The design procedure for an adaptive power management control strategy, based on a driving pattern recognition algorithm is proposed. The design goal of the control strategy is to minimize fuel consumption and engine-out NOx and PM emissions on a set of diversified driving schedules. Six representative driving patterns (RDP) are designed to represent different driving scenarios. For each RDP, the Dynamic Programming (DP) technique is used to find the global optimal control actions. Implementable, sub-optimal control algorithms are then extracted by analyzing the behavior of the DP control actions. A driving pattern recognition (DPR) algorithm is subsequently developed and used to classify the current driving pattern into one of the RDPs; thus, the most appropriate control algorithm is selected adaptively. This 'multi-mode' control scheme was tested on several driving cycles and was found to work satisfactorily.


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    Title :

    Driving pattern recognition for control of hybrid electric trucks


    Contributors:
    Lin, Chan-Chiao (author) / Jeon, Soonil (author) / Peng, Huei (author) / Lee, Jang-Moo (author)

    Published in:

    Vehicle System Dynamics ; 42 , 1-2 ; 41-58


    Publication date :

    2004


    Size :

    18 Seiten, 19 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Driving Pattern Recognition for Control of Hybrid Electric Trucks

    Lin, Chan-Chiao / Jeon, Soonil / Peng, Huei et al. | Taylor & Francis Verlag | 2004


    Driving pattern recognition for control of hybrid electric trucks

    Lin,C.C. / Jeon,S. / Peng,H. et al. | Automotive engineering | 2004



    Driving Pattern Recognition for Control of Hybrid Electric Trucks

    Lin, C.-C. / Jeon, S. / Peng, H. et al. | British Library Conference Proceedings | 2004


    Hybrid-electric trucks

    Carney,D. | Automotive engineering | 2002