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A model-based interfacing concept for accurate power hardware-in-the-loop systems

Author

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  • Stefan Jakubek
  • Elisabeth Luchini
  • Alexander Oberhummer
  • Felix Pfister

Abstract

This article introduces a novel concept for the interface of power hardware-in-the-loop (PHiL) test systems. In a PHiL system, a real device under test is connected to dynamic simulation models that emulate high power flows running to and from the device under test. The states of these dynamic models are thus used to physically actuate the real hardware component and likewise the states of the latter serve as an external excitation of the dynamic model. Thus, a PHiL system constitutes a complex interaction of dynamic mathematical models and real hardware components. The purpose of PHiL systems is to operate and test the hardware component as closely to its future designated environment as possible. A crucial factor for a highly accurate PHiL system lies in the interface between virtual dynamic simulation and the physical hardware. Accuracy and performance is often impaired by signal communication delays, sensor noise and insufficient performance of test bed control systems. The approach presented in this article reduces unwanted oscillations based on an online receding optimization of specific state variables in the dynamic simulation environment. In addition, the adherence to physical conservation laws is assured. The interface algorithm makes use of an online model which incorporates knowledge about the dynamics in the underlying simulation. The performance of the proposed methodology is demonstrated and discussed by means of a highly dynamic automotive powertrain PHiL test bed in combination with a complex multibody real-time vehicle simulation.

Suggested Citation

  • Stefan Jakubek & Elisabeth Luchini & Alexander Oberhummer & Felix Pfister, 2016. "A model-based interfacing concept for accurate power hardware-in-the-loop systems," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 22(1), pages 1-20, January.
  • Handle: RePEc:taf:nmcmxx:v:22:y:2016:i:1:p:1-20
    DOI: 10.1080/13873954.2015.1069748
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    References listed on IDEAS

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    1. Albers, C.J. & Critchley, F. & Gower, J.C., 2011. "Quadratic minimisation problems in statistics," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 698-713, March.
    2. Albers, C.J. & Critchley, F. & Gower, J.C., 2011. "Applications of quadratic minimisation problems in statistics," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 714-722, March.
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