Modelling of Electrically-Assisted Turbocharger Compressor Performance

Mamdouh Alshammari, Nikolaos Xypolitas and Apostolos Pesyridis
Additional contact information
Mamdouh Alshammari: College of Engineering and Design, Brunel University London, Uxbridge UB8, UK
Nikolaos Xypolitas: College of Engineering and Design, Brunel University London, Uxbridge UB8, UK
Apostolos Pesyridis: College of Engineering and Design, Brunel University London, Uxbridge UB8, UK

Energies, 2019, vol. 12, issue 6, 1-25

Abstract: For the purposes of design of a turbocharger centrifugal compressor, a one-dimensional modelling method has been developed and applied specifically to electrically-assisted turbochargers (EAT). For this purpose, a mix of authoritative loss models was applied to determine the compressor losses. Furthermore, an engine equipped with an electrically-assisted turbocharger was modelled using commercial engine simulation software (GT-Power) to assess the performance of the engine equipped with the designed compressor. A commercial 1.5 L gasoline, in-line, 3-cylinder engine was selected for modeling. In addition, the simulations have been performed for an engine speed range between 1000 and 5000 rpm. The design target was an electric turbocharger compressor that could meet the boosting requirements of the engine with noticeable improvement in a transient response. The results from the simulations indicated that the EAT improved the overall performance of the engine when compared to the equivalent conventional turbocharged engine model. Moreover, the electrically-assisted turbochargers (EAT) equipped engine with power outputs of 1 kW and 5 kW EAT was increased by an average of 5.96% and 15.4%, respectively. This ranged from 1000 rpm to 3000 rpm engine speed. For the EAT model of 1 kW and 5 kW, the overall net reduction of the BSFC was 0.53% and 1.45%, respectively, from the initial baseline engine model.

Keywords: centrifugal compressor; electrically-assisted turbocharger; 1D modelling; compressor design; transient response (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/6/975/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/6/975/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:6:p:975-:d:213540

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().