Well-to-Wheel Analysis of Energy Efficiency & CO2 emissions for Hybrids & EVs in India: Current Trends & Forecasting for 2030

Author:

Nandola Yash1,Krishna Uttam1,Pramanik Santanu1,M Himabindu1,V Ravikrishna R1

Affiliation:

1. Indian Institute of Science, Bangalore

Abstract

Abstract A comprehensive Well-to-Wheel (WTW) analysis was performed to evaluate WTW energy use, efficiency & CO2 emissions for 12 vehicle/fuel configurations for a passenger sedan in the Indian context. The WTW analysis covered gasoline, diesel, and compressed natural gas (CNG) powered conventional vehicles, series hybrids, and plug-in series hybrids. In addition, hydrogen fuel cell-powered series hybrid and its plug-in version, along with a battery-electric vehicle, were also studied. The WTW analysis was repeated for a couple of electricity generation scenarios for the year 2030 to forecast future trends and finally for a couple of hydrogen production scenarios, where hydrogen was produced via electrolysis of water in addition to being produced from natural gas. The electricity pathway showed minimum Well-to-Tank (WTT) efficiency and maximum WTT CO2 emissions among the five fuels being considered for the study for all three electricity generation scenarios. The hybridization of vehicles showed improvement in the Tank-to-Wheel (TTW) efficiency and reduction in TTW CO2 emissions. Plug-in hybrid configuration of gasoline, diesel, CNG, and hydrogen showed higher TTW efficiency and lower TTW CO2 emissions than the conventional and series hybrid configurations. Battery electric configuration showed the maximum TTW efficiency of 68.2% and was associated with zero TTW CO2 emissions. For the current electricity generation scenario, diesel hybrid showed maximum WTW efficiency, and CNG series hybrid showed lowest WTW CO2 emissions. With the decrease in % share of coal, increased % share of renewables and reduction in transmission and distribution losses, it is expected that there would be an increase in the WTW efficiency and decrease in WTW CO2 emissions for plug-in hybrids and battery-electric vehicles. For the year 2030, assuming that 44% of electricity is generated from renewable sources, plug-in hybrids and battery electric vehicles showed substantial improvement in WTW efficiency, with diesel plug-in hybrid still showing maximum WTW efficiency, and CO2 emissions being the lowest for the CNG plug-in hybrid. For the hydrogen generation scenarios, WTW efficiency was the lowest, and WTW CO2 emissions were the highest for the fuel cell series hybrid electric vehicle when hydrogen was produced via electrolysis using electricity from the current grid mix. Hydrogen plug-in hybrid showed the highest WTW efficiency and zero WTW CO2 emissions when hydrogen was produced via electrolysis of water using electricity generated from 100% renewable sources.

Publisher

Research Square Platform LLC

Reference65 articles.

1. Argonne National Laboratory. Energy Systems - GREET Model n.d. https://greet.es.anl.gov/ (accessed September 15, 2020).

2. Life-cycle analysis of energy and greenhouse gas emissions of automotive fuels in India: Part 1 – Tank-to-Wheel analysis;Gupta S;Energy,2016

3. Life-cycle analysis of energy and greenhouse gas emissions of automotive fuels in India: Part 2 – Well-to-wheels analysis;Patil V;Energy,2016

4. General Motors Corporation, Argonne National Laboratory, BP, Exxon Mobil, Shell. Well to Wheel energy use and greenhouse gas emissions of advanced fuel/vehicle systems - North American Analysis. 2001.

5. Weiss M, Heywood J, Drake E, Schafer A, AuYeung F, Energy Laboratory. On the Road in 2020 A life-cycle analysis of New automobile technologies. Massachusetts Institute of Technology, Cambridge, Massachusetts: 2000.

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