Load sharing behavior is very important for power-split gearing system, star gearing reducer as a new type and special transmission system can be used in many industry fields. However, there is few literature regardin...Load sharing behavior is very important for power-split gearing system, star gearing reducer as a new type and special transmission system can be used in many industry fields. However, there is few literature regarding the key multiple-split load sharing issue in main gearbox used in new type geared turbofan engine. Further mechanism anal- ysis are made on load sharing behavior among star gears of star gearing reducer for geared turbofan engine. Compre- hensive meshing error analysis are conducted on eccentricity error, gear thickness error, base pitch error, assembly error, and bearing error of star gearing reducer respectively. Floating meshing error resulting from meshing clearance variation caused by the simultaneous floating of sun gear and annular gear are taken into account. A refined mathematical model for load sharing coefficient calculation is established in consideration of different meshing stiffness and support- ing stiffness for components. The regular curves of load sharing coefficient under the influence of interactions, single action and single variation of various component errors are obtained. The accurate sensitivity of load sharing coefficienttoward different errors is mastered. The load sharing coef- ficient of star gearing reducer is 1.033 and the maximum meshing force in gear tooth is about 3010 N. This paper provides scientific theory evidences for optimal parameter design and proper tolerance distribution in advanced devel- opment and manufacturing process, so as to achieve optimal effects in economy and technology.展开更多
A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performan...A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications.展开更多
In order to study component matching which exists in off-design situation at the initial design stage of turbine engine,by establishing performance analysis model of low bypass ratio mixed flow turbofan engine and com...In order to study component matching which exists in off-design situation at the initial design stage of turbine engine,by establishing performance analysis model of low bypass ratio mixed flow turbofan engine and components characteristic data,and by applying Newton-Raphson method to solve the nonlinear equations of offdesign points in flying envelop,the factors which affect matching between engine components are studied.The results show that low pressure turbine(LPT)must not operate in a critical condition,and the partial derivative(slope)of pressure ratio to similitude mass flow ratio of working point in LPT characteristic map affects the stability of engine.The smaller the slope is,the more stable the engine is.In addition,the engine is more stable when the fan characteristic map is steep.展开更多
Aircraft engine design is a complicated process,as it involves huge number of components.The design process begins with parametric cycle analysis.It is crucial to determine the optimum values of the cycle parameters t...Aircraft engine design is a complicated process,as it involves huge number of components.The design process begins with parametric cycle analysis.It is crucial to determine the optimum values of the cycle parameters that would give a robust design in the early phase of engine development,to shorten the design cycle for cost saving and man-hour reduction.To obtain a robust solution,optimisation program is often being executed more than once,especially in Reliability Based Design Optimisations(RBDO)with Monte-Carlo Simulation(MCS)scheme for complex systems which require thousands to millions of optimisation loops to be executed.This paper presents a fast heuristic technique to optimise the thermodynamic cycle of two-spool separated flow turbofan engines based on energy and probability of failure criteria based on Luus-Jaakola algorithm(LJ).A computer program called Turbo Jet Engine Optimiser v2.0(TJEO-2.0)has been developed to perform the optimisation calculation.The program is made up of inner and outer loops,where LJ is used in the outer loop to determine the design variables while parametric cycle analysis of the engine is done in the inner loop to determine the engine performance.Latin-Hypercube-Sampling(LHS)technique is used to sample the design and model variations for uncertainty analysis.The results show that optimisation without reliability criteria may lead to high probability of failure of more than 11%on average.The thrust obtained with uncertainty quantification was about 25%higher than the one without uncertainty quantification,at the expense of less than 3%of fuel consumption.The proposed algorithm can solve the turbofan RBDO problem within 3 min.展开更多
In recent years, the cost of engines has become increasingly important to engine manufacturers, who are consistently faced with major problems on how to reduce cost to a minimum. Cost has become a decisive factor for ...In recent years, the cost of engines has become increasingly important to engine manufacturers, who are consistently faced with major problems on how to reduce cost to a minimum. Cost has become a decisive factor for aircraft design. To control the continual rapid increased cost, engine cost prediction is indispensable early in the design phase. But the cost data of an aircraft engine is small; we introduce the Robust Partial Least Squares Method in solving this problem, and reducing or removing the effect of outlying data points, which is different from the Classical PLS. We use the MATLAB software doing several simulations; results and analysis of a real turbofan engine data set show the effectiveness and robustness of the Robust PLS method. The Robust PLS method can effectively be used to estimate Turbofan Engine cost with reasonable accuracy.展开更多
Focusing on the internal flow and heat transfer analysis,a platform for the performance evaluation of the Secondary Air System(SAS)is developed.A multi-fidelity modeling technique has been developed in a turbofan engi...Focusing on the internal flow and heat transfer analysis,a platform for the performance evaluation of the Secondary Air System(SAS)is developed.A multi-fidelity modeling technique has been developed in a turbofan engine model under different flight conditions.A turbine blade cool-ing model which integrates external heat transfer calculations and coolant side modeling with com-mon components is proposed.In addition,the Computational Fluid Dynamics(CFD)method is selected to capture the complex flow field structure in the preswirl system.The validity of the SAS models is compared with publicly available data.An elaborately designed cooling system for the AGTF30 engine is analyzed through three main branches.It is found that the 1D-3D mod-eling technique can provide more accurate predictions of the SAS for the AGTF30 engine.The results demonstrate the versatility and flexibility of the SAS models,thereby indicating the capacity of meeting most of the demands of flow and thermal analysis of the SAS.展开更多
Gas turbine engines must be operated by means of control,and how to achieve multivariable control decoupling with aero-engine control constraints is an open thorny issue attracting increasingly more attention.The pape...Gas turbine engines must be operated by means of control,and how to achieve multivariable control decoupling with aero-engine control constraints is an open thorny issue attracting increasingly more attention.The paper considers the multivariable decoupling problems of aero-engines by using a compound controller,which originates from the fact that it is impossible to eliminate all the nonlinear dynamics of system to obtain desired constant linear closed-loop system by using full actuated control because of modeling errors and some physical constraints.Two controllers are involved in the compound controller.One is a fully actuated controller and the other is classical feedback controller.In order to use fully actuated control and maintain the accuracy of engine model,a full state scheduling linear parameter-varying(LPV)modeling method is proposed based on fuzzy neural network weights.For a general input matrix of the system,its generalized inverse is applied to design fully actuated controller to result in a pseudolinear system.Combined with a feedback controller and control limiter,the control synthesis is achieved.The simulation shows that the proposed method is possessed of a better decoupling and tracking effect compared with traditional control approach.展开更多
Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which som...Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.展开更多
The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The ...The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.展开更多
This paper is concerned with identifying a Takagi-Sugeno(TS) fuzzy model for turbofan aero-engines working under the maximum power status(non-afterburning). To establish the fuzzy system, theoretical contributions...This paper is concerned with identifying a Takagi-Sugeno(TS) fuzzy model for turbofan aero-engines working under the maximum power status(non-afterburning). To establish the fuzzy system, theoretical contributions are made as follows. First, by fixing antecedent parameters, the estimation of consequent parameters in state-space representations is formulated as minimizing a quadratic cost function. Second, to avoid obtaining unstable identified models, a new theorem is proposed to transform the prior-knowledge of stability into constraints. Then based on the aforementioned work, the identification problem is synthesized as a constrained quadratic optimization.By solving the constrained optimization, a TS fuzzy system is identified with guaranteed stability.Finally, the proposed method is applied to the turbofan aero-engine using simulation data generated from an aerothermodynamics component-level model. Results show the identified fuzzy model achieves a high fitting accuracy while stabilities of the overall fuzzy system and all its local models are also guaranteed.展开更多
基金Supported by National Key Technology R&D Program(No.2014BAF08B01)Natural Science Foundation of Tianjin(Grant No.17JCQNJC04300)
文摘Load sharing behavior is very important for power-split gearing system, star gearing reducer as a new type and special transmission system can be used in many industry fields. However, there is few literature regarding the key multiple-split load sharing issue in main gearbox used in new type geared turbofan engine. Further mechanism anal- ysis are made on load sharing behavior among star gears of star gearing reducer for geared turbofan engine. Compre- hensive meshing error analysis are conducted on eccentricity error, gear thickness error, base pitch error, assembly error, and bearing error of star gearing reducer respectively. Floating meshing error resulting from meshing clearance variation caused by the simultaneous floating of sun gear and annular gear are taken into account. A refined mathematical model for load sharing coefficient calculation is established in consideration of different meshing stiffness and support- ing stiffness for components. The regular curves of load sharing coefficient under the influence of interactions, single action and single variation of various component errors are obtained. The accurate sensitivity of load sharing coefficienttoward different errors is mastered. The load sharing coef- ficient of star gearing reducer is 1.033 and the maximum meshing force in gear tooth is about 3010 N. This paper provides scientific theory evidences for optimal parameter design and proper tolerance distribution in advanced devel- opment and manufacturing process, so as to achieve optimal effects in economy and technology.
文摘A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications.
基金supported in part by the Fundamental Research Funds for the Central Universities(No.NZ2016103)
文摘In order to study component matching which exists in off-design situation at the initial design stage of turbine engine,by establishing performance analysis model of low bypass ratio mixed flow turbofan engine and components characteristic data,and by applying Newton-Raphson method to solve the nonlinear equations of offdesign points in flying envelop,the factors which affect matching between engine components are studied.The results show that low pressure turbine(LPT)must not operate in a critical condition,and the partial derivative(slope)of pressure ratio to similitude mass flow ratio of working point in LPT characteristic map affects the stability of engine.The smaller the slope is,the more stable the engine is.In addition,the engine is more stable when the fan characteristic map is steep.
基金The project is funded by the Ministry of Higher Education Malaysia,under the Fundamental Research Grant Scheme(FRGS Grant No.FRGS/1/2017/TK07/SEGI/02/1).
文摘Aircraft engine design is a complicated process,as it involves huge number of components.The design process begins with parametric cycle analysis.It is crucial to determine the optimum values of the cycle parameters that would give a robust design in the early phase of engine development,to shorten the design cycle for cost saving and man-hour reduction.To obtain a robust solution,optimisation program is often being executed more than once,especially in Reliability Based Design Optimisations(RBDO)with Monte-Carlo Simulation(MCS)scheme for complex systems which require thousands to millions of optimisation loops to be executed.This paper presents a fast heuristic technique to optimise the thermodynamic cycle of two-spool separated flow turbofan engines based on energy and probability of failure criteria based on Luus-Jaakola algorithm(LJ).A computer program called Turbo Jet Engine Optimiser v2.0(TJEO-2.0)has been developed to perform the optimisation calculation.The program is made up of inner and outer loops,where LJ is used in the outer loop to determine the design variables while parametric cycle analysis of the engine is done in the inner loop to determine the engine performance.Latin-Hypercube-Sampling(LHS)technique is used to sample the design and model variations for uncertainty analysis.The results show that optimisation without reliability criteria may lead to high probability of failure of more than 11%on average.The thrust obtained with uncertainty quantification was about 25%higher than the one without uncertainty quantification,at the expense of less than 3%of fuel consumption.The proposed algorithm can solve the turbofan RBDO problem within 3 min.
文摘In recent years, the cost of engines has become increasingly important to engine manufacturers, who are consistently faced with major problems on how to reduce cost to a minimum. Cost has become a decisive factor for aircraft design. To control the continual rapid increased cost, engine cost prediction is indispensable early in the design phase. But the cost data of an aircraft engine is small; we introduce the Robust Partial Least Squares Method in solving this problem, and reducing or removing the effect of outlying data points, which is different from the Classical PLS. We use the MATLAB software doing several simulations; results and analysis of a real turbofan engine data set show the effectiveness and robustness of the Robust PLS method. The Robust PLS method can effectively be used to estimate Turbofan Engine cost with reasonable accuracy.
基金financially supported by Sichuan Gas Turbine Establishment, Aero Engine Corporation of China
文摘Focusing on the internal flow and heat transfer analysis,a platform for the performance evaluation of the Secondary Air System(SAS)is developed.A multi-fidelity modeling technique has been developed in a turbofan engine model under different flight conditions.A turbine blade cool-ing model which integrates external heat transfer calculations and coolant side modeling with com-mon components is proposed.In addition,the Computational Fluid Dynamics(CFD)method is selected to capture the complex flow field structure in the preswirl system.The validity of the SAS models is compared with publicly available data.An elaborately designed cooling system for the AGTF30 engine is analyzed through three main branches.It is found that the 1D-3D mod-eling technique can provide more accurate predictions of the SAS for the AGTF30 engine.The results demonstrate the versatility and flexibility of the SAS models,thereby indicating the capacity of meeting most of the demands of flow and thermal analysis of the SAS.
基金supported by National Science and Technology Major Project(2017-V-0010-0060,2017-V-0013-0065,J2019-V-0010-0104),Original exploration project of National Natural Science Foundation of China(62250056)Major Basic Research of Natural Science Foundation of Shandong Province(ZR2021ZD14)+2 种基金High-Level Talent Team Project of Qingdao West Coast New Area(RCTD-JC-2019-05)Key Research and Development Program of Shandong Province(2020CXGC01208)National Natural Science Foundation of China(51506176).
文摘Gas turbine engines must be operated by means of control,and how to achieve multivariable control decoupling with aero-engine control constraints is an open thorny issue attracting increasingly more attention.The paper considers the multivariable decoupling problems of aero-engines by using a compound controller,which originates from the fact that it is impossible to eliminate all the nonlinear dynamics of system to obtain desired constant linear closed-loop system by using full actuated control because of modeling errors and some physical constraints.Two controllers are involved in the compound controller.One is a fully actuated controller and the other is classical feedback controller.In order to use fully actuated control and maintain the accuracy of engine model,a full state scheduling linear parameter-varying(LPV)modeling method is proposed based on fuzzy neural network weights.For a general input matrix of the system,its generalized inverse is applied to design fully actuated controller to result in a pseudolinear system.Combined with a feedback controller and control limiter,the control synthesis is achieved.The simulation shows that the proposed method is possessed of a better decoupling and tracking effect compared with traditional control approach.
基金supported by the Fundamental Research Funds for the Central Universities(NO.NS2018018)
文摘Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.
基金supported by the National Natural Science Foundation of China(No.51766011)the Aeronautical Science Foundation of China(No.2014ZB56002)
文摘The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.
文摘This paper is concerned with identifying a Takagi-Sugeno(TS) fuzzy model for turbofan aero-engines working under the maximum power status(non-afterburning). To establish the fuzzy system, theoretical contributions are made as follows. First, by fixing antecedent parameters, the estimation of consequent parameters in state-space representations is formulated as minimizing a quadratic cost function. Second, to avoid obtaining unstable identified models, a new theorem is proposed to transform the prior-knowledge of stability into constraints. Then based on the aforementioned work, the identification problem is synthesized as a constrained quadratic optimization.By solving the constrained optimization, a TS fuzzy system is identified with guaranteed stability.Finally, the proposed method is applied to the turbofan aero-engine using simulation data generated from an aerothermodynamics component-level model. Results show the identified fuzzy model achieves a high fitting accuracy while stabilities of the overall fuzzy system and all its local models are also guaranteed.