This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller. This study provides a sound basis for the further study of stochastic MPC and NMPC for the HEV power management with the consideration of battery aging and thermal performance.


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    Title :

    Nonlinear Model Predictive Control of a Power-Split Hybrid Electric Vehicle with Electrochemical Battery Model


    Additional title:

    Sae Technical Papers


    Contributors:
    Chen, Bo (author) / Feng, Lei (author) / Cheng, Ming (author)

    Conference:

    WCX™ 17: SAE World Congress Experience ; 2017



    Publication date :

    2017-03-28




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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