航空活塞式发动机空燃比实时控制算法  

Real time control algorithm of aviation piston engine air-fuel ratio

作　　者：黎艺华[1] 胡东宁[2] 胡春明[2] 刘娜[2] 

机构地区：[1]柳州职业技术学院,广西柳州545006 [2]天津大学天津内燃机研究所,天津300072

出　　处：《航空动力学报》2014年第5期1234-1241,共8页Journal of Aerospace Power

基　　金：天津市科技计划(13ZCZDGX04400);天津市科技计划项目科技支撑重点项目(12ZCZDGX03800);2013年度广西教育厅科研项目(2013LX2222)

摘　　要：采用比例-积分-微分神经网络(PIDNN)的控制算法,集合了传统PID控制及神经网络各自的优点,控制发动机在不同工况下的空燃比,实现发动机在不同工况间切换时,能够快速地控制空燃比至目标值.在AMESim软件中建立发动机模型,在MATLAB软件中建立PIDNN控制算法,进行模型在环仿真,仿真结果表明:在不同海拔高度下,PIDNN控制算法都能够准确地把空燃比控制在目标值,当发动机在不同工况间切换时,PIDNN能够在0.5s内把发动机空燃比控制至目标值,并且保证过量空气系数超调量在0.2之内,改善了发动机的动力性、经济性,提高了发动机的响应能力.Adopting the proportion-integration-differentiation neural network（PIDNN） control algorithm,the advantages of both the tradition PID and neural network were combined.It was used to control the engine air-fuel ratio under different operating conditions, and when the condition changed,it could control the air-fuel ratio to the target value.An engine model was built in software AMESim.The PIDNN control algorithm was built in software MATLAB.Through the model-in-the-loop,the simulation results show that：at different altitudes,the PIDNN could control the air-fuel ratio to the targets accurately.When the engine operating condition changes,the PIDNN could control the air-fuel ratio to the target within 0.5sand ensure the overshoot under 0.2,which results in the improvements of the engine dynamic property,fuel economy and rapid responsibility.

关 键 词：PID神经网络 活塞式发动机 过渡工况空燃比 模型在环仿真 仿真模型 

分 类 号：V233.7[航空宇航科学与技术—航空宇航推进理论与工程]