Optimization of the special-shaped relief groove structure of fuel gear pump based on multi-cavity lumped parameter model
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摘要:
高效卸荷槽的设计与优化是缓解航空燃油齿轮泵因高速化、高压化、高温化而产生的剧烈困油问题的有效措施。为此提出了一种基于多容腔集中参数模型的燃油齿轮泵卸荷槽结构优化方法，引入集中参数框架建立燃油齿轮泵多容腔性能模型，对两种典型及异形卸荷槽的工作性能展开对比分析，确定异形卸荷槽优化方向；基于神经网络建立代理模型并通过遗传算法优化程序对异形卸荷槽结构参数进行多目标性能优化，并对优化前后卸荷槽的困油特性进行仿真对比。研究结果表明：所构建的燃油齿轮泵多容腔性能模型具有较高的仿真精度，仿真结果与试验结果的误差在5%以内；异形卸荷槽抑制空化和缓解流量脉动的能力显著，与传统卸荷槽相比出口流量脉动下降约20%；优化后卸荷槽与原卸荷槽相比，齿轮泵出口流量品质基本不变且齿腔困油区压力峰值由12.49 MPa减少至10.52 MPa，下降约15.77%，工作性能更优，能够显著缓解困油带来的不利影响。
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关键词:
- 航空发动机航空燃油泵 /
- 齿轮泵困油现象 /
- 多容腔集中参数 /
- 异形卸荷槽 /
- 结构优化
Abstract:The design and optimization of the new high-efficiency relief groove is an effective measure to alleviate the drastic fuel trapping problem of aviation fuel gear pumps due to high speed, high pressure and high temperature. A research method of fuel gear pump relief groove structure optimization based on multi-cavity lumped parameter model was proposed, which introduced a lumped parameter framework to establish a multi-cavity performance model of the fuel gear pump; and a comparative analysis of the working performance of two typical and special-shaped relief grooves was conducted to determine the direction of the optimization of special-shaped relief grooves; and a multi-objective performance optimization of the structural parameters of the special-shaped relief groove based on the optimization engine of the neural network coupled genetic algorithm was carried out. The fuel trapping characteristics of the relief groove before and after optimization were compared in simulation. The results showed that: the constructed multi-cavity lumped performance model of the fuel gear pump had high simulation accuracy, and the error between the simulation results and the experimental results was within 5%; the ability of the special-relief groove to inhibit cavitation and alleviate the flow pulsation was remarkable, and the outlet flow pulsation decreased by about 20%. Compared with the original relief groove, the optimized relief groove had basically the same outlet flow quality and the peak pressure in the fuel-trapped area of the tooth cavity was reduced from 12.49 MPa to 10.52 MPa, a decrease of about 15.77%, which had a better working performance and can significantly alleviate the adverse effects caused by the fuel trapping.
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图 3 吸排油腔与其他容腔的流量交换
Figure 3. Flow exchange between suction and discharge chambers and other chambers
图 4 相邻齿腔间的端面泄漏与顶隙泄漏
Figure 4. End face leakage and headspace leakage between adjacent tooth cavities
图 6 交互区齿腔与吸、排油腔的过流面积及意义
SHG1 排油腔与主动齿腔的轴向过流面积；SHV1 排油腔与主动齿腔的径向过流面积；SLG1 吸油腔与主动齿腔的轴向过流面积；SLV1 吸油腔与主动齿腔的径向过流面积；SHG2 排油腔与从动齿腔的轴向过流面积；SHV2 排油腔与从动齿腔的径向过流面积；SLG2 吸油腔与从动齿腔的轴向过流面积；SLV2 吸油腔与从动齿腔的径向过流面积。
Figure 6. Overflow area and significance of tooth cavities and suction and discharge cavities in the interaction zone
图 7 困油区齿腔的啮合泄漏与侧隙泄漏
Figure 7. Engagement leakage and side gap leakage of tooth cavity in fuel-trapped area
图 9 两种典型卸荷槽及异形卸荷槽结构图
Figure 9. Structural drawings of two typical relief grooves and the special-shaped relief groove
图 10 无卸荷槽及不同卸荷槽下的齿腔压力
Figure 10. Cavity pressures with no relief groove and with different designs of relief grooves
图 11 无卸荷槽及不同卸荷槽设计的齿轮泵出口流量脉动
Figure 11. Outlet flow pulsations of gear pumps without relief groove and with different of under relief groove
图 13 燃油齿轮泵外特性试验数据与仿真数据
Figure 13. Fuel gear pump external characteristics test data and simulation data
图 14 燃油齿轮泵异形卸荷槽优化流程
Figure 14. Optimization process for the special-shaped relief groove in fuel gear pumps
图 18 数值模拟结果与神经网络预测结果对比图
Figure 18. Plot of numerical simulation results against neural network prediction results
图 20 优化前后卸荷槽轮廓对比
Figure 20. Comparison of relief groove profiles before and after optimization
图 21 优化前后燃油齿轮泵困油特性对比
Figure 21. Comparison of fuel trapping characteristics of fuel gear pumps before and after optimization
表 1 燃油齿轮泵结构参数
Table 1. Parameters of the fuel gear pumps
参数 数值 压力角/（°） 28 模数/mm 2 齿宽/mm 9 齿数/个 13 顶隙系数 1 齿顶高系数 0.25 
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表 2 4级精度齿轮对应偏差
Table 2. Deviation corresponding to 4th level precision gears
μm 偏差类型 4级精度公差限值 齿距累计总偏差Fp 3.36 齿廓总偏差Fα 1.73 径向综合总偏差$ {F}''_{{\mathrm{i}}} $ 11.3 径向跳动Fr 1.81 螺旋线总偏差Fβ 1.92
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表 3 油液主要参数
Table 3. Main parameters of the fuel
参数 数值 密度/（kg/m3） 780 动力黏度/10−3 （Pa·s） 1.15 初始体积弹性模量/MPa 1700 油液温度/℃ 20
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表 4 不同卸荷槽出口流量数据
Table 4. Outlet flow data for different relief groove designs
卸荷槽形状 Qmax/
（L/min）Qmin/
（L/min）Qavg/
（L/min）σQ/% 矩形卸荷槽 20.32 11.65 16.50 52.54 圆形卸荷槽 20.09 12.02 16.42 49.10 异形卸荷槽 18.23 13.52 16.30 28.33
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表 5 抽样样本对应的数值模拟结果
Table 5. Numerical simulation results corresponding to the samples
序号 $ {l} $/mm d0/mm $ {{p}}_{{{\mathrm{f,peak}}}} $/MPa Qavg/（L/min） 1 5.14 21.56 9.45 15.87 2 5.69 20.11 8.51 15.87 3 5.58 21.10 9.69 16.04 4 5.23 21.18 9.10 15.83 5 5.93 21.92 11.59 16.26 6 5.75 21.68 10.90 16.20 7 5.40 20.06 7.87 15.61 8 6.45 21.21 11.62 16.29 9 6.25 21.73 11.96 16.29 10 6.38 20.50 10.48 16.24 11 4.99 21.82 9.53 15.83 12 6.28 20.20 9.83 16.19 13 5.19 20.49 8.05 15.58 14 5.36 20.81 8.82 15.81 15 5.83 20.97 10.02 16.13 16 6.00 20.34 9.46 16.11 17 6.03 20.74 10.12 16.18 18 5.53 21.42 10.08 16.08 19 6.14 21.32 11.18 16.26 20 4.91 20.66 7.72 15.39
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表 6 抽样所得验证样本
Table 6. Validation samples from sampling
mm 序号 l d0 1 5.13 20.41 2 6.50 21.60 3 4.94 20.48 4 5.53 21.21 5 6.37 21.90
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表 7 误差计算结果
Table 7. Calculation of the error
优化目标 神经网络预测值 数值模拟值 εmap/% 齿腔困油压力峰值
pf，peak/MPa7.80 8.01 2.71 12.26 12.49 7.54 7.66 9.76 9.15 12.42 12.30 出口平均流量
$ {{Q}}_{\rm{avg}} $/（L/min）15.49 15.32 0.68 16.30 16.31 15.36 15.12 16.04 15.94 16.30 16.31
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表 8 优化前后卸荷槽性能对比
Table 8. Performance comparison of relief groove before and after optimization
卸荷槽形状 $ {l} $/mm $ {{{d}}}_{{0}} $/mm pf，peak预测值/MPa pf，peak模拟值/MPa Qavg预测值/（L/min） Qavg模拟值/（L/min） 原卸荷槽 6.50 21.60 12.49 16.30 优化后卸荷槽 5.93 21.31 10.73 10.52 16.21 16.21
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