Along with the shortage of energy and the increasingly serious pollution of environment in cities, automobile industries all over the world are exploring and developing energy saving and clean automobile. Hydraulic hybrid vehicle has better potential in medium-size and large-size passenger vehicles than its electric counterparts. The key components' sizes have remarkable influence on the vehicle performance and fuel economy, and an optimization process is needed to find the best design parameters for maximum fuel economy while satisfying the vehicle performance constraints. multi-objective optimization method based on adaptive simulated annealing genetic algorithm (ASAGA) is proposed to optimize the key components in HHV. In the objective function of the optimization, all the weighting factors can be set with different values according to different requirements. The optimal results show that the proposed method effectively distinguishes the key components' optimal parameters' position of HHV, enhances the performance and fuel consumption.


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    Title :

    Multi-objective optimization for hydraulic hybrid vehicle based on adaptive simulated annealing genetic algorithm


    Additional title:

    Multikriterielle Optimierung eines hydraulischen Hybridfahrzeuges auf Basis des adaptiven genetischen Simulated-Annealing-Algorithmus


    Contributors:
    Hui, Sun (author)


    Publication date :

    2010


    Size :

    7 Seiten, 6 Bilder, 4 Tabellen, 16 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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