研究目的
To design and optimize a solar power conversion system for space applications, focusing on maximizing the ratio of daily average deliverable power to total system mass (W/kg) using multi-objective optimization with a Genetic Algorithm, and to evaluate and compare different DC-DC converter topologies for suitability in space environments.
研究成果
The non-inverting buck-boost converter with eGaN transistors in a DMPPT architecture is identified as the optimal choice for space applications, achieving a specific power of 35.56W/kg. The prototype demonstrates high efficiency (98.4%), power density (3.54W/cm3), specific power (3.76W/g), and reliability under low-temperature conditions, validating the design and optimization approach for solar power systems in space.
研究不足
The study assumes specific metrics for conductor density, resistivity, converter mass, PV panel area, and mass, which may not account for all real-world variations. The optimization is based on theoretical loss models and may not fully capture all practical inefficiencies. Low-temperature testing is limited by the microcontroller's failure at extreme temperatures, and the prototype uses parameters close to but not exactly the optimized values.
1：Experimental Design and Method Selection:
The study employs a multi-objective optimization using a Genetic Algorithm to optimize system parameters (battery voltage, PV maximum power, PV maximum power point voltage, number of panels per string) for a 500kW solar microgrid. Four DC-DC converter topologies (buck, boost, buck-boost, non-inverting buck-boost) are evaluated based on efficiency and loss models.
2：Sample Selection and Data Sources:
The optimization uses practical ranges for parameters (e.g., battery voltage 300-800V, PV power 100-600W) based on terrestrial and space application standards.
3：List of Experimental Equipment and Materials:
Components include GaN MOSFETs (e.g., GS66508T), inductors (e.g., ER32/6/25-3F36 core), capacitors, and a control board with STM32F108C8T6 microcontroller.
4：Experimental Procedures and Operational Workflow:
A prototype of the non-inverting buck-boost converter is built and tested for efficiency using a DC source, electronic load, and power analyzer. Low-temperature testing is conducted in a chamber with cycles from 0°C to -140°C to assess reliability.
5：Data Analysis Methods:
Efficiency is measured and compared to theoretical models; system performance is analyzed using the W/kg metric and Pareto front from the Genetic Algorithm optimization.
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