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The drive to improve and optimize hybrid vehicle performance is increasing with the growth of the market. With this market growth, the automotive industry has recognized a need to train and educate the next generation of engineers in hybrid vehicle design. The University of Waterloo Alternative Fuels Team (UWAFT), as part of the EcoCAR 3 competition, has developed a control strategy for a novel parallel-split hybrid architecture. This architecture features an engine, transmission and two electric motors; one pre-transmission motor and one post-transmission motor. The control strategy operates these powertrain components in a series, parallel, and all electric power flow, switching between these strategies to optimize the energy efficiency of the vehicle. Control strategies for these three power flows are compared through optimization of efficiencies within the powertrain.

This paper describes the design strategy used by the University of Waterloo's Team Eco-Snow to modify a stock snowmobile in order to compete in the Clean Snowmobile Challenge for 2002. A two-stroke snowmobile is modified to operate more cleanly, quietly, and without sacrificing performance. Excessive noise emissions were Team Eco-Snow's major concern. Noise reductions between 9 and 16 dBA are achieved. Drivetrain and engine efficiency are improved through reduced track frictional drag losses, reduced peak operating engine speed, increased compression ratio, and port modifications that redirect tumble and enhance swirl. Emissions are primarily reduced through an air-assisted catalytic converter system coupled with leaner carburetor settings.

Supervisory control strategies for a hybrid fuel cell powertrain are developed and simulated using Simulink models and the Powertrain Systems Analysis Toolkit (PSAT). The control strategy selects the power splitting ratio between a 65kW Hydrogenics fuel cell power module and a 70kW Cobasys Nickel Metal Hydride (NiMH) battery pack. Simple control algorithms targeting a battery pack State of Charge (SOC), or maximizing the instantaneous powertrain efficiency are initially considered and analyzed. A comprehensive control strategy optimizing powertrain efficiency, vehicle performance, emissions, and long-term reliability is then developed and simulated. The simulated vehicle using the comprehensive control strategy with reliability considerations exhibits a 21% mileage improvement as compared to a simple rule-based control algorithm.

Mean value engine models (MVEMs) are intermediate-level internal combustion (IC) engine models which include more physical details than simplistic linear transfer function models, but significantly fewer details than large complex cylinder-by-cylinder models [1]. The MVEM is well-known as a suitable plant model for model-based control applications. The combinations of physics-based component models, which allow the physical parameter effects to be evaluated and controlled, and look-up table models, with fast response, make the MVEM suitable for control applications. A mean value engine model based on mathematical and parametric equations has recently been developed in the new MapleSim software. The model consists of three main components: the throttle body, the manifold, and the engine. The model is developed in the MapleSim environment which takes advantages from both Maple's powerful symbolic mathematical tool and Modelica's modern equation-based language.

In this paper, initial results of Li-ion battery performance characterization through field tests are presented. A fully electrified Ford Escape that is equipped by three Li-ion battery packs (LiFeMnPO4) including an overall 20 modules in series is employed. The vehicle is in daily operation and data of driving including the powertrain and drive cycles as well as the charging data are being transferred through CAN bus to a data logger installed in the vehicle. A model of the vehicle is developed in the Powertrain System Analysis Toolkit (PSAT) software based on the available technical specification of the vehicle components. In this model, a simple resistive element in series with a voltage source represents the battery. Battery open circuit voltage (OCV) and internal resistance in charge and discharge mode are estimated as a function of the state of charge (SOC) from the collected test data.

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.

This paper presents a math-based spark ignition (SI) engine model for fast simulation with enough fidelity to predict in-cylinder thermodynamic properties at each crank angle. The quasi-dimensional modelling approach is chosen to simulate four-stroke operation. The combustion model is formulated based on two-zone combustion theory with a turbulent flame propagation model [1]. Cylinder design parameters such as bore and stroke play an important role to achieve higher performance (e.g. power) and reduce undesirable in-cylinder phenomenon (e.g. knocking). A symbolic sensitivity analysis is used to study the effect of the design parameters on the SI engine performance. We used the symbolic Maple/MapleSim environment to obtain highly-optimized simulation code [3]. It also facilitates a sensitivity analysis that identifies the critical parameters for design and control purposes.

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.