Analysis of dynamic and static features of intrinsically safe electromagnetic valves and optimization of influencing parameters
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摘要: 针对在驱动功率和电磁阀体积约束下存在的电磁铁驱动力不足、电磁阀响应速度慢的问题，分析了电磁阀的动静态特性，通过仿真分析和样机试验验证了提高本安型电磁铁电磁力可明显改善电磁阀的响应特性，确定了通过优化电磁力改善电磁阀响应特性的方案。提出了本安型电磁铁特性评价指标：有效行程指标、平均电磁力指标和静态综合性能指标，解决了因电磁铁行程不同而造成的电磁铁性能评价困难的问题。利用Maxwell电磁仿真软件分析了导向筒深度变化量δa、衔铁半径变化量δb、非工作气隙变化量δc1、非工作气隙变化量δc2、盆口高度变化量δd对电磁铁静态特性的影响，得到不同参数对静态特性的敏感度，为参数优化中尺寸控制范围的选择提供参考依据。通过正交试验结果构建了铁芯结构参数对电磁铁综合特性评价指标的二阶响应面模型，利用遗传算法对铁芯参数进行优化。样机试验结果表明：优化后电磁铁水平段电磁力提升了50%，有效行程提高了26%，本安型电磁阀的开启响应时间缩短了52.5%。Abstract: In response to the problems of insufficient electromagnetic driving force and slow response speed of electromagnetic valves under the constraints of driving power and electromagnetic valve volume, the dynamic and static features of electromagnetic valves are analyzed. Through simulation analysis and prototype experiments, it is verified that improving the intrinsically safe electromagnetic force can significantly improve the response features of electromagnetic valves. A plan to improve the response features of electromagnetic valves by optimizing the electromagnetic force is determined. The evaluation indicators for the features of intrinsically safe electromagnets, including effective stroke index, average electromagnetic force index, and static comprehensive performance index, have been proposed to solve the problem of difficult performance evaluation of electromagnets caused by different stroke. The Maxwell electromagnetic simulation software is used to analyze the effects of changes in guide tube depth, armature radius, non working air gap, non working air gap, and pot mouth height on the static features of the electromagnet. The sensitivity of different parameters to the static features is obtained, providing a reference for selecting the size control range in parameter optimization. A second-order response surface model is constructed based on the results of orthogonal experiments to evaluate the comprehensive features of electromagnets using iron core structural parameters. Genetic algorithm is used to optimize the iron core parameters. The prototype test results show that the optimized electromagnetic force in the horizontal section of the electromagnet has increased by 56%, the effective stroke has increased by 26%, and the opening response time of the intrinsically safe electromagnetic valve has been shortened by 52.5%.
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图 1 本安型电磁铁结构及磁路
Figure 1. Structure and magnetic circuit of intrinsically safety mining electromagnets
图 5 10.5 V激励下电磁阀的压力响应特性
Figure 5. Pressure response characteristics of solenoid valve under 10.5 V excitation
图 6 12.5 V激励下电磁阀的压力响应特性
Figure 6. Pressure response characteristics of solenoid valve under 12.5 V excitation
图 9 非工作气隙c1对静态特性的影响
Figure 9. Influence of non-working air gap c1 on static characteristics
图 10 非工作气隙c2对静态特性的影响
Figure 10. Influence of non-working air gap c2 on static characteristics
图 11 盆口高度d对静态特性的影响
Figure 11. Influence of height d of basin structure on static characteristics
图 12 盆口高度和工作气隙对磁感应强度的影响
Figure 12. Influence of the height of the basin structure and the working air gap on the magnetic induction intensity
图 13 电磁铁静态综合性能及对各参数的敏感度
Figure 13. Static comprehensive performance of electromagnet and sensitivity to various parameters
图 14 参数优化前后仿真电磁力对比
Figure 14. Comparison of simulated electromagnetic force before and after parameter optimization
图 15 参数优化前后样机电磁力对比
Figure 15. Comparison of electromagnetic force of prototype before and after parameter optimization
图 16 10.5 V激励下优化后电磁阀的压力响应特性
Figure 16. Pressure response characteristics of the optimized solenoid valve under 10.5 V excitation
表 1 仿真材料设置
Table 1. Material settings for simulation
零件名称 材料 壳体 Steel_1010 衔铁 Steel_1010 极靴 Steel_1010 线圈 Copper 骨架 Teflon 
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表 2 关键尺寸参数变化范围
Table 2. Range of changes in key dimensional parameters
mm 参数 最小值 最大值 颗粒度 $\delta_ {{a}}$ −4 0 0.25 $\delta _{{b}}$ −0.4 0 0.05 $\delta _{{c1}}$ −0.05 0.05 0.01 $\delta _{{c2}}$ −0.05 0.05 0.01 $\delta _{{d}}$ −0.5 0.5 0.2
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表 3 试验参数设置及计算结果
Table 3. Experimental parameter settings and calculation results
序号 δa/mm δb/mm δc1/mm δc2/mm δd/mm λ 1 −2 7.75 −0.05 −0.05 0 303.824 2 −2 7.75 −0.05 −0.05 0 337.021 3 −4 7.75 −0.05 0 0 290.789 4 −2 8.5 −0.05 0 −0.5 292.208 5 −2 7 −0.05 0 −0.5 277.848 $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ 49 −2 8.5 −0.05 0 0.5 265.928
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表 4 方差分析
Table 4. Analysis of variance
方差来源 P值 方差来源 P值 方差来源 P值 模型 ＜0.000 1 δaδc1 0.714 6 δc1δd 0.722 1 δa 0.363 6 δaδc2 0.985 2 δc2δd 0.842 0 δb 0.000 4 δaδd 0.910 2 δa2 0.628 2 δc1 0.016 8 δbδc1 0.848 4 δb2 0.021 2 δc2 ＜0.000 1 δbδc2 0.309 3 δc12 0.436 9 δd 0.000 4 δbδd 0.000 8 δc22 0.875 1 δaδb 0.605 3 δc1δc2 0.883 1 δd2 0.225 5
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表 5 参数优化前后对比
Table 5. Comparison before and after parameter optimization
参数 δa/mm δb/mm δc1/mm δc2/mm δd/mm $L$/mm ${F_{{\mathrm{av}}}}$ $\lambda $ 优化前 0 7.879 0.063 0.049 0 33.67 244.8 278.5 优化后 −4 7.5 −0.023 −0.05 0.5 69.31 270.2 339.5
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