Refuse trucks, commonly referred to as garbage trucks are a critical component of a municipality’s waste management industry. Their primary purpose is to collect, transport and deposit waste from households or businesses to designated transfer sites or dumps. Historically, refuse trucks have been powered by diesel fuel. The consumption of diesel fuel paired with the frequent accelerations or decelerations between each residential household along a route attribute to high amounts of tailpipe emissions and noise pollution within neighbourhoods. There is significant opportunity to explore avenues of powertrain electrification in refuse trucks to reduce their emissions and improve energy efficiency.
To rapidly test promising powertrains, vehicle software models were developed. To accurately model the energy usage and power requirements of refuse trucks, environments for the models to operate were created. The environments were created using on-board diagnostic and positional data collected from refuse trucks in the City of Hamilton in Ontario, Canada. The data collection was done under a research collaboration between the City of Hamilton and the McMaster Automotive Resource Centre. The approaches used to develop the drive and duty cycles for the vehicle models offer some innovative approaches without the need for invasive devices to be installed.
The powertrains that were modelled includes an all-electric, ranged extended electric and conventional refuse trucks. A comparative analysis of the pump-to-wheel powertrain efficiencies were completed looking at metrics such as fuel economy, payload capacity and fuel costs. Lastly, a look at truck emissions from a well-to-wheel perspective were completed to investigate the impact of each powertrain on greenhouse gasses and the effect on air quality of their immediate surroundings. / Thesis / Master of Applied Science (MASc)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/27897 |
Date | 11 1900 |
Creators | Toller, Jack |
Contributors | Emadi, Ali, Mechanical Engineering |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
Type | Thesis |
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