Model-based on-board turbofan thrust estimation

Henriksson, Mattias; Grönstedt, Tomas; Breitholtz, Claes

doi:10.1016/j.conengprac.2011.02.004

Cited by 37 publications

(13 citation statements)

References 8 publications

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“…Evaluation of the considered region (3) shows that the design point displacement on center part has small impacts on the profile of the polytrophic efficiency curves; however, there is a slight increase in efficiency for the selected required thrust, if the design point is slightly moved across the operation line. An interesting observation is that in this region we obtain a wide thrust range with high efficiency for all simulated points, according to Fig.…”

Section: Low-pressure System Optimizationmentioning

confidence: 99%

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Turbofan engine performance optimization based on aircraft cruise thrust level

Filho

Ribeiro

Lacava

2019

J Braz. Soc. Mech. Sci. Eng.

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The aim of this paper is to define a methodology to minimize the adjustment effort required to comply with aircraft design performance requirements, when commercial off-the-shelf turbofan engines are installed, which is a challenge to aircraft manufactures. In order to achieve an efficient operation, a reasonable proposal is to adapt the propulsive performance by turbofan engine optimization. This work is carried out according to the following steps: (i) creation of estimated performance curves for a gas turbine from limited data; (ii) analysis of the impacts on performance and propulsive integration, applying computer simulation of the most promising engine components configuration; and (iii) matching between the lowest specific fuel consumption and the net thrust required for the cruise flight phase of the aircraft. The technical feasibility and the possible predisposition of engine manufactures to perform the implementation were also considered as critical points in this procedure. As a final result, an evaluation that presents the most suitable turbofan engine component modifications proposal to comply with engine/aircraft performance integration to be applied in the conceptual design phase was obtained.

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Section: Low-pressure System Optimizationmentioning

confidence: 99%

“…Thus, it represents only a numerical distortion of the real phenomenon. Caution must be taken in interpreting these results, once it can be concluded that the approach of new scaled maps only has real physical sense if performed on points on an isocontour of the same efficiency as in the case of region (3).…”

Section: Low-pressure System Optimizationmentioning

confidence: 99%

Turbofan engine performance optimization based on aircraft cruise thrust level

Filho

Ribeiro

Lacava

2019

J Braz. Soc. Mech. Sci. Eng.

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“…to overcome this, model based control techniques are used where an on-board engine model is used to estimate the thrust produced [61] generally with the assistance of estimation filters [63]. However, if the linear engine model being used has the thrust as the output with an accurate relation between the thrust produced and the state vectors, then the thrust produced can be used in the feedback loop.…”

Section: Thrust Control Simulationsmentioning

confidence: 99%

“…Since a LTI engine model is used as the plant whose outputs readily includes thrust, thrust estimation techniques such as those proposed in references in [63,64,65] can be avoided since the estimated thrust is almost identical to the actual thrust produced. MPC being a model based technique uses a reference model whose output includes the thrust produced, which can be weighted accordingly.…”

Section: Thrust Control Simulationsmentioning

confidence: 99%

Fault Tolerant Model Predictive Control of a Turbofan Engine using C-MAPSS40k

Saluru

Yedavalli

2013

51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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Aircraft engine control is a crucial component for the safe and stable operation of gas turbine engines which are complex nonlinear systems. As engines have evolved to higher capabilities it is crucial to update the control strategy to ensure maximum functionality of the engine. Current industrial baseline controllers are based in the Proportional-Integral-Derivative (PID) control scheme along with individual limit controllers having critically damped responses housed in the min-max architecture. In light of the distributed engine control architecture that exploits digital electronics and hence higher on-board computational capabilities, the baseline controller is replaced by a Model Predictive Control (MPC) law with on-line optimization. MPC is a model based control technique that can handle complex constrained dynamics thus allowing the incorporation of component faults in the design process of the controller. Component faults occur during an engine's operation mainly due to fan blade-shroud rubbing, structural wear and tear and foreign object ingestion thus affecting the engine performance. Simulations on the Linear Time Invariant (LTI) as well as the nonlinear turbofan engine of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS40k) tool are carried out. In the presence of a component fault, active fault tolerant control using the multi-model MPC approach is applied by switching between the MPC blocks, each using its respective LTI reference model.The control of both

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“…Aero-engine mathematical models play important roles in the R&D stage, and they are used widely in performance simulation [1], [2], control and health management system design [3]- [6] and so on. Among many types of models, component level models (CLMs) are preferred because they are applicable to large envelopes and can calculate unmeasurable performance parameters [7]- [10].…”

Section: Introductionmentioning

confidence: 99%

Joint Steady State and Transient Performance Adaptation for Aero Engine Mathematical Model

Pang

Feng

et al. 2019

IEEE Access

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In the field of aero-engine control, it is valuable to build highly accurate component level models to meet the requirements of controller validation and model-based control. The accuracy of current performance map generation method is limited by the test data that always cannot cover the full envelope. The scaling-based performance map correction methods only focus on the adjustment of the steady-state performance. Therefore, a performance map segmentation-based joint steady-state and transient performance adaptation technique is proposed. Both the idle point and the design point are taken as precision references to scale the performance maps with large deviations. A scaling factor domain determination method is provided based on the characters of the speed lines. The performance map is first optimized with the steady state calculation based on the steady-state test data, and further optimized with the transient calculation based on the transient test data. Both the steady-state and transient performance adaptations are achieved by adjusting the performance maps. The proposed method was applied to a turbofan engine model. For continuous acceleration case, the average error is less than 1% at steady state points and less than 2% during transient operation. For large magnitude acceleration and rapid deceleration cases, the maximum errors for parameters around the idle point decrease by about one time (from 8.3% to 4.1%) and three and a half times (from 28% to 8%), respectively, by comparing with the model without transient performance adaptation. Thus, the effectiveness of the proposed method is demonstrated.

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Model-based on-board turbofan thrust estimation

Cited by 37 publications

References 8 publications

Turbofan engine performance optimization based on aircraft cruise thrust level

Turbofan engine performance optimization based on aircraft cruise thrust level

Fault Tolerant Model Predictive Control of a Turbofan Engine using C-MAPSS40k

Joint Steady State and Transient Performance Adaptation for Aero Engine Mathematical Model

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