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Exhaust Energy Recovery with Variable Geometry Turbine to Reduce Fuel Consumption for Microcars
Technical Paper
2018-01-1825
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The objective proposed by EU to reduce by about 4%/year CO2 emission of internal combustion engines for the next years up to 2030, requires to increase the engine efficiency and accordingly improving the technology. In this framework, hybrid powertrains can have the possibility of a deep market penetration since they may recover energy during brake, allow the engine to operate in better efficiency conditions and with less transients, Moreover, they can recover a large amount of energy lost through the exhaust and use it to reduce fuel consumption.
This paper concerns the modification of a conventional two in-line cylinders Diesel engine (440 cm3) adding a variable geometry turbine (VGT) coupled with a generator. The turbine is used to recover exhaust gas energy that otherwise would be lost. The generator, connected to the turbo shaft, converts mechanical energy into electrical energy and is used to charge the vehicle battery or the auxiliaries. The aim of this work is reducing fuel consumption by replacing the alternator with a kind of electric turbo-compounding system to drive vehicle auxiliaries. If the selected turbine recovers enough energy to power auxiliaries, the alternator, which usually has low efficiency, can be removed. Along these lines, fuel consumption savings can be achieved.
At a later stage, a microcar has been tested on WLTC (Class 1) driving cycle.
The results show fuel consumption reduction of 6 to 9%, depending on VGT size. Indeed, four different VGT sizes have been analyzed to choose the optimal configuration that reflects a compromise between energy recovery and fuel consumption reductions.
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Citation
Ortenzi, F., Genovese, A., Carrazza, M., Rispoli, F. et al., "Exhaust Energy Recovery with Variable Geometry Turbine to Reduce Fuel Consumption for Microcars," SAE Technical Paper 2018-01-1825, 2018, https://doi.org/10.4271/2018-01-1825.Data Sets - Support Documents
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