Propulsion Controls Modeling for a Small Turbofan Engine

Abstract

A nonlinear dynamic model and propulsion controller are developed for a small-scale turbofan engine. The small-scale turbofan engine is based on the Price Induction company's DGEN 380, one of the few turbofan engines targeted for the personal light jet category. Comparisons of the nonlinear dynamic turbofan engine model to actual DGEN 380 engine test data and a Price Induction simulation are provided. During engine transients, the nonlinear model typically agrees within 10% error, even though the nonlinear model was developed from limited available engine data. A gain scheduled proportional integral low speed shaft controller with limiter safety logic is created to replicate the baseline DGEN 380 controller. The new controller provides desired gain and phase margins and is verified to meet Federal Aviation Administration transient propulsion system requirements. In understanding benefits, there is a need to move beyond simulation for the demonstration of advanced control architectures and technologies by using real-time systems and hardware. The small-scale DGEN 380 provides a cost effective means to accomplish advanced controls testing on a relevant turbofan engine platform.

Study on Identification Method for Parameter Uncertainty Model of Aero Engine

“…The purpose of the comparison is (1) to reveal the error between the state value computed by the parameter uncertain model and experimental value and (2) to compare the model behavior between the parameter uncertainty model and a linear model. This linear model of DGEN380 is selected for comparison that is built at the maximum continuous power point by NASA Glenn Research Center [17]. This model is often used for DGEN380 controller design and diagnosis algorithm design which has universality because of the high accuracy.…”

Intelligent Situational Control of Small Turbojet Engines

“…In operational control, the acceleration and constant speed controllers are the most important ones, as they are responsible for tracking of command signals [1,2,20]. Both controllers can be also designed as a single robust feedback controller [30,31] or fuel flow scheduler [19,20]; however, the situational control approach allows to design them as two specialized feedback controllers aimed to improve the resulting control quality.…”

“…Both controllers can be also designed as a single robust feedback controller [30,31] or fuel flow scheduler [19,20]; however, the situational control approach allows to design them as two specialized feedback controllers aimed to improve the resulting control quality. The situational control system with intelligent switching can fluently switch between those controllers and even have them operate in cooperative mode to further enhance control quality in order to remove any transients, which could appear during a switch between the acceleration and constant speed controllers.…”

“…On top of that, special strategies like limiters and auxiliary systems are used to protect the engine from departing its operational envelope [19]. Transient states of the engine are handled by acceleration/deceleration min/max schedulers [19], typical architecture of the baseline digital engine control using engine protection logic being shown in the recent work of Connolly et al in [20]. Diagnostics and health management are usually running as a separate process influencing operation and control of the engine using limiters [18,19].…”

The Nonlinear Single Controller of DGEN380 Aero Engine Design

“…There are two essential functions in the control system of the aero engine which are power management and limitation protection. And power management includes steady state control and transition state control [1]. However, the real controller of the aero engine consists of steady controller, transient controller, and limitation controller now.…”