An adaptive matching control method of multiple turboshaft engines

Abstract

In order to overcome the problem that the conventional multi-engine matching control method never balance the service lives of engines and transmission system synchronously while engines have individual differences and performance degradations, an adaptive matching control method of multiple turboshaft engines is proposed and designed. Firstly, based on the deep neural network (DNN), the onboard adaptive model is established to simulate the coupling dynamics of multiple engines. It can automatically trace engine output torques, discharge temperatures of gas turbine and rotational speeds of compressor. Then, the numerical optimization problem of multi-engine matching is built to obtain the optimal discharge temperatures of gas turbine online. It is featured with a multi-objective function that integrates the maximum deviations of engine output torques, discharge temperatures of gas turbine and the relative rotational speeds of compressor. Finally, the optimal discharge temperatures of gas turbine are input to the conventional matching strategy to accomplish the adaptive matching control. The results demonstrate that compared with the conventional matching strategy, when the number of turboshaft engine is three, the adaptive matching control method can dramatically decrease the maximum matching error of compressor speeds and engine output torques by more than 40% and 60% individually with the maximum deviation of the discharge temperatures of gas turbine no more than 3%. It proves to be conducive to balancing the service lives of multiple engines and transmission system.