LI Tianxing, DU Haoran, LIU Yongzhi, et al. Nonlinear Modeling and Hardware-in-the-Loop Implementation of Three-Stage Aircraft Power Generation Systems[J]. 2024, 58(11): 205-216.
DOI:
LI Tianxing, DU Haoran, LIU Yongzhi, et al. Nonlinear Modeling and Hardware-in-the-Loop Implementation of Three-Stage Aircraft Power Generation Systems[J]. 2024, 58(11): 205-216.DOI: 10.7652/xjtuxb202411020.
Nonlinear Modeling and Hardware-in-the-Loop Implementation of Three-Stage Aircraft Power Generation Systems
To address the sluggish progress in fault diagnosis and condition monitoring of three-stage aircraft power generation systems
this paper investigates the system's nonlinear relationships and signal transmission logic by developing a nonlinear model of the power generation system and a hardware-in-the-loop test platform. Initially
a current-flux linkage neural network is utilized to model the nonlinear relationship of motor current-flux linkage. Subsequently
an improved variable parameter average value model is introduced to accurately predict the output voltage drop of the rotary rectifier. Finally
the signal transmission logic of the system is analyzed to finalize the nonlinear modeling process. The hardware-in-the-loop test platform is established by combining the nonlinear model of the three-stage aircraft power generation system with the RT-LAB real-time simulator
and its effectiveness and control capability are verified against GJB 181B—2012. The verification results show that under the requirement of a 45 kV·A output power for small single-engine aircraft
the three-phase AC output maintains a stable voltage of 113.017 4 V
with a voltage unbalance of 0.253 2 V and a voltage modulation amplitude of 2.059 6 V
meeting the power supply quality standard required by GJB 181B—2012. Additionally
the platform can precisely track any specified output power within the 30 to 50 kV·A range. This platform leverages nonlinear modeling technology and hardware-in-the-loop methodology to eliminate the traditional requirements for experimental environments in aircraft power generation system research. It can lower research costs
shorten project durations
and expedite research on aircraft power generation system controllers and upgrades.
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references
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