Analysis of Plug-In hybrid Electric Vehicles' utility factors using GPS-based longitudinal travel data.

详细信息   

• 作者：Aviquzzaman ; Md.
• 学历：Master
• 年：2014
• 毕业院校：Lamar University - Beaumont
• Department：Civil Engineering.
• ISBN：9781321485516
• CBH：1572911
• Country：USA
• 语种：English
• FileSize：577683
• Pages：71

文摘

The benefit of using a Plug-in Hybrid Electric Vehicle (PHEV) comes from its ability of substituting gasoline with electricity in operation. Defined as the share of distance traveled in the electric mode,the utility factor (UF) depends mostly on the battery capacity but also on many other factors,such as travel pattern and recharging pattern. Conventionally,the UFs are calculated from the daily vehicle miles traveled (DVMT) of vehicles by assuming motorists leaving home in the morning with full battery and return home in the evening. Such assumption,however,ignores the impact of the heterogeneity in both travel and charging behavior. The main objective of the thesis is to compare the UF by using multiday GPS-based travel data in regards to the charging decision. This thesis employs the global positioning system (GPS) based longitudinal travel data (covering 3-18 months) collected from 403 vehicles in the Seattle metropolitan area to investigate the impacts of such travel and charging behavior on UFs by analyzing the DVMT and home and work related tours. The UFs based on the DVMT are found close to those based on home-to-home tours. On the other hand,it is seen that the workplace charge opportunities largely improve UFs if the battery capacity is no more than 50 miles. It is also found that the gasoline price does not have significant impact on the UFs.