Identification of key transfer parameters of rocket engine pressurization system
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摘要:
针对火箭增压系统设计过程中关键换热参数难以确定的问题，提出1种基于混沌自适应粒子群算法（ACPSO）的增压系统换热参数辨识方法。建立了考虑换热模型的液体火箭增压系统非线性数学模型，通过灵敏度分析筛选出待识别参数，采用含有早熟抑制和惯性权重自适应调节策略的粒子群方法对选定参量进行辨识，对引入了权重衰减机制的方均根目标函数进行优化。结果表明：辨识后的仿真曲线与实测曲线具有良好的一致性，氧箱增压电磁阀打开时间仿真值与实测值偏差低于3%，气瓶1次飞行结束温度仿真值与实测值仅相差2.4 K。将辨识结果应用于某相似的新研型号，气瓶设计容积和质量相比绝热假设的设计方案降低了32 L和11.6 kg，有效减少了由设计过度冗余造成的额外试验和设计迭代成本。
Abstract:In order to solve the difficulty of determining the key heat transfer parameters in the design of rocket pressurization system, a heat transfer parameter identification method based on adaptive chaotic particle swarm optimization (ACPSO) algorithm was proposed. The mathematical model of the pressurization system considering the heat transfer terms was established. The parameters to be identified were selected by sensitivity analysis, and then identified by particle swarm optimization method with local minimum prevention and adaptive weight strategy. The root mean square function with weight decay was optimized. The results showed that the identified simulation value was in good agreement with the measured value. The deviation between the simulation and the measured value of the opening time of the pressurization electric valve of the oxygen tank was less than 3%, and the deviation between the simulation value and the measured value of the temperature at the end of a flight of the gas bottle was only 2.4 K. If the identification results were applied to a similar newly developed pressurization system, the volume and weight of the gas bottle was reduced by 32 L and 11.6 kg compared with the design under the adiabatic assumption, which effectively saved cost caused by redundant design.
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图 2 增压输送系统热力学参数传递示意图（仅画出单个贮箱）
Figure 2. Thermodynamic parameter transfer in the pressurization system （only single propellant tank）
图 4 典型的增压过程中气瓶、贮箱压力变化
Figure 4. Pressure of gas bottle and tank in typical pressurization process
图 5 各因素各水平下气瓶末压平均值
Figure 5. Average pressure of gas bottle at the end of flight under different factors and levels
图 6 各因素各水平下氧箱电磁阀首次打开时间平均值
Figure 6. Average first opening time of oxide tank valve under different factors and levels
图 7 各因素各水平下燃箱电磁阀首次打开时间平均值
Figure 7. Average first opening time of fuel tank valve under different factors and levels
图 8 基于改进粒子群算法的系统参数辨识方法流程图
Figure 8. Schematic diagram of parameter identification method based on improved particle swarm optimization algorithm
图 9 飞行期间气瓶压力的仿真值和实测值对比
Figure 9. Comparison between simulation value and measured value of gas bottle pressure during the flight
图 10 贮箱压力的仿真值和实测值对比
Figure 10. Comparison between simulation value and measured value of ullage pressure
图 11 滑行期间气瓶压力的仿真值和实测值对比
Figure 11. Comparison between simulation value and measured value of gas bottle pressure during the taxing
图 12 某新研型号应用换热辨识结果后的增压参数变化
Figure 12. Changes in pressurization parameters of a new-developed pressurization system after applying identified heat transfer parameters
表 1 增压输送系统换热参数表
Table 1. Heat transfer parameters in the pressurization system
换热位置 换热项 待辨识参数 搜索范围 增压气瓶 气瓶综合传热系数$ {k_{\text{p}}} $ $ {k_{\text{p}}} $ 100～500 燃、氧路增压气体
与穿舱管壁燃、氧增压气体与管壁强制
表面传热系数$ {h}_{\text{rf}}、{h}_{\text{yf}} $$ {c_{\text{r}}} $、$ {c_{\text{y}}} $ 0.1～0.3 $ {n_{\text{r}}} $、$ {n_{\text{y}}} $ 0.6～0.9 燃、氧箱气枕
与贮箱壁燃、氧箱壁与气枕自然表面传热系数
$ {h}_{\text{rl}}、{h}_{\text{yl}} $ （平行于过载方向）$ {c_{\text{r}}} $、$ {c_{\text{y}}} $ 0.5～0.7 $ {n_{\text{r}}} $、$ {n_{\text{y}}} $ 0.15～0.35 燃、氧箱气枕
与推进剂液面燃、氧箱气枕与推进剂液面自然
表面传热系数$ {h}_{\text{rl}}、{h}_{\text{yl}} $ （垂直于过载方向）$ {c_{\text{r}}} $、$ {c_{\text{y}}} $ 0.5～0.7 $ {n_{\text{r}}} $、$ {n_{\text{y}}} $ 0.15～0.35 
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表 2 增压输送系统换热参数辨识结果
Table 2. Identification result of heat transfer parameters in the pressurization system
参数 数值 $ {k_{\text{p}}} $/（W/（m2·K）） 424.41 $ {c_{\text{r}}} $ 0.153 $ {n_{\text{r}}} $ 0.759 $ {c_{\text{y}}} $ 0.213 $ {n_{\text{y}}} $ 0.731
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