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A series plug-in hybrid electric powertrain with all-wheel drive is designed using real-world drive cycles as part of the EcoCAR 2 competition. A stock 2013 Chevrolet Malibu Eco is being re-engineered to reduce fuel consumption and emissions while improving consumer acceptability. Waterloo utilizes a 18.9 kWh A123 energy storage system (ESS), which powers two 105 kW TM4 traction motors. A 2.4 L LE9 General Motors coupled to a 105 kW TM4 motor provides range extending performance. Each step of the design process is discussed, including a novel approach to powertrain selection and controls requirement selection that uses real-world drive cycles. The mechanical integration and unique ESS design is also discussed.

Due to the high power and energy density and also relative safety, lithium ion batteries are receiving increasing acceptability in industrial applications especially in transportation systems with electric traction such as electric vehicles and hybrid electric vehicles. In this regard, to ensure performance reliability, accurate modeling of calendar life of such batteries is a necessity. In fact, potential failure of Li-ion battery packs remains a barrier to commercialization. Battery pack life is a critical feature to warranty and maintenance planning for hybrid vehicles, and will require adaptive control systems to account for the loss in vehicle range, and loss in battery charge and discharge efficiency. Failure not only results in large replacement costs, but also potential safety concerns such as overheating or short circuiting which may lead to fires.

This paper describes the design strategy followed to modify a 1998 Polaris Indy Trail [1] as a part of the University of Waterloo's Team Eco-Snow's participation in the Clean Snowmobile Challenge 2000. The team's objectives are to engineer a clean, quiet snowmobile that provides recreational users with a more environmentally friendly vehicle while maintaining a snowmobile that performs on par with current production snowmobiles. The design strategy followed includes the selection of a liquid-cooled engine and subsequent modifications completed to improve the combustion process, the implementation of catalytic converters in the exhaust, and the incorporation of an improved silencer. Less innovative but somewhat overlooked strategies, such as proper carburetor tuning, are also discussed. The completed modifications are reliable and fairly inexpensive, considering the benefits provided.

The autoignition delay of a turbulent methane jet in a Diesel-like environment is calculated by the conditional moment closure(CMC) model. Methane is injected into hot air in a constant volume chamber under various temperatures and pressures. Detailed chemical reaction mechanisms are implemented with turbulence-chemistry interaction treated by the first order CMC. The CMC model solves the conditional mean species mass fraction and temperature equations with the source term given in terms of the conditional mean quantities. The flow and mixing field are calculated by the transient SIMPLE algorithm with the k -ε model and the assumed beta function pdf. The CMC equations are solved by the fractional step method which sequentially treats the transport and chemical reaction terms in each time step. The predictions in quiescent homogeneous mixture are presented to evaluate the effects of turbulence in jet ignition.

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.

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.

The conversion design strategy, and emissions and performance results for a dedicated propane, vapour injected, 1995 Dodge Dakota truck are reported. Data is obtained from the University of Waterloo entry in the 1997 Propane Vehicle Challenge. A key feature of the design strategy is its focus on testing and emissions while preserving low engine speed power for drivability. Major changes to the Dakota truck included the following: installation of a custom shaped fuel tank, inclusion of a fuel temperature control module, addition of a vaporizer and a fuel delivery metering unit, installation of a custom vapour distribution manifold, addition of an equivalence ratio electronic controller, inclusion of a wide range oxygen sensor, addition of an exhaust gas recirculation cooler and installation of thermal insulation on the exhaust system. A competition provided natural gas catalyst was used.

Direct injected natural gas diesel engines are currently being developed. Numerical analyses results are presented for 20.0 MPa (≈ 3000 psia; 200 atm), 444 K, natural gas injection into 4.0 MPa cylinder air where the ambient turbulence field is representative of diesel engines. Two very important non-intuitive, observations are made. First, the seemingly reasonable spatially uniform velocity profile currently used at the injector exit is not appropriate, rather a double-hump profile is correct. Second, a spatially uniform, injector exit, temperature profile results in local temperature overestimates as large as 300 K. Considering the strong role of temperature on chemical kinetics, this second observation may have profound implications on the validity of conclusions reached using uniform exit profiles.

This work presents the autoignition delay time characteristics of methane and natural gas under simulated diesel engine conditions. A constant-volume combustion vessel is used for the experiments. Results are presented for the pressure and temperature ranges of 5 to 55 atm and 600 to 1700 K, respectively. Comparisons are then made with autoignition data for methanol, ethanol, isooctane, and n-cetane. Three major trends are observed. First, there is little effect on the autoignition delay time of natural gas as the vessel pressure is increased from 5 to 55 atm. Second, there is a slight decrease in the autoignition delay time of methane-ethane gas mixtures as the concentration of ethane is increased. Third, the autoignition delay time of natural gas is strongly dependent on temperature and continually decreases with increasing temperature.