Global optimization techniques, such as dynamic programming, serve mainly to evaluate the potential fuel economy of a given powertrain configuration. Unless the future driving conditions can be predicted during real-time operation but the results obtained using this noncausal approach establish a benchmark for evaluating the optimality of realizable control strategies. Real-time controllers must be simple in order to be implementable with limited computation and memory resources. Moreover, manual tuning of control parameters should be avoided. This article has analyzed two approaches, namely, feedback controllers and ECMS. Both of these approaches can lead to system behavior that is close to optimal, with feedback controllers based on dynamic programming. Additional challenges stem from the need to apply optimal energy-management controllers to advanced HEV architectures, such as combined and plug-in HEVs, as well as to optimization problems that include performance indices in addition to fuel economy, such as pollutant emissions, driveability, and thermal comfort.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Control of hybrid electric vehicles


    Contributors:

    Published in:

    Publication date :

    2007


    Size :

    11 Seiten, 49 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Induction Motor Control Schemes for Hybrid Electric Vehicles/Electric Vehicles

    Sarin, M.V. / Chitra, A. / Sanjeevikumar, P. et al. | Wiley | 2020



    Adaptive control for hybrid electric vehicles

    Wirasingha,S.G. / Lukic,S.M. / Rodriguez,F. et al. | Automotive engineering | 2011


    Hybrid electric vehicles advanced control system

    Giuffre,F. / Rizzotto,G. / Itali,F. et al. | Automotive engineering | 2001


    Hybrid electric vehicles

    Future Transportation Technology Conference | TIBKAT | 2000