An advanced powertrain cooling system with appropriate control strategy and active actuators allows greater flexibility in managing engine temperatures and operating near constraints. An organized controls development process is necessary to allow comparison of multiple configurations to select the best way forward. In this work, we formulate, calibrate and validate a Model Predictive Controller (MPC) for temperature regulation and constraint handling in an advanced cooling system. A model-based development process was followed; where the system model was used to develop and calibrate a gain scheduled linear MPC. The implementation of MPC for continuous systems and the modification related to implementing switching systems has been described.Multiple hardware configurations were compared with their corresponding control system in simulations. The system level requirements were translated into MPC calibration parameters for consistent comparison between multiple configurations. Some of the configurations were then evaluated via hardware in the loop testing prior to evaluation in a vehicle. The paper works through key steps related to the development of MPC for system level evaluation of actuators for powertrain thermal management.


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    Titel :

    Vehicle Powertrain Thermal Management System Using Model Predictive Control


    Weitere Titelangaben:

    Sae Int. J. Mater. Manf
    Sae International Journal of Materials and Manufacturing


    Beteiligte:
    Fuxman, Adrian (Autor:in) / Karnik, Amey Y. (Autor:in) / Pekar, Jaroslav (Autor:in) / Jankovic, Mrdjan (Autor:in) / Bonkoski, Phillip (Autor:in)

    Kongress:

    SAE 2016 World Congress and Exhibition ; 2016



    Erscheinungsdatum :

    2016-04-05


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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    Calibration and Demonstration of Vehicle Powertrain Thermal Management Using Model Predictive Control

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    Calibration and Demonstration of Vehicle Powertrain Thermal Management Using Model Predictive Control

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