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Well-to-Wheel Analyses for Energy Consumption and Greenhouse Gas Emissions of Electric Vehicles Using Various Thermal Power Generation Technologies in China

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Proceedings of the FISITA 2012 World Automotive Congress

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 191))

Abstract

Since majority of electricity in China is generated from coal and natural gas, the study carried out WTW analyses for battery electric vehicles (BEVs) using China’s various thermal power generation technologies and compare their total energy use and GHG emissions against gasoline or diesel internal combustion engine vehicles (ICEVs), as well as hybrid electric vehicles (HEVs). The WTW analyses of BEVs, HEVs and ICEVs were conducted using the GREET (Greenhouse gases, regulated emissions, and energy use in Transportation) model developed by Argonne National Lab combined with a localized database of Chinese domestic data. A 2011 mid-size gasoline car is used as a baseline. Two types of BEV assumed in this study: Common BEVs and High-efficient BEVs. Common BEV pathways will save up to 99 % petrol consumption. However, comparing to that of HEV pathway, WTW energy consumption of all Common BEV pathways will be increased, with a maximum of 71 %. WTW energy consumption of High-efficient BEVs will be 2–29 % less than the WTW energy in the HEV pathway. GHG emissions of Common BEVs depend on differences in power generation technologies. Without CCS, the WTW GHG emissions of Common BEVs using coal-fired electricity are 11–77 % higher than the WTW GHG emissions of the baseline. When USC and IGCC generation technologies are equipped with CCS, the WTW GHG emissions of High-efficient BEVs are 79–83 % less than that of the baseline, and 69–75 % less than the hybrid pathway. This is the first time that a WTW analysis in China at this magnitude was completed with a fully localized fuel-cycle database. Outcomes of the study provide more relevance and accuracy for both the government and industry to develop strategies and policies in China. The model and database developed in this study can be used for analysis both at national and regional levels. This study did not include the energy use and GHG emissions in vehicle manufacturing stage. Although it is a small portion in the analysis, it could provide understanding of the difference in vehicle manufacturing process between EVs and traditional gasoline vehicles. This paper shows that the Common BEVs currently demonstrated are not a silver bullet for attacking energy consumption challenges and GHG emissions. In China context, full HEVs seem more attractive than Common BEVs to deal with energy security and GHG reduction challenge today. In order to achieve GHG reduction targets through vehicle electrification, China must promote CCS technology to help USC and IGCC power plants deliver low-carbon transportation energy on supply side. At the same time, High-efficient BEVs have to be set as the highest priority of automotive technology development.

F2012-B01-022

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Notes

  1. 1.

    More recently, by incorporating gas-aerosol interactions, some researchers have indicated that the methane GWP ought to be revised upward to about 33 [11]. This revision is not considered here.

  2. 2.

    In order to use coal gangue and low quality lignite, China also built a number of power plants with circulating fluidized bed technology, currently about seventeen 300 MW units and one 600 MW unit, 1 % in total thermal power capacity. In addition, ther is a 250 MW IGCC demonstration unit located in Tianjin.

  3. 3.

    According to definition from U.S. EPA, mid-size car is pointed to the car with a total passenger & cargo volume from 110 to 119 cubic feet.

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Shen, W., Han, W. (2013). Well-to-Wheel Analyses for Energy Consumption and Greenhouse Gas Emissions of Electric Vehicles Using Various Thermal Power Generation Technologies in China. In: Proceedings of the FISITA 2012 World Automotive Congress. Lecture Notes in Electrical Engineering, vol 191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33777-2_8

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  • DOI: https://doi.org/10.1007/978-3-642-33777-2_8

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