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针对变循环发动机非线性部件模型共同工作方程组求解时初值选取对收敛速度和精度的影响问题,提出一种基于量子粒子群算法(Quantum Particle Swarm,QPSO)与Broyden拟牛顿法混合的求解思路。对变循环发动机进行变几何特性分析以及BP神经网络下的外涵道稳态特性分析基础上,建立反映变几何特性以及模式切换等全状态部件模型。以该模型性能计算为基准,提出了一种基于量子粒子群优化的Broyden拟牛顿混合算法来达到发动机共同工作平衡要求,通过发散系数实现混合算法的切换,以改善单一Broyden拟牛顿法对初值选取的依赖性同时提高量子粒子群算法的求解效率。通过高阶非线性方程组的仿真验证了算法的有效性、求解效率以及精度。最后进行变循环航空发动机部件模型稳态、动态仿真计算,结果表明:与Gasturb性能计算结果对比可以看出发动机速度特性、高度特性等变化趋势与Gasturb基本一致,且误差均小于2%;基于量子粒子群优化的Broyden拟牛顿混合算法可有效快速的完成变循环发动机部件模型的求解;所建变循环发动机部件模型能够有效实现该新型发动机的性能模拟分析。
Aiming at the problem that the initial value selection affects the convergence speed and precision when the nonlinear equations model of a variable cycle engine is solved, a solution based on the hybrid of Quantum Particle Swarm (QPSO) and Broyden quasi-Newton method . Based on the analysis of variable geometry characteristics of variable cycle engine and the analysis of the steady state characteristics of the outer tunnel under BP neural network, a full state component model reflecting variable geometry characteristics and mode switching is established. Based on the model performance calculation, a Broyden quasi-Newton hybrid algorithm based on quantum particle swarm optimization is proposed to meet the requirements of engine common work balance. The hybrid algorithm is switched by the divergence coefficient to improve the performance of a single Broyden quasi-Newton method for initial value The selected dependencies also improve the efficiency of quantum particle swarm optimization. The effectiveness of the algorithm, efficiency and accuracy of the algorithm are verified by the simulation of higher-order nonlinear equations. Finally, the steady-state and dynamic simulation of variable cycle aeroengine component model are carried out. The results show that compared with the results of Gasturb performance calculation, it can be seen that the variation trend of engine speed characteristics and height characteristics are basically the same with Gasturb, and the errors are less than 2% Particle swarm optimization based on the Newton-Bleyton hybrid algorithm can effectively and quickly complete the variable cycle engine component model solution; the modified cycle engine component model can effectively achieve the performance of the new engine simulation analysis.