研究目的
To develop a universal control scheme for solar array simulators that eliminates mode transitions and provides stable, fast tracking across the entire I-V curve of photovoltaic panels.
研究成果
The proposed universal control scheme using operating point projection effectively eliminates mode transitions, providing stable and fast tracking across the entire I-V curve. It is suitable for high-performance SAS applications with complex irradiance patterns, as validated by simulations and experiments showing improved response and reduced oscillations compared to conventional methods.
研究不足
The study is limited to a specific 120W PV panel and uses a buck converter topology; it may not generalize to all panel types or power levels. Experimental noise and component tolerances could affect results, and the method relies on accurate panel data from datasheets.
1：Experimental Design and Method Selection:
The study employs a novel operating point projection technique to design a single PID controller for SAS, avoiding the need for multiple controllers. It involves theoretical analysis of loop stability and practical implementation using a buck converter and DSP-based control.
2：Sample Selection and Data Sources:
A 120W PV panel (MSX120) is emulated under standard test conditions (1000W/m2 irradiance, 25°C temperature). Data is sourced from panel datasheets and simulated/experimental setups.
3：List of Experimental Equipment and Materials:
Includes a buck power converter with specified components (inductor, capacitor, etc.), resistive loads, F28377S DSP board for control implementation, and simulation tools like PSIM.
4：Experimental Procedures and Operational Workflow:
Simulations are conducted in PSIM with load changes (e.g., from 12Ω to 40Ω) to test transient response. Experiments involve building a prototype SAS, implementing the control algorithm on DSP, and capturing output waveforms (voltage, current, duty cycle) during load transients.
5：Data Analysis Methods:
Performance is evaluated based on stability, response speed, and comparison with conventional hybrid control methods. Data from simulations and experiments are summarized in tables for quantitative analysis.
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