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Surrogate-Assisted Compressor Geometry Optimization for Fuel Economy and Emissions Trade-Off in a Turbocharged Diesel Engine.

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Title: Surrogate-Assisted Compressor Geometry Optimization for Fuel Economy and Emissions Trade-Off in a Turbocharged Diesel Engine.
Authors: Wang, Penghui1 (AUTHOR), Tian, Jing1,2 (AUTHOR) jingtian@jlu.edu.cn, Yin, Yuting1,2 (AUTHOR), Wang, Hui2 (AUTHOR)
Source: Energies (19961073). Jul2026, Vol. 19 Issue 14, p3306. 29p.
Subject Terms: *Surrogate-based optimization, *Multi-objective optimization, *Compressor performance, *Metaheuristic algorithms, *Fuel industry, *Diesel motors
Abstract: Turbocharger compressor geometry affects the pressure ratio, flow range, and efficiency distribution of the compressor map, but the influence pathway from compressor geometry to engine fuel economy and emissions trade-off has not been sufficiently quantified. This study develops a surrogate-assisted multi-objective optimization framework that couples compressor and engine models. A calibrated one-dimensional compressor model generated a geometry-specific map for each design, which was imported into a validated one-dimensional engine model to calculate brake-specific fuel consumption and brake-specific NOx emissions at four loads. The results for the four loads were aggregated into weighted brake-specific fuel consumption (BSFCw) and weighted brake-specific NOx emissions (BSNOxw). Extreme gradient boosting (XGBoost) surrogate models are trained to predict these weighted responses. The non-dominated sorting genetic algorithm II (NSGA-II) identified Pareto-optimal compressor geometries. Representative solutions were re-evaluated using the original coupled models. The Pareto front reveals a clear trade-off between BSFCw and BSNOxw, with the minimum-BSFCw and minimum-BSNOxw solutions defining the respective lower bounds within the investigated design space. For the selected trade-off solution, BSNOxw was 1.18 g/(kW·h) lower than the baseline value, while BSFCw was 0.82 g/(kW·h) higher. Compressor geometry alters the distribution of engine operating points on the compressor map under different loads, thereby affecting the trade-off between fuel economy and NOx emissions. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 195801910
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Label: Title
  Group: Ti
  Data: Surrogate-Assisted Compressor Geometry Optimization for Fuel Economy and Emissions Trade-Off in a Turbocharged Diesel Engine.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Penghui%22">Wang, Penghui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tian%2C+Jing%22">Tian, Jing</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> jingtian@jlu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yin%2C+Yuting%22">Yin, Yuting</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Hui%22">Wang, Hui</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Label: Source
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jul2026, Vol. 19 Issue 14, p3306. 29p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Surrogate-based+optimization%22">Surrogate-based optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Compressor+performance%22">Compressor performance</searchLink><br />*<searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Fuel+industry%22">Fuel industry</searchLink><br />*<searchLink fieldCode="DE" term="%22Diesel+motors%22">Diesel motors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Turbocharger compressor geometry affects the pressure ratio, flow range, and efficiency distribution of the compressor map, but the influence pathway from compressor geometry to engine fuel economy and emissions trade-off has not been sufficiently quantified. This study develops a surrogate-assisted multi-objective optimization framework that couples compressor and engine models. A calibrated one-dimensional compressor model generated a geometry-specific map for each design, which was imported into a validated one-dimensional engine model to calculate brake-specific fuel consumption and brake-specific NOx emissions at four loads. The results for the four loads were aggregated into weighted brake-specific fuel consumption (BSFCw) and weighted brake-specific NOx emissions (BSNOxw). Extreme gradient boosting (XGBoost) surrogate models are trained to predict these weighted responses. The non-dominated sorting genetic algorithm II (NSGA-II) identified Pareto-optimal compressor geometries. Representative solutions were re-evaluated using the original coupled models. The Pareto front reveals a clear trade-off between BSFCw and BSNOxw, with the minimum-BSFCw and minimum-BSNOxw solutions defining the respective lower bounds within the investigated design space. For the selected trade-off solution, BSNOxw was 1.18 g/(kW·h) lower than the baseline value, while BSFCw was 0.82 g/(kW·h) higher. Compressor geometry alters the distribution of engine operating points on the compressor map under different loads, thereby affecting the trade-off between fuel economy and NOx emissions. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=195801910
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/en19143306
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 29
        StartPage: 3306
    Subjects:
      – SubjectFull: Surrogate-based optimization
        Type: general
      – SubjectFull: Multi-objective optimization
        Type: general
      – SubjectFull: Compressor performance
        Type: general
      – SubjectFull: Metaheuristic algorithms
        Type: general
      – SubjectFull: Fuel industry
        Type: general
      – SubjectFull: Diesel motors
        Type: general
    Titles:
      – TitleFull: Surrogate-Assisted Compressor Geometry Optimization for Fuel Economy and Emissions Trade-Off in a Turbocharged Diesel Engine.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Wang, Penghui
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          Name:
            NameFull: Tian, Jing
      – PersonEntity:
          Name:
            NameFull: Yin, Yuting
      – PersonEntity:
          Name:
            NameFull: Wang, Hui
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 19961073
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              Value: 19
            – Type: issue
              Value: 14
          Titles:
            – TitleFull: Energies (19961073)
              Type: main
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