Increasing engine power and efficiency using a particle swarm optimization technique is investigated by using thermodynamics based quasi-steady engine simulation model. A simplified engine friction model is also incorporated to estimate the brake power output. Further, a simple knock model is used to make sure of knock free engine operation. Model is calibrated and validated to a Ford Falcon AU six-cylinder gasoline engine.Nine different engine-operating parameters are considered as input variables for the optimization; spark timing, equivalence ratio, compression ratio, inlet and exhaust vale opening timing and durations, maximum inlet valve lift and manifold pressure. Significant improvement of the engine power output for a given amount of induced gas is observed with the optimized conditions when compared to the corresponding power output with the reference engines normal operating conditions. Further, the importance of variable compression ratio and intelligent valve control, for maximum power output for a given amount of mass induced, is understood from this investigation


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Enhanced ICSI Engine Performance With Particle Swarm Optimization


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SIAT 2004 ; 2004



    Publication date :

    2004-01-16




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Enhanced ICSI Engine Performance with Particle Swarm Optimization

    Ratnaweera, A. / Halgamuge, S.K. / Watson, H.C. | British Library Conference Proceedings | 2004


    Application of Particle Swarm Optimization for Diesel Engine Performance Optimization

    Karra, Prashanth / Kong, Song-Charng | SAE Technical Papers | 2010



    Particle Swarm Optimization with Enhanced Autonomous Search Ability of Each Particle

    Iima, H. / Kuroe, Y. | British Library Online Contents | 2008


    Particle Swarm Optimization

    Gerhard Venter / Jaroslaw Sobieszczanski-Sobieski | AIAA | 2003