研究目的
Investigating the application of high-gain observers for fault detection and isolation in boost dc–dc converters within photovoltaic maximum power point tracking systems to mitigate inefficiencies caused by open- and short-circuit faults.
研究成果
The proposed robust model-based FDI technique for boost dc–dc converters in PV MPPT systems effectively operates under closed-loop control, decouples from load variations and irradiance changes, and enables fast and reliable detection of OSCFs. The use of high-gain observers mitigates the shortcomings of model-based FDI techniques, as demonstrated by experimental results. The study highlights the importance of an integral control action in the closed-loop operation for HGO-based FDI schemes.
研究不足
The study acknowledges the challenges of parametric uncertainty and no-modelled dynamics in model-based FDI techniques. The proposed solution mitigates these issues but may still be affected by extreme conditions not covered in the experimental tests.
1:Experimental Design and Method Selection:
The study employs a model-based FDI technique using high-gain observers as residual generators to detect and isolate faults in boost dc–dc converters. The methodology includes the design of a nominal closed-loop control algorithm and the development of a faulty model for FDI purposes.
2:Sample Selection and Data Sources:
Experimental tests were conducted on a boost dc–dc converter of 350 W, using a battery bank as load and two PVMs in parallel connection. The irradiance drop was emulated by disconnecting one of the PVMs.
3:List of Experimental Equipment and Materials:
The setup includes a boost dc–dc converter, a battery bank, PVMs, and a dSpace board (DS1104) for running the control algorithm.
4:Experimental Procedures and Operational Workflow:
The control algorithm runs at a sampling frequency of 40 kHz, with observer gains and thresholds selected for fast and reliable fault diagnosis. The FDI technique is validated through experimental results under harsh fault scenarios.
5:Data Analysis Methods:
The residual signal is analyzed using a windowed norm for fault detection, with thresholds selected to account for measurement noise and the peaking phenomenon.
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