied using both physical and numerical model systems. The duration of the cycle time is shown to be an important parameter in the operation of the converter. Shorter cycle times produced the least fluctuation in reactor temperature and gave the highest time-averaged conversion. Intermediate cycle times gave the most rapid increase in the maximum reactor temperature.

Natural gas is a challenging fuel for HCCI engines because its single-stage ignition and rapid combustion make it difficult to optimize combustion timing over a significant load range. This study investigates direct injection of a pilot quantity of high-cetane fuel near TDC as a range extension and combustion control mechanism for natural gas HCCI engines. The EGR and load range is studied in a supercharged natural gas HCCI engine equipped with external EGR, intake heating and a direct injection system for n-heptane pilot fuel. The operating range and emissions are of primary interest and are compared between both the baseline HCCI engine with variable intake temperature and the direct injected HCCI (DI-HCCI) engine with constant intake temperature. Test results show the EGR and load range at fixed intake temperature can be extended using pilot direct injection.

The combination of on-board diagnostics and evaporative emission control (EVAP) systems has led to a growing need to identify and repair leaks in automotive EVAP systems. The normal leakfinding method involves purging the system with a smoke fluid, usually air or nitrogen containing an oil aerosol and then looking for a visual indication of the leak. The purge flow used to distribute smoke through the system displaces substantial amounts of fuel vapor from the tank vapor space and can also raise the oxygen level inside the fuel system. If any ignition source is present, the formation of flammable mixtures both inside and outside the vehicle systems can lead to a flash fire hazard associated with leak finding procedures. Currently available fire statistics (such as NFPA) are not sufficiently detailed to attribute service shop fires to specific testing procedures.

The development and calibration of modern combustion engines is challenging in the area of continuously tightening emission limits and the necessity for meeting real driving emissions regulations. A focus is on the knowledge of the internal engine processes and the determination of pollutants formations in order to predict the engine emissions. A physical model-based development provides an insight into hardly measurable phenomena properties and is robust against changing input data. With increasing modeling depth the required computing capacities increase. As an alternative to physical modeling, data-driven machine learning methods can be used to enable high-performance modeling accuracy. However, these are dependent on the learned data. To combine the performance and robustness of both types of modeling a hybrid application of data-driven and physical models is developed in this paper as a grey box model for the exhaust emission prediction of a commercial vehicle diesel engine.

Fuel choices are being made today by consumers, industry and government. One such choice is whether to use reformulated gasoline to replace regular unleaded gasoline. A second choice involves the source of crude oil, with synthetic crude oil from tar sands currently expanding its share of the Canadian supply. Decision makers usually work with the direct economic consequences of their fuel choice. However, they generally lack the knowledge to measure environmental aspects of different fuel systems. This paper uses Life Cycle Value Assessment (LCVA) to demonstrate how the life cycle environmental aspects can be compared for alternative fuel choices. LCVA is an engineering decision making tool which provides a framework for the decision maker to consider the key economic and environmental impacts for the entire life cycle of alternative products or process systems.

Transportation, with its high energy consumption, is commonly recognized as a major contributor to local, regional, and global environmental impacts. With around 95% of transportation energy originating from petroleum and an increasing emphasis on the associated environmental impacts, alternative transportation fuels are receiving great attention from industry, government, researchers, and the public. When the motivation for developing alternative fuels is to reduce environmental impact, a rigorous tool is needed for comparing the effects of very different alternative and conventional fuels. Such an evaluation tool must consider not only the effects of fuel combustion, but also the effects of producing, refining/processing, distributing, and disposing of wastes associated with that fuel… in other words, the life cycle effects of the fuel.

High speed schlieren video and pressure trace analyses were used to study the effects of turbulence on burning velocity in a fixed volume combustion chamber. Lean methane-air mixtures of equivalence ratios of 0.76 and 0.96 were ignited at 1 atm and 23°C. Schlieren images of flame growth were recorded on video at 2000 frames per second while combustion chamber pressure was simultaneously recorded. The turbulence intensity at ignition was set at 0 m/s to 4 m/s intensity with integral scale around 7.6 mm by pulling a perforated plate across the chamber prior to ignition. In the analysis, the turbulence parameters were adjusted for the effect of decay and rapid distortion in a closed vessel during combustion. Results of both video and pressure trace analyses show a linear relationship between turbulent burning velocity and turbulence intensity as expected. Moderate changes in equivalence ratio had a negligible effect on this relationship.

A diesel piloted natural gas engine's performance varies depending on operating conditions and has performed best under medium to high loads. It can often equal or better the fuel conversion efficiency of a diesel-only engine in this operating range. This paper presents a study performed on a multi-cylinder Cummins ISB 6.7L diesel engine converted to run stoichiometric natural gas/diesel micro-pilot combustion with a maximum diesel contribution of 10%. This study systematically quantifies and ranks the sensitivity of control factors on combustion and performance while operating at medium loads. The effects of combustion control parameters, including the pilot start of injection, pilot injection pressure, pilot injection quantity, exhaust gas recirculation, and global equivalence ratio, were tested using a design of experiments orthogonal matrix approach.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.