基于蜂群算法的变循环发动机最小耗油率优化

性能寻优控制是使变循环发动机满足长寿命、低油耗和大推力需求的主要途径,也是实现飞机推进系统综合控制的关键技术.基于双外涵变循环发动机非线性数学模型,在满足发动机各部件物理约束条件和推力条件下,采用人工蜂群算法对变循环发动机典型亚声速巡航点(H=11 km,Ma=0.8)耗油率进行了寻优分析,找到了耗油率最小条件下发动机6个几何可调参数、5个发动机循环参数最优值.结果表明:亚声速巡航点的耗油率在优化后比优化前降低了4.5％,从而证实人工蜂群算法能够完成变循环发动机多维优化问题.

The minimum fuel consumption optimization of variable cycle engine based on artificial bee colony algorithm

Performance seeking control is the main way to meet the needs of keeping Variable Cycle Engine (VCE) long-life, low fuel consumption and large thrust, it is also the key technology to realize the Integrated Flight of Propulsion Control (IFPC). Based on Double Bypass Variable Cycle Engine (DBVCE) nonlinear mathematical model,by satisfying the physical constrains and thrust condition of engine,the Artificial Bee Colony(ABC) has been adopted to the fuel consumption optimization analysis of VCE typical subsonic cruise point (H=11 km, Ma=0.8). Six engine geometric variable parameters and five engine cycle parameters are found under the lowest specific fuel consumption condition. The results showed that the optimized fuel consumption is 4.5% lower than before, thus confirming that the problem of VCE multidimensional optimization can be solved by the ABC.