<p>The world transportation sector has been relying on the oil industry for more than a hundred years, accounting for the largest oil consumption and one third of the greenhouse gas emissions. However, with the boosting demand, escalating national energy security concerns and emerging environmental issues, reducing and displacing petroleum fuel in transportation sector has become an urging global target. As a result, hybrid electric vehicles evolve as one solution to displace petroleum fuel by utilizing vehicle onboard electrical systems, achieving higher fuel economy and less emissions by vehicle electrification and hybridization.</p> <p>However, since hybrid electric vehicles add additional electrical components and systems to realize better fuel economy, the system complexity increases and thus the cost increases. Hence, it is an objective of this thesis research to focus on the integrations and optimizations, aiming to simplify and optimize the hybrid power-trains in both system level and component level.</p> <p>This thesis contributes to a novel integrated electro-mechanical hybrid transmission that is potentially more compact and more operational flexible with fewer components compared to the GM Allison Two-Mode hybrid transmission. Comprehensive commercialized power-train transmissions are reviewed and analyzed to serve as background information for comparison. It also contributes to a family of double-rotor switched reluctance machines that are more integrated and suitable for hybrid electric vehicle applications. A prototype double-rotor switched reluctance machine has been built and tested for concept proving. Detailed machine design process is reported with the emphasis on design novelties. Finite element analysis and optimization techniques are applied and the accuracy is confirmed by the experiments. In addition, methods of machine loss analysis, thermal analysis and drive analysis are established; manufacturing and testing procedures are documented in detail that can be used for future machine designs guidance.</p> / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/15340 |
| Date | 03 March 2015 |
| Creators | Yang, Yinye |
| Contributors | Emadi, Ali, Schofield, Nigel, Habibi, Saeid, Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | dissertation |
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