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A potential route to reduce CO2 emissions from heavy-duty trucks is to combine low-carbon fuels and a hybrid-electric powertrain to maximize overall efficiency. A hybrid electric powertrain can reduce the peak power required from the internal combustion engine, leading to opportunities to reduce the engine size but still meet vehicle performance requirements. Although engine downsizing in the light-duty sector can offer significant fuel economy savings mainly due to increased part-load efficiency, its benefits and downsides in heavy-duty engines are less clear. As there has been limited published research in this area to date, there is a lack of a standardized engine downsizing procedure.

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.

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.

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.

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.

Because of domestic production from renewable sources and their clean burning nature, alcohols, especially ethanol, have seen growing use as a blending agent and replacement for basic hydrocarbons in gasoline. The increasing use of alcohol in fuels raises questions on the safety of these fuels under certain non-operational situations. Modern vehicles use evaporative emission control systems to minimize environmental emissions of fuel. These systems must be relatively leak-free to function properly and are self-diagnosed by the vehicle On-Board Diagnostic system. When service is required, the service leak testing procedures may involve forcing test gases into the “evap” system and also exposure of the fuel vapors normally contained in the system to atmosphere. Previous work has discussed the hazards involved when performing shop leak testing activities for vehicles fuelled with conventional hydrocarbon gasoline [1, 2].

Although HCCI engines promise low NOx emissions with high efficiency, they suffer from a narrow operating range between knock and misfire because they lack a direct means of controlling combustion timing. A series of previous studies showed that reformer gas, (RG, defined as a mixture of light gases dominated by hydrogen and carbon monoxide), can be used to control combustion timing without changing mixture dilution, (λ or EGR) which control engine load. The effect of RG blending on combustion timing was found to be mainly related to the difference in auto-ignition characteristics between the RG and base fuel. The practical effectiveness of RG depends on local production using a fuel processor that consumes the same base fuel as the engine and efficiently produces high-hydrogen RG as a blending additive.

Magnesium AZ80 is a medium strength alloy with good corrosion resistance and very good forging capability which offers an affordable commercial alternative to the Mg ZK60 alloy used for wheels in racing cars. Extending the market of Mg AZ80 alloy to automotive wheels requires a better understanding of macro- and micro-properties of this structural material, especially its forging behaviour. In this study the deformation behaviour of Mg AZ80 alloy is characterized by uniaxial compression tests from ambient to 420°C at a variety of strain rates using a Gleeble 1500 simulator. A constitutive relationship coupling materials work hardening and strain rate and temperature dependences is calibrated based on test results. This flow behaviour is input into a finite element model to simulate the forging operation of an automotive wheel with ABAQUS codes.

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.

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.

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.

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.

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.

This paper demonstrates vehicle emission factor measurement using an on-board, on-road system and examines the effects of ambient temperature on those emission factors. Vehicle operating parameters, fuel consumption and emissions were measured on-road using a portable measurement system designed for ease of use with a range of vehicles, drivers and driving situations. The results reported here come from repeated trips over a 17.4 km urban / suburban route with a particular driver and vehicle. As such, the emission factors developed here do not represent the current on-road fleet. However, they show the strong influence of actual operating conditions (particularly ambient temperature) and of the vehicle control system's response to non-standard conditions. This leads to an appreciation for on-road testing as a means to illustrate vehicle emission behavior in real conditions and to highlight conditions which may require more detailed study.

The University of Alberta Clean Snowmobile Challenge Team used a modified 2000 Bombardier Ski-Doo MXZ-X for the 2002 Clean Snowmobile Challenge (CSC). A Suzuki GSX-R 600 engine with a custom tuned port fuel injection system and custom exhaust system weree installed to maximize power while reducing emissions and noise from the snowmobile. This design was intended to meet the objectives of the CSC2002 competition which were a 50% reduction in hydrocarbon and carbon monoxide emissions and a reduction in noise to 74 dBA at 15 m (50 ft.) and wide open throttle (WOT). The reduction in emissions was easily achieved through the use of a four stroke engine with fuel injection and exhaust catalyst. The team was unable to meet the noise reduction goal although the entry was significantly quieter than the stock control snowmobile.

It is commonly stated that natural gas-fueled forklifts produce less emissions than propane-fueled forklifts. However, there is relatively little proof. This paper reports on a detailed comparative study at one plant in Edmonton, Canada where a fleet of forklift trucks is used for indoor material movement. (For convenience, the acronym NGV, ie. Natural Gas Vehicle is used to designate natural gas-fueled and LPG, ie. Liquified Petroleum Gas, is used to designate propane-fueled forklifts). Until recently the forklift trucks (of various ages) were LPG carburetted units with two-way catalytic converters. Prompted partially by worker health concerns, the forklifts were converted to fuel injected, closed-loop controlled NGV systems with three-way catalytic converters. The NGV-converted forklifts reduced emissions by 77% (NOX) and 76% (CO) when compared to just-tuned LPG forklifts.

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.

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.

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.

Life Cycle Value Assessment (LCVA) is a decision making tool which considers environmental, economic and/or social aspects for the entire life cycle of a product or process from “cradle-to-grave”. LCVA can be used for a wide range of public policy and business decisions with the analysis being performed at various levels of rigour. By its nature, LCVA utilizes data sets of varying qualities drawn from a wide range of sources. The uncertainties in the input data obviously lead to uncertainties in the results of the LCVA analysis. To establish confidence in an LCVA's recommendations, it is important to consider these uncertainties and incorporate an assessment of uncertainty into the LCVA process. However, the diverse nature of the data sets being used makes it difficult to rigorously establish data uncertainty levels. In addition, the complexity of most life cycle models makes it difficult to trace uncertainty through the analysis process.