Vehicle certification data are used to study the effectiveness of the major powertrain technologies used by car manufacturers to reduce fuel consumption. Methods for differentiating vehicles effectively were developed by leveraging theoretical models of engine and vehicle fuel consumption. One approach normalizes by displacement per unit distance, which puts both fuel used and vehicle work in mean effective pressure units, and is useful when comparing engine technologies. The other normalizes by engine rated power, a customer-relevant output metric. The normalized work/power is proportional to weight/power, the most fundamental performance metric. Certification data for 2016 and 2017 U.S. vehicles with different powertrain technologies are compared to baseline vehicles with port fuel injection (PFI) naturally aspirated engines and six-speed automatic transmissions. The most efficient baseline vehicles are low performance and achieve Environmental Protection Agency (EPA) efficiencies of 30 % Highway, 20 % City, and 23 % Combined cycles. The data show that efficiency drops linearly as the weight/power ratio decreases. The data shows turbocharging, cylinder deactivation, Atkinson cycle, and eight-speed transmissions providing larger benefits in higher power/weight vehicles, so that a common best efficiency of 24 % EPA Combined is achieved across a wide range of vehicle sizes and power/weight levels. The improvements on intrinsically efficient low power/weight vehicles are limited. Continuously variable transmissions are found to provide substantial benefits across the vehicle performance range, mainly on the EPA City cycle. The data also show that most technologies have distinct preferred ranges of application.
Characterization of Powertrain Technology Benefits Using Normalized Engine and Vehicle Fuel Consumption Data
Sae Int. J. Fuels Lubr
Sae International Journal of Fuels and Lubricants
WCX World Congress Experience ; 2018
Sae International Journal of Fuels and Lubricants ; 11 , 4 ; 517-531
2018-04-03
15 pages
Conference paper
English
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