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Heavy-duty diesel trucking is responsible for 25%-30% of the road transportation CO2 emissions in North America. Retrofitting class-8 trucks with a complementary hydrogen fuelling system makes it possible to co-combust hydrogen and diesel in the existing internal combustion engine (ICE), thus minimizing the costs associated with switching to non-ICE platforms and reducing the barrier for the implementation of low-carbon gaseous fuels such as hydrogen. This retrofitting approach is evaluated based on the exhaust emissions of a converted truck with several thousand kilometres of road data. The heavy-duty truck used here was retrofitted with an air-intake hydrogen injection system, onboard hydrogen storage tanks, and a proprietary hydrogen controller enabling it to operate in hydrogen-diesel co-combustion (HDC) mode.

This paper examines the combustion and emissions produced using a prototype fuel injector nozzle for pilot-ignited direct-injection natural gas engines. In the new geometry, 7 individual equally-spaced gas injection holes were replaced by 7 pairs of closely-aligned holes (“paired-hole nozzle”). The paired-hole nozzle was intended to reduce particulate formation by increasing air entrainment due to jet interaction. Tests were performed on a single-cylinder research engine at different speeds and loads, and over a range of fuel injection and air handling conditions. Emissions were compared to those resulting from a reference injector with equally spaced holes (“single-hole nozzle”). Contrary to expectations, the CO and PM emissions were 3 to 10 times higher when using the paired-hole nozzles. Despite the large differences in emissions, the relative change in emissions in response to parametric changes was remarkably similar for single-hole and paired-hole nozzles.

In direct-injection engines, combustion and emission formation is strongly affected by injection quality. Injection quality is related to mass-flow rate shape, momentum rate shape, stability of pulses as well as mechanical and hydraulic delays associated with fuel injection. Finding these injector characteristics aids the interpretation of engine experiments and design of new injection strategies. The goal of this study is to investigate the rate of momentum for the single and post injections for high-pressure direct-injection natural gas injectors. The momentum measurement method has been used before to study momentum rate of injection for single and split injections for diesel sprays. In this paper, a method of momentum measurement for gas injections is developed in order to present transient momentum rate shape during injection timing. In this method, a gas jet impinges perpendicularly on a pressure transducer surface.

The emissions and efficiency of modern internal combustion engines need to be improved to reduce their environmental impact. Many strategies to address this (e.g., alternative fuels, exhaust gas aftertreatment, novel injection systems, etc.) require engine calibrations to be modified, involving extensive experimental data collection. A new approach to modeling and data collection is proposed to expedite the development of these new technologies and to reduce their upfront cost. This work evaluates a Gaussian Process Regression, Artificial Neural Network and Bayesian Optimization based strategy for the efficient development of machine learning models, intended for engine optimization and calibration. The objective of this method is to minimize the size of the required experimental data set and reduce the associated data collection cost for engine modeling.