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DC Field | Value | Language |
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dc.contributor.author | Chi, Haoran | en_US |
dc.date.accessioned | 2013-08-26T08:03:00Z | |
dc.date.accessioned | 2017-09-19T09:13:51Z | |
dc.date.accessioned | 2019-02-12T07:31:52Z | - |
dc.date.available | 2013-08-26T08:03:00Z | |
dc.date.available | 2017-09-19T09:13:51Z | |
dc.date.available | 2019-02-12T07:31:52Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.other | 2013eech454 | en_US |
dc.identifier.uri | http://144.214.8.231/handle/2031/7038 | - |
dc.description.abstract | Nowadays fuel becomes less and less, which urges human being to find other power to supply the modern life. As a result, electricity, which relies on its relatively lower pollution, strong power and advanced technology to store it, becomes one of the most common alternative powers, and electricity-fuel hybrid vehicles get into our life. Up to now, this kind of vehicles has power controllers in which under certain conditions the ratio of using electricity and fuel are set previously. However, my FYP focus on the state of charging of fuel and battery at one period to determine the ratio of using these two powers, and the main aim is to use electricity more while keeping a good condition. Fuzzy logic and GA are chosen in this case. Furthermore, combined with scrip methodologies, as well as combining those two, it can provide a better performance. | en_US |
dc.rights | This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner. | en_US |
dc.rights | Access is restricted to CityU users. | en_US |
dc.title | Energy Management of Hybrid Vehicles Using Artificial Intelligence | en_US |
dc.contributor.department | Department of Electronic Engineering | en_US |
dc.description.supervisor | Supervisor: Dr. Tsang, K F; Assessor: Prof. Chan, W S | en_US |
Appears in Collections: | Electrical Engineering - Undergraduate Final Year Projects |
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fulltext.html | 145 B | HTML | View/Open |
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