Model-based predictive control of dc-dc converter for EV applications

  • Authors

    • Chang Hyun Kim
    • Houng Kun Joung
    https://doi.org/10.14419/ijet.v7i2.12.11312

    Received date: April 9, 2018

    Accepted date: April 9, 2018

    Published date: April 3, 2018

  • MPC, EV Charger, DC-DC Converter, Optimal Control, Off-Board EV Charger

  • Abstract

    Background/Objectives: The power performance of electric vehicle chargers depends on the control efficiency of the power converters with on-board and off-board types. In this paper, a new control method is proposed for power converter of fast electric vehicle chargers in order to improve the power efficiency.

    Methods/Statistical analysis: The proposed control method is the optimal control to minimize the performance objectives from the predicted output, based on the system model. The discretized model of DC-DC converter with sampling time is derived by using lifting operation for taking into account with the desired prediction time.

    Findings: The existing conventional controllers are obtained by off-line optimal solution and applied to the systems. Once the control gain is determined, the controller is able to reflect the system response at the real-time.

    Improvements/Applications: The proposed control method has advantages to deal with system performances at real-time and the control actuation is updated every sampling time via the derived mathematical model. It can be directly applicable to real electric vehicle charger systems in industry.

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  • How to Cite

    Hyun Kim, C., & Kun Joung, H. (2018). Model-based predictive control of dc-dc converter for EV applications. International Journal of Engineering and Technology, 7(2.12), 308-311. https://doi.org/10.14419/ijet.v7i2.12.11312