Reducing the Number of Simulations in Operation Strategy Optimization for Hybrid Electric Vehicles

  • Christopher Bacher
  • Thorsten Krenek
  • Günther R. Raidl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8602)

Abstract

The fuel consumption of a simulation model of a real Hybrid Electric Vehicle is optimized on a standardized driving cycle using metaheuristics (PSO, ES, GA). Search space discretization and metamodels are considered for reducing the number of required, time-expensive simulations. Two hybrid metaheuristics for combining the discussed methods are presented. In experiments it is shown that the use of hybrid metaheuristics with discretization and metamodels can lower the number of required simulations without significant loss in solution quality.

Keywords

Hybrid Electric Vehicles Hybrid metaheuristics Search space discretization Metamodels 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Christopher Bacher
    • 1
  • Thorsten Krenek
    • 2
  • Günther R. Raidl
    • 1
  1. 1.Institute of Computer Graphics and AlgorithmsVienna University of TechnologyViennaAustria
  2. 2.Institute for Powertrains and Automotive TechnologyVienna University of TechnologyViennaAustria

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