Battery Emulation for Power-HIL Using Local Model Networks and Robust Impedance Control

Abstract

Battery emulation with a controllable high-power dc supply enables repeatable hardware-in-the-loop testing of powertrains for hybrid and electric vehicles. For this purpose, not only the power flow but also the nonlinear characteristic and dynamic impedance of batteries need to be emulated. In this paper, nonlinear local model networks are used to obtain dynamic battery models with high fidelity that can be computed in real time. This approach also allows the extraction of local linear impedance models for high-bandwidth impedance emulation, leading to a tighter coupling between the test bed and simulation model with predictable closed-loop dynamics. A model predictive controller that achieves optimal control with adherence to system constraints is extended to impedance control and robustness against constant power loads. This results not only in superior dynamic performance but also in stable dc-bus voltage control even for testing of tightly controlled electric motor inverters with negative differential input resistance. Since the controller design is based on a model of the test bed setup including the virtual battery model, emulator hardware, and input characteristics of the powertrain under test, it is possible to systematically analyze stability.