A real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.
An integrated model including inlet, engine and nozzle with their internal and external characteristics was built to simulate the propulsion installed performance. With the integrated model, a new performance seeking control scheme under supersonic state is firstly proposed, taking inlet ramp angle as optimizing variable, which is equally important to fuel flow rate, nozzle throat area, guided vane angle of fan and compressor. Specially, engine installed thrust replaces its total thrust as one crucial factor for performance seeking control. Installed performances under supersonic state are significantly improved with the new scheme, as installed thrust increases of up to 4.9% in the maximum thrust mode, installed specific fuel consumption improvements of up to 3.8% in the minimum fuel consumption mode, and turbine temperature decreases of up to 0.6% in the minimum turbine temperature mode. The simulation results also indicates that, the performance seeking control scheme proposed shows superiority in restraining of the increasing of rotational speed and turbine temperature in performance seeking control.
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