To design the optimum acceleration control schedule for the Adaptive Cycle Engine(ACE)in the full flight envelope,this paper establishes a direct simulation model of the ACE transient state.In this model,geometric par...To design the optimum acceleration control schedule for the Adaptive Cycle Engine(ACE)in the full flight envelope,this paper establishes a direct simulation model of the ACE transient state.In this model,geometric parameters are used to replace the component state parameters.The corresponding relationship between geometric parameters and component state parameters is determined by sensitivity analysis.The geometric variables are controlled when the geometric adjustment speed exceeds the limit,and at the same time the corresponding component state parameters are iterated.The gradient optimization algorism is used to optimize the ground acceleration process of ACE,and the control schedule in terms of operating point of compression components and corrected acceleration rate is used as the full-envelope acceleration control schedule based on the similarity principle.The acceleration control schedules of the triple-bypass mode and the double-bypass mode are designed in this paper.The acceleration processes under various flight conditions are simulated using the acceleration control schedules.Compared with the acceleration process with the linear geometric adjustment schedule,the acceleration performance of ACE is improved by the acceleration control schedule,with the impulse of the acceleration process of the triple-bypass mode being increased by 8.7%-12.3% and the impulse of the double-bypass mode acceleration process being increased by 11.8%-14.1%.展开更多
In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support ve...In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.展开更多
As a novel aero-engine concept,adaptive cycle aero-engines（ACEs） are attracting wide attention in the international aviation industry due to their potential superior task adaptability along a wide flight regime.Howe...As a novel aero-engine concept,adaptive cycle aero-engines（ACEs） are attracting wide attention in the international aviation industry due to their potential superior task adaptability along a wide flight regime.However,this superior task adaptability can only be demonstrated through proper combined engine control schedule design.It has resulted in an urgent need to investigate the effect of each variable geometry modulation on engine performance and stability.Thus,the aim of this paper is to predict and discuss the effect of each variable geometry modulation on the matching relationship between engine components as well as the overall engine performance at different operating modes,on the basis of a newly developed nonlinear component-based ACE performance model.Results show that at all four working modes,turning down the high pressure compressor variable stator vane,the low pressure turbine variable nozzle,the nozzle throat area,and turning up the core-driven fan stage variable stator vane,the high pressure turbine variable nozzle can increase the thrust at the expense of a higher high pressure turbine inlet total temperature.However,the influences of these adjustments on the trends of various engine components＇ working points and working lines as well as the ratio of the rotation speed difference are different from each other.The above results provide valuable guidance and advice for engine combined control schedule design.展开更多
Front Variable Area Bypass Injector(Front-VABI) is a component of the Adaptive Cycle Engine(ACE) with important variable-cycle features. The performance of Front-VABI has a direct impact on the performance and stabili...Front Variable Area Bypass Injector(Front-VABI) is a component of the Adaptive Cycle Engine(ACE) with important variable-cycle features. The performance of Front-VABI has a direct impact on the performance and stability of ACE, but the current ACE performance model uses approximate models for Front-VABI performance calculation. In this work, a multi-fidelity simulation based on a de-coupled method is developed which delivers a more accurate calculation of the Front-VABI performance based on Computational Fluid Dynamics(CFD) simulation. This simulation method proposes a form of Front-VABI characteristic and its matching calculation method between it and the ACE performance model, constructs a coupling method between the(2-D) Front-VABI model and the(0-D) ACE performance model. The result shows, when ACE works in triple bypass mode, the approximate model cannot account for the effect of FrontVABI pressure loss on Core Driven Fan Stage(CDFS) design pressure ratio, and the calculated error of high-pressure turbine inlet total temperature is more than 40 K in mode transition condition(the transition operating condition between triple bypass mode and double bypass mode). In double bypass mode, the approximate model can better simulate the performance of FrontVABI by considering the local loss of area expansion. This method can be applied to the performance-optimized design of Front-VABI and the ACE control law design during mode transition.展开更多
The alternative working modes and flexible working states are the outstanding features of an adaptive cycle engine, with a proper control schedule design being the only way to exploit the performance of such an engine...The alternative working modes and flexible working states are the outstanding features of an adaptive cycle engine, with a proper control schedule design being the only way to exploit the performance of such an engine. However, unreasonable design in the control schedule causes not only performance deterioration but also serious aerodynamic stability problems. Thus, in this work,a hybrid optimization method that automatically chooses the working modes and identifies the optimal and smooth control schedules is proposed, by combining the differential evolution algorithm and the Latin hypercube sampling method. The control schedule architecture does not only optimize the engine steady-state performance under different working modes but also solves the control-schedule discontinuity problem, especially during mode transition. The optimal control schedules are continuous and almost monotonic, and hence are strongly suitable for a control system, and are designed for two different working conditions, i.e., supersonic and subsonic throttling,which proves that the proposed hybrid method applies to various working conditions. The evaluation demonstrates that the proposed control method optimizes the engine performance, the surge margin of the compression components, and the range of the thrust during throttling.展开更多
In conjunction with the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA),the Department of Electrical and Computer Engineering at the University of Massachusetts Amherst invi...In conjunction with the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA),the Department of Electrical and Computer Engineering at the University of Massachusetts Amherst invites applications for a tenure-track position in Integrative Systems Engineering(ISE) at the Assistant Professor level to begin September 2009.展开更多
Accurate engine performance models are important for model-based performance evaluation of aero engine.The accuracy of the model often depends on engine component maps,so there is a need for a method that can accurate...Accurate engine performance models are important for model-based performance evaluation of aero engine.The accuracy of the model often depends on engine component maps,so there is a need for a method that can accurately correct the component maps of the model over a wide range.In this paper,a new method for modifying component maps is proposed,this method combines the correction of the scaling factors with the solution process of the off-design working point,and uses the adjustment of the variable geometric parameters of the engine to change the position of the working line,in order to obtain more correction results and guarantee high accuracy in a wider range.The method is validated by taking the main fan of the Adaptive Cycle Engine(ACE),an ideal power unit for a new generation of multi-purpose and ultra-wide working range aircraft,as an example.The results show that the maximum error between the corrected component maps and the target maps is less than 1%.New possibility for more precise component maps can be realized in this paper.展开更多
基金co-supported by the National Science and Technology Major Project,China(No.J2019-I-0015-0014)the National Natural Science Foundation of China(No.52372397).
文摘To design the optimum acceleration control schedule for the Adaptive Cycle Engine(ACE)in the full flight envelope,this paper establishes a direct simulation model of the ACE transient state.In this model,geometric parameters are used to replace the component state parameters.The corresponding relationship between geometric parameters and component state parameters is determined by sensitivity analysis.The geometric variables are controlled when the geometric adjustment speed exceeds the limit,and at the same time the corresponding component state parameters are iterated.The gradient optimization algorism is used to optimize the ground acceleration process of ACE,and the control schedule in terms of operating point of compression components and corrected acceleration rate is used as the full-envelope acceleration control schedule based on the similarity principle.The acceleration control schedules of the triple-bypass mode and the double-bypass mode are designed in this paper.The acceleration processes under various flight conditions are simulated using the acceleration control schedules.Compared with the acceleration process with the linear geometric adjustment schedule,the acceleration performance of ACE is improved by the acceleration control schedule,with the impulse of the acceleration process of the triple-bypass mode being increased by 8.7%-12.3% and the impulse of the double-bypass mode acceleration process being increased by 11.8%-14.1%.
基金co-supported by Aeronautical Science Foundation of China (No. 2010ZB52011)Funding of Jiangsu Innovation Program for Graduate Education (No.CXLX11_0213)
文摘In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.
基金supported by the National Natural Science Foundation of China(No.51206005)Collaborative Innovation Center of Advanced Aero-Engine of China
文摘As a novel aero-engine concept,adaptive cycle aero-engines（ACEs） are attracting wide attention in the international aviation industry due to their potential superior task adaptability along a wide flight regime.However,this superior task adaptability can only be demonstrated through proper combined engine control schedule design.It has resulted in an urgent need to investigate the effect of each variable geometry modulation on engine performance and stability.Thus,the aim of this paper is to predict and discuss the effect of each variable geometry modulation on the matching relationship between engine components as well as the overall engine performance at different operating modes,on the basis of a newly developed nonlinear component-based ACE performance model.Results show that at all four working modes,turning down the high pressure compressor variable stator vane,the low pressure turbine variable nozzle,the nozzle throat area,and turning up the core-driven fan stage variable stator vane,the high pressure turbine variable nozzle can increase the thrust at the expense of a higher high pressure turbine inlet total temperature.However,the influences of these adjustments on the trends of various engine components＇ working points and working lines as well as the ratio of the rotation speed difference are different from each other.The above results provide valuable guidance and advice for engine combined control schedule design.
基金funded by National Natural Science Foundation of China(Nos.51776010 and 91860205)National Science and Technology Major Project,China(No.2017-I0001-0001)。
文摘Front Variable Area Bypass Injector(Front-VABI) is a component of the Adaptive Cycle Engine(ACE) with important variable-cycle features. The performance of Front-VABI has a direct impact on the performance and stability of ACE, but the current ACE performance model uses approximate models for Front-VABI performance calculation. In this work, a multi-fidelity simulation based on a de-coupled method is developed which delivers a more accurate calculation of the Front-VABI performance based on Computational Fluid Dynamics(CFD) simulation. This simulation method proposes a form of Front-VABI characteristic and its matching calculation method between it and the ACE performance model, constructs a coupling method between the(2-D) Front-VABI model and the(0-D) ACE performance model. The result shows, when ACE works in triple bypass mode, the approximate model cannot account for the effect of FrontVABI pressure loss on Core Driven Fan Stage(CDFS) design pressure ratio, and the calculated error of high-pressure turbine inlet total temperature is more than 40 K in mode transition condition(the transition operating condition between triple bypass mode and double bypass mode). In double bypass mode, the approximate model can better simulate the performance of FrontVABI by considering the local loss of area expansion. This method can be applied to the performance-optimized design of Front-VABI and the ACE control law design during mode transition.
基金funded by National Nature Science Foundation of China(Nos.51776010 and 91860205)supported by the Academic Excellence Foundation of BUAA for PhD Students,China。
文摘The alternative working modes and flexible working states are the outstanding features of an adaptive cycle engine, with a proper control schedule design being the only way to exploit the performance of such an engine. However, unreasonable design in the control schedule causes not only performance deterioration but also serious aerodynamic stability problems. Thus, in this work,a hybrid optimization method that automatically chooses the working modes and identifies the optimal and smooth control schedules is proposed, by combining the differential evolution algorithm and the Latin hypercube sampling method. The control schedule architecture does not only optimize the engine steady-state performance under different working modes but also solves the control-schedule discontinuity problem, especially during mode transition. The optimal control schedules are continuous and almost monotonic, and hence are strongly suitable for a control system, and are designed for two different working conditions, i.e., supersonic and subsonic throttling,which proves that the proposed hybrid method applies to various working conditions. The evaluation demonstrates that the proposed control method optimizes the engine performance, the surge margin of the compression components, and the range of the thrust during throttling.
文摘In conjunction with the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA),the Department of Electrical and Computer Engineering at the University of Massachusetts Amherst invites applications for a tenure-track position in Integrative Systems Engineering(ISE) at the Assistant Professor level to begin September 2009.
基金funded by National Nature Science Foundation of China(NSFC)(Nos.51776010,and 91860205)the support from Collaborative Innovation Center of Advanced Aero-Engine,china。
文摘Accurate engine performance models are important for model-based performance evaluation of aero engine.The accuracy of the model often depends on engine component maps,so there is a need for a method that can accurately correct the component maps of the model over a wide range.In this paper,a new method for modifying component maps is proposed,this method combines the correction of the scaling factors with the solution process of the off-design working point,and uses the adjustment of the variable geometric parameters of the engine to change the position of the working line,in order to obtain more correction results and guarantee high accuracy in a wider range.The method is validated by taking the main fan of the Adaptive Cycle Engine(ACE),an ideal power unit for a new generation of multi-purpose and ultra-wide working range aircraft,as an example.The results show that the maximum error between the corrected component maps and the target maps is less than 1%.New possibility for more precise component maps can be realized in this paper.
