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This paper presents a methodology that optimizes the periods of engine operation on a selected route for a Plug-in Hybrid Electric Vehicle (PHEV) or Hybrid Electric Vehicle (HEV) using Connected Vehicle data to minimize energy consumption. The study was conducted using a Reduced-Order Powertrain model of second-generation Chevrolet Volt. The method utilizes the Backward Induction Dynamic Programming algorithm to come up with an optimal control mode matrix of engine operation along the selected route for various battery states of charge. The objective of this method is to make use of Vehicle Connectivity to minimize the energy utilization of an HEV by using the speed and elevation profile of a selected route transmitted to the vehicle via V2X communication systems.

An over-expanded spark ignited engine was investigated in this work via engine simulation with a design constrained, mechanically actuated Atkinson cycle mechanism. A conventional 4-stroke spark-ignited turbo-charged engine with a compression ratio of 9.2 and peak brake mean effective pressure of 22 bar was selected for the baseline engine. With geometry and design constraints including bore, stroke, compression ratio, clearance volume at top dead center (TDC) firing, and packaging, one over-expanded engine mechanism with over expansion ratio (OER) of 1.5 was designed. Starting with a validated 1D engine simulation model which included calibration of the in-cylinder heat transfer model and SI turbulent combustion model, investigations of the Atkinson engine including cam optimization was studied. The engine simulation study included the effects of offset of piston TDC locations as well as different durations of the 4-strokes due to the mechanism design.

A three phase catalytic mathematical model was developed for analysis and optimization of the volatile reactor assembly (VRA) used on International Space Station (ISS) Water Processor. The Langmuir-Hinshelwood Hougen-Watson (L-H) expression was used to describe the surface reaction rate. Small column experiments were used to determine the L-H rate parameters. The test components used in the experiments were acetic acid, acetone, ethanol, 1-propanol, 2-propanol and propionic acid. These compounds are the most prevalent ones found in the influent to the VRA reactor. The VRA model was able to predict performance of small column data and experimental data from the VRA flight experiment.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.