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摘要:
以小型涡扇发动机DGEN380燃油控制规律为研究目标，使用解析法基于MATLAB平台建立其整机部件级稳态及动态数学模型并进行仿真计算。在旋转部件建模过程中使用工具获取特性数据，并绘制可以即时显示当前工作点/线的部件特性图；在稳态仿真时使用Newton-Raphson法和遗传算法2种方法求解发动机工作方程组，并对二者进行评估对比，针对遗传算法在发动机模型求解过程中的局限性对一般基础模型进行优化改进；在动态仿真时，采用欧拉法计算微分项。基于模型分析发动机燃油控制规律，并以发动机高度特性为例进行仿真计算。试验结果表明：Newton-Raphson法具有高精度和高速度，改进模型后遗传算法具有更好的适应性，模型及燃油控制规律的仿真结果较好地符合试验数据和理论趋势，对比误差小于3%。
Abstract:Focusing on the fuel control law of the small size turbofan engine DGEN380, a steady and transient component-level mathematical model was developed and simulated on MATLAB platform with analytic method. A special tool was used for modeling the rotating parts in order to get the components characteristics and draw the maps which can show the current operating point/line. In the steady model simulation process, the Newton-Raphson method and genetic algorithm were evaluated and compared for solving the working equations of the engine. The basic model was modified to overcome the limitations of simulation in the genetic algorithm. The Euler method was used to calculate the differential term for the transient model simulation. Based on the model, the fuel control law was studied, and the altitude characteristic was described as an example. The experimental results show that the Newton-Raphson method has high accuracy and speed, while the genetic algorithm has better adaptability with the model modification. The simulation results of the model and the control law fit the test data and theory well, as the error is maintained below 3%.
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图 8 风扇和低压涡轮特性图上的加速线
Figure 8. Acceleration lines on fan and low pressure turbine characteristic maps
表 1 Newton-Raphson法、遗传算法仿真结果
Table 1. Simulation results of Newton-Raphson method and genetic algorithm
方法 nl/
(r·min-1)nh/
(r·min-1)πf πc πhpt πlpt Newton-Raphson法 42 798 50 653 1.16 4.56 2.28 1.93 遗传算法 42 919 50 712 1.17 4.56 2.30 1.92 实际值 42 830 50 687 1.16 4.57 2.27 1.93 
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