Reinforced Explorit on Optimizing Vehicle Powertrains View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Victor Parque , Masakazu Kobayashi , Masatake Higashi

ABSTRACT

How to build optimal vehicular powertrains? We study this question and propose an algorithm inspired by a domain-general design process. The basic idea is to interplay co-biasingly between the local approximations of discrete design and the global refinements of continuous parameters. The proposed method was evaluated to design powertrains of four types of vehicles: Series Hybrid Electric Vehicle(SHEV), Parallel Hybrid Electric Vehicle(PHEV), Fuel Cell(FC) and Electric Vehicle(EV). Simulation results show noticeable improvements on mileage per gas emissions over different study cases. To our knowledge, this is the first study aiming at designing vehicle powertrains considering the holistic point of view. More... »

PAGES

579-586

References to SciGraph publications

  • 2012-05. A survey of multidisciplinary design optimization methods in launch vehicle design in STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
  • 2008-02. PSO algorithm-based parameter optimization for HEV powertrain and its control strategy in INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY
  • Book

    TITLE

    Neural Information Processing

    ISBN

    978-3-642-42041-2
    978-3-642-42042-9

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-42042-9_72

    DOI

    http://dx.doi.org/10.1007/978-3-642-42042-9_72

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1026446104


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