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摘要:
燃油热管理系统设计随着运载器多电化与机载高能电子设备的发展已经得到高度重视，其中燃油的热承载能力是最关键因素。针对喷气推进式高速运载器，提出了一种大范围、多任务的燃油热管理系统多目标优化配置方法，其以热沉利用率最高和燃油质量代偿损失最小为目标函数，以循环回路的燃油最大质量流量、冷却水携带量和机载热负荷发热量为优化变量，采用改进的遗传算法NSGA-Ⅱ，在不同飞行任务规划下进行双目标优化设计，所获得的目标函数Pareto最优解集，满足预期的燃油热管理系统模式选择原则，且通过分析优化变量与优化目标间的相关性，可以量化燃油热管理系统优化配置准则与可达到的最小燃油质量代偿损失，可应用于支持多热沉重构的机载高效燃油热管理系统。
Abstract:With the rapid development of multi-electrification of aircraft and airborne high-energy electronic equipment, the design of fuel heat management system has been paid great attention to. The most critical factor is the thermal load capacity of fuel. For jet propulsion high-speed aircraft, this paper presents a multi-objective optimal allocation method for a large-scale and multi-task fuel heat management system. The thermal carrying capacity of fuel decreases with the increase of flight time, due to the dual effect of airborne thermal load and aerodynamic heating. In this paper, the improved genetic algorithm NSGA-Ⅱ is used to optimize the design of two targets under different flight mission planning. The objective function is heat sink efficiency and fuel compensation loss. The optimization variables are the maximum flow rate of the fuel cycle, the consumption of coolant and the heat load on board. The objective function Pareto optimal solution set is obtained to meet the expected model selection principle of the fuel heat management system. By analyzing the correlation between the optimized variable and the optimization target, the optimization configuration criterion and the minimum fuel compensation loss can be quantified, and the airborne efficient heat management system supporting the multiple heat sink reconstruction is designed.
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Key words:
- high-speed aircraft /
- heat management system /
- fuel heat sink /
- flight time length /
- expendable coolant
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图 1 高速运载器燃油热管理系统架构
Figure 1. Architecture of fuel heat management system for high-speed aircraft
图 2 多目标优化配置可行解的目标值空间
Figure 2. Target value space of optimal configuration of feasible solutions of multiple target
图 3 燃油最大质量流量与优化目标之间的关系
Figure 3. Relationship between maximum mass flow rate of fuel and optimization objective
图 4 冷却水的携带量与优化目标之间的关系
Figure 4. Relationship between cooling water carrying capacity and optimization objective
图 5 机载热负荷发热量与优化目标之间的关系
Figure 5. Relationship between airborne heat load and optimization objective
图 6 燃油热管理系统参数优化配置方案
Figure 6. Parameter optimal configuration scheme of fuel heat management system
表 1 燃油热管理系统多目标优化配置仿真参数
Table 1. Simulation parameters for multi-objective optimal configuration of fuel heat management system
参数 数值 仿真时间τdesign/s 4 200 仿真步长Δτ/s 2 升阻比K 4.62 油箱侧壁面积A1/m2 94.5 油箱底面面积A2/m2 46.25 燃油泵增压ΔP/Pa 1 000 油箱壁面发射率ε 0.9 油箱外壁面厚度δ3/mm 1.2 燃油初始质量m0/kg 23 560 燃油初始温度T0/℃ 20 冷却水初始温度Tw, 0/℃ 20 冷却水饱和温度Tsat/℃ 60 燃油泵效率η 0.8 油箱内壁面厚度δ1/mm 1.2 
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表 2 NSGA-Ⅱ算法参数设定
Table 2. NSGA-Ⅱ algorithm parameter setting
参数 设定值 种群个数 10 种群代数 100 交叉概率 0.9 实数向量变异概率 1.0 二进制字符串变异概率 1.0 实数交叉分配指数 20 实数变异分配指数 20
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