Real-time optimization control of variable rotor speed based on Helicopter/ turboshaft engine on-board composite system

Song, Jie; Wang, Yong; Ji, Chuang; Zhang, Haibo

doi:10.1016/j.energy.2024.131701

Energy

2024

DOI: 10.1016/j.energy.2024.131701

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Real-time optimization control of variable rotor speed based on Helicopter/ turboshaft engine on-board composite system

Jie Song,

Yong Wang,

Chuang Ji

et al.

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2024

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Cited by 3 publications

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Speed controller design for turboshaft engine using a high-fidelity AeroThermal model

Yazar

2024

International Journal of Turbo &Amp; Jet-Engines

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One of the main objectives of this research is to construct a high-fidelity aerothermal model for controlling the turboshaft engine power turbine rotational speed. Firstly, a high-fidelity aerothermal model of General Electric T700 is formed. The turboshaft engine aerothermal model is simulated and compared to engine design point data on MATLAB/Simulink environment. Thermodynamic equations and some algebraic equations are used. In predicting compressor mass flow rate, the adaptive neuro-fuzzy inference system method is preferred. A propeller model is also added to the turbo shaft engine aerothermal model and to keep the power turbine rotational speed at a constant value, a Proportional Integral Derivative controller is designed and applied. Open-loop and closed-loop simulations are conducted and successful outcomes are achieved. Results indicate that the differences between simulation and actual engine data are within acceptable limits. The suggested model can be readily updated and expanded to control additional parameters of the engine. PACS 2010 Classification: Control theory in mathematical physics, 02.30. Yy, Computer modeling and simulation, 07.05.Tp, 05.70.Ce Thermodynamic functions and equations of state.

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Speed controller design for turboshaft engine using a high-fidelity AeroThermal model

Yazar

2024

International Journal of Turbo &Amp; Jet-Engines

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An Innovative Applied Control System of Helicopter Turboshaft Engines Based on Neuro-Fuzzy Networks

Vladov,

Lytvynov,

Vysotska

et al. 2024

ASI

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This study focuses on helicopter turboshaft engine innovative fault-tolerant fuzzy automatic control system development to enhance safety and efficiency in various flight modes. Unlike traditional systems, the proposed automatic control system incorporates a fuzzy regulator with an adaptive control mechanism, allowing for dynamic fuel flow and blade pitch angle adjustment based on changing conditions. The scientific novelty lies in the helicopter turboshaft engines distinguishing separate models and the fuel metering unit, significantly improving control accuracy and adaptability to current flight conditions. During experimental research on the TV3-117 engine installed on the Mi-8MTV helicopter, a parametric modeling system was developed to simulate engine operation in real time and interact with higher-level systems. Innovation is evident in the creation of the failure model that accounts for dynamic changes and probabilistic characteristics, enabling the prediction of failures and minimizing their impact on the system. The results demonstrate high effectiveness for the proposed model, achieving an accuracy of 99.455%, while minimizing the loss function, confirming its reliability for practical application in dynamic flight conditions.

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Method for Helicopter Turboshaft Engines Controlling Energy Characteristics Through Regulating Free Turbine Rotor Speed and Fuel Consumption Based on Neural Networks

Vladov,

Bulakh,

Czyżewski

et al. 2024

Energies

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This research is devoted to the development of a method for helicopter turboshaft engine energy characteristics control by regulating the free turbine rotor speed and fuel consumption using neural network technologies. A mathematical model was created that links the main rotor and free turbine rotor speed parameters, based on which a relation with the engine output power was established. In this research, a differential equation was obtained that links fuel consumption, output power, and rotor speed, which makes it possible to monitor engine dynamics in various operating modes. A fuel consumption controller was developed based on a neuro-fuzzy network that processes input data, including the desired and current rotor speed, which allows real-time adjustments to improve the operational efficiency. In the research, based on the flight data analysis obtained during the Mi-8MTV helicopter with a TV3-117 turboshaft engine flight test, improved signal processing quality was obtained due to time sampling and adaptive quantisation methods (this is confirmed by assessing the homogeneity and representativeness of the training and test datasets). A comparative analysis of the developed and traditional controllers showed that the neuro-fuzzy network use reduces the transient fuel consumption process time by 8.92% while increasing the accuracy and F1 score by 18.28% and 21.32%, respectively.

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Real-time optimization control of variable rotor speed based on Helicopter/ turboshaft engine on-board composite system

Cited by 3 publications

References 31 publications

Speed controller design for turboshaft engine using a high-fidelity AeroThermal model

Speed controller design for turboshaft engine using a high-fidelity AeroThermal model

An Innovative Applied Control System of Helicopter Turboshaft Engines Based on Neuro-Fuzzy Networks

Method for Helicopter Turboshaft Engines Controlling Energy Characteristics Through Regulating Free Turbine Rotor Speed and Fuel Consumption Based on Neural Networks

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