Prediction model of mechanical loss in turbocharger

Satoshi Sakagami, Akane Uemichi, Yudai Yamasaki, Shigehiko Kaneko

Research output: Contribution to conferencePaper

Abstract

Recently, internal combustion (IC) engine systems for automobiles have been required to improve the whole efficiency in a real world. Above all, the turbocharged engine system is attracting attentions. Therefore, it is quite important to consider efficiencies of machine elements such as a turbocharger as well as those related to the combustion process. However, the methods for estimating thermal and mechanical losses of the turbocharger separately and precisely have not been established. In this research, to propose mathematical model capable of predicting mechanical loss induced in a turbocharger, we started with deriving governing equation of the friction loss by a journal bearing and a thrust bearing under operating condition and finally compared with reported data to validate the proposed method. In addition, sensitivity analysis based on the proposed model is performed to investigate the influence of individual physical factors such as rotational speed of the turbocharger, lubrication oil temperature, flow rate and the thrust force on the friction work.

Original languageEnglish
Publication statusPublished - 2017 Jan 1
Externally publishedYes
Event9th International Conference on Modeling and Diagnostics for Advanved Engine Systems, COMODIA 2017 - Okayama, Japan
Duration: 2017 Jul 252017 Jul 28

Other

Other9th International Conference on Modeling and Diagnostics for Advanved Engine Systems, COMODIA 2017
CountryJapan
CityOkayama
Period17/7/2517/7/28

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Keywords

  • Mechanical loss
  • Modeling
  • Oil temperature
  • Thrust force
  • Turbocharger

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering

Cite this

Sakagami, S., Uemichi, A., Yamasaki, Y., & Kaneko, S. (2017). Prediction model of mechanical loss in turbocharger. Paper presented at 9th International Conference on Modeling and Diagnostics for Advanved Engine Systems, COMODIA 2017, Okayama, Japan.