Full
Outline
The large-scale application of megawatt-level off-board chargers faces problems such as high energy consumption, low dynamic accuracy, and lack of multi-module collaborative detection capabilities existing in traditional detection methods. A model prediction test method integrating model-in-the-loop (MIL) simulation and orthogonally optimized long short-term memory network (Orthogonal-LSTM) is proposed, aiming to break through the power bottleneck of test platform and improve detection adaptability under complex working conditions. By constructing a virtual charger model driven by model predictive control (MPC), the dynamic characteristics of the charger under test are simulated. However, in the face of the superposition of charging modules and the increase in power, the error between the model and the actual test results increases. To solve this problem, the LSTM model parameters are optimized in combination with the orthogonal test method to achieve the error prediction-compensation of the model. Experimental results show that the proposed method provides a high-precision, low-energy-consumption and scalable detection solution for megawatt-class chargers with a single-unit multi-module structure, and has great value for engineering promotion.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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