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To improve the cooling effect, this paper proposed a highly symmetrical bionic network channel cold plate. It firstly analyzed the influence of the cold plate’s structure parameters on its performance through single-factor analysis, then, optimized the structure parameters of the cold plate using the Multi-ObjectiveParticle Swarm Optimization (MOPSO) algorithm, with the average temperature, temperature standard deviation, and coolant pressure loss of the cold plate serving as performance indexes. The optimal channel width, channel depth, and cold plate wall thickness were found to be 9.0 mm, 1.5 mm, and 1.4 mm respectively. The corresponding average temperature, temperature standard deviation, and pressure loss were measured as 33.20 ℃, 1.33 ℃, and 65.63 Pa respectively. When compared with the initial structural parameters, the optimized mean temperature and temperature standard deviation decreased by 1.92 ℃ and 0.02 ℃ respectively, while the pressure loss increased by 27.10 Pa. Finally, the optimization results were verified using the battery module.
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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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