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用于电力开关柜散热的脉动热管参数优化

Parameter Optimization of Pulsating Heat Pipes for the Heat Dissipation of Electric Switchgear Cabinets

  • 摘要: 为进一步提高电力开关柜母线的散热能力,将直径为2 mm圆形脉动热管加装于电力开关柜B相母线表面,选取脉动热管充液率、通风进口风速、母线负载电流作为因素,采用中心复合设计法进行脉动热管散热优化实验;基于实验结果采用多元线性回归建立B相母线表面平均温度与因素之间的函数关系,采用响应曲面法模拟分析不同因素交互作用下B相母线表面平均温度的变化情况,优化脉动热管工况参数,且通过温升实验验证响应曲面法预测结果的准确性。结果表明:对于加装脉动热管的电力开关柜,通风进口风速、母线负载电流以及通风进口风速和负载电流的交互作用对电力开关柜B相母线表面平均温度的影响较为显著;当负载电流为853 A、通风进口风速为1.7 m/s、脉动热管的充液率为50%时,电力开关柜母线表面平均温度最低,电力开关柜母线表面散热能力最强;温升实验测试结果的平均值均落在响应曲面95%置信区间内,验证了响应曲面法预测结果的准确性。

     

    Abstract: Abstrace: To further improve the heat dissipation ability of busbars in electric switchgear cabinets, a circular pulsating heat pipe with a diameter of 2 mm was installed on the surface of the B-phase busbar. Factors including the filling ratio of the pulsating heat pipe, air inlet velocity, and busbar load current were chosen for optimization experiments using the central composite design method. Based on experimental results, a multivariate linear regression model was established to describe the relationship between the average surface temperature of the B-phase busbar and these factors. Response surface methodology was applied to simulate and analyze changes in the average surface temperature of the B-phase busbar under different interactions among factors, optimizing the operating parameters of the pulsating heat pipe. The accuracy of the response surface methodology prediction was verified through temperature rise experiments. Results show that for electric switchgear cabinets with added pulsating heat pipes, the air inlet velocity, busbar load current, and their interaction significantly affect the average surface temperature of the B-phase busbar. When the load current is 853 A, air inlet velocity is 1.7 m/s, and the filling ratio of the pulsating heat pipe is 50%, the average surface temperature of the busbar reaches its lowest point, indicating the strongest heat dissipation capability. The mean values of the temperature rise experiment fall within the 95% confidence interval of the response surface, confirming the accuracy of the predictions made by the response surface methodology.

     

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