Full Authority Digital Engine Control Research Articles

Aero-engine on-board model based on big Quick Access Recorder data

With the development of the Full Authority Digital Engine Controller (FADEC) technology, the aero-engine on-board model is widely used in Engine Health Management (EHM) and control. Due to the FADEC’s limited computational capability and storage capacity, the model should not be very intricate; consequently, the interpolation model is widely utilized. Although the interpolation model’s low precision precludes further development of on-board models for EHM and control. To address the trade-off between precision and complexity, a novel on-board modeling method is proposed based on the Nonlinear Autoregressive with Exogenous Inputs Backpropagation neural network (NARX-BPNN) trained using the mini-batch Levenberg–Marquardt (LM) algorithm on large Quick Access Recorder (QAR) data. The NARX model’s features and time delay are chosen by referring to the line interpolation model, which gives interpretability for feature selection. The combination of a shallow neural network and big data training can guarantee the on-board model’s real-time and storage requirements, as well as its generalizability. The mini-batch LM method can avoid both the local optimum problem in the shallow neural network and the storage difficulty associated with massive data while still achieving a rapid convergence rate due to the LM algorithm’s global view. The NARX-BPNN models are compared to an existing line interpolation model using 100 different aero-engines' QAR data. The results reveal that accuracy may be increased by approximately 30% while maintaining superior dynamic performance and anti-noise capacity compared to the line interpolation approach.

Advanced Control Algorithm for FADEC Systems in the Next Generation of Turbofan Engines to Minimize Emission Levels

New propulsion systems in aircrafts must meet strict regulations and emission limitations. The Flightpath 2050 goals set by the Advisory Council for Aviation Research and Innovation in Europe (ACARE) include reductions of 75%, 90%, and 65% in CO2, NOx, and noise, respectively. These goals are not fully satisfied by marginal improvements in gas turbine technology or aircraft design. A novel control design procedure for the next generation of turbofan engines is proposed in this paper to improve Full Authority Digital Engine Control (FADEC) systems and reduce the emission levels to meet the Flightpath 2050 regulations. Hence, an Adaptive Network–based Fuzzy Inference System (ANFIS), nonlinear autoregressive network with exogenous inputs (NARX) techniques, and the block-structure Hammerstein–Wiener approach are used to develop a model for a turbofan engine. The Min–Max control structure is chosen as the most widely used practical control algorithm for gas turbine aero engines. The objective function is considered to minimize the emission level for the engine in a pre-defined maneuver while keeping the engine performance in different aspects. The Genetic Algorithm (GA) is applied to find the optimized control structure. The results confirm the effectiveness of the proposed approach in emission reduction for the next generation of turbofan engines.

Formal system interactive failure analysis method based on systems theoretic process analysis model

Interactive failures are failures caused by two or more components that often occur in complex systems when the system is modified, upgraded, or simply designed inadequately. However, the official guideline provided, namely, common cause analysis, cannot discover these problems. It cannot establish a complex interactive system model, nor can it provide a unified analysis method for all parts of the system. Another method, systems theoretic process analysis, is limited to the control system.To solve this problem, a method called system theoretic formal analysis method (STFAM) is proposed in this paper. STFAM establishes a system-component-interactive model that provides an abundance of interactive information for failure analysis and presents a unified model to support the analysis of multiple components in the system. It is divided into three steps. First, a hierarchical system structure is built and then transformed into a formalized state machine. Next, the interactive failures are determined and converted into a linear temporal logic or computation tree logic model. Finally, NuSMV is used to verify the model and record the results. To evaluate the proposed method, a practical problem that occurred in full-authority digital engine control, in which in some cases, the valve closes for unknown reasons until the system is reset is presented. An analysis of the issue demonstrates the effectiveness of our method.

Accuracy analysis of a single-fault Markov model for FADEC system

Time-limited dispatching (TLD) analysis of the full authority digital engine control (FADEC) systems is an important part of the aircraft system safety analysis and a necessary task for the certification of commercial aircraft and aeroengines. In the time limited dispatch guidance document ARP5107B, a single-fault Markov model (MM) approach is proposed for TLD analysis. However, ARP5107B also requires that the loss of thrust control (LOTC) rate error calculated by applying the single-fault MM must be less than 5% when performing airworthiness certification. Firstly, the sources of accuracy errors in three kinds of MM are analyzed and specified through a case study of the general FADEC system, and secondly a two-fault MM considering maintenance policy is established through analyzing and calculating the expected repair time when two related faults happen. Finally, a specific FADEC system is given to study on the influence factors of accuracy error in the single-fault MM, and the results show that the accuracy error of the single-fault MM decreases with the increase of short or long prescribed dispatch time, and the range values of short time (ST) and long time (LT) are determined to satisfy the requirement of accuracy error within 5%.

Intelligent Reasoning for Gas Turbine Fault Isolation and Ambiguity Resolution

An engine health management (EHM) system typically consists of automated logic for data acquisition, parameter calculation, anomaly detection and eventually, fault identification (or isolation). Accurate fault isolation is pivotal to timely and cost-effective maintenance but is often challenging due to limited fault symptom observability and the intricacy of reasoning with heterogeneous parameters. Traditional fault isolation methods often utilize a single fault isolator (SFI) that primarily relies on gas path performance parameters. While effective for many performance-related faults, such approaches often suffer from ambiguity when two or more faults have signatures that are very similar when monitored by a rather limited number of gas path sensors. In these cases, the ambiguity often has to be resolved by experienced analysts using additional information that takes many different forms, such as various nongas path symptoms, full authority digital engine control fault codes, comparisons with the companion engine, maintenance records, and quite often, the analyst's gas turbine domain knowledge. This paper introduces an intelligent reasoner that combines the strength of an optimal, physics-based SFI and a fuzzy expert system that mimics the analytical process of human experts for ambiguity resolution. A prototype diagnostic reasoner software has been developed and evaluated using existing flight data. Significant performance improvements were observed as compared with traditional SFI results. As a generic reasoning framework, this approach can be applied not only to traditional snapshot data, but to full flight data analytics as well.

Full Authority Digital Engine Control: Overall System, Function and its Application

Full Authority Digital Engine Control: Overall System, Function and its Application

System On Chip (SOC) ASIC chipset for Smart Actuators in Distributed Propulsion Systems

Abstract This paper describes the results of the risk reduction testing task recently completed by Embedded Systems LLC under the Air Force SBIR contract {5} titled “Improved Full Authority Digital Engine Control (FADEC) System”. The objective of this program has been to develop a hierarchical, distributed architecture for future propulsion FADEC and aerospace control systems with flexible, scalable and reconfigurable Smart Nodes (SN) built with high temperature capable devices. A key part of this program is the design, development and validation of the System On Chip (SOC) chipset in high temperature (225 Deg. C) SOI (Silicon On Insulator) technology ASIC (Application Specific Integrated Circuit) devices. The SOC chipset designed by Embedded Systems LLC provides the scalability and reconfigurability that enables the Smart Node to interfaces with most sensors and actuators found in FADEC and other aircraft control systems. The analog portion of this 2-chip SOC chipset fabricated by Honeywell using their SOI process is working properly. The digital portion of the SOC chipset, currently implemented in a commercial temperature FPGA (Field Programmable Gate Array), contains important computational functions needed for reconfiguring the SOC and performing complex control functions, such as real time control of an actuator, The risk reduction task was therefore focused on verification and validation of these key functions in a real environment before converting the design into an ASIC. The recent successful demonstration of the real time actuator control capability has minimized the risks and cleared the way for the digital ASIC implementation. The complete high temperature SOC chipset is expected to be available in late 2016.

Full Authority Digital Engine Control (FADEC)

Full Authority Digital Engine Control (FADEC) Systems is a system consisting of a digital computer and ancillary components that control an aircraft's engine and propeller. The system consists of a digital computer, called an electronic engine controller (EEC) or engine control unit (EEU), and its related accessories that control all aspects of aircraft engine performance. This paper includes the functionality and importance of this technology.

Линейная адаптивная бортовая математическая модель двигателя для повышения надежности систем автоматического управления авиационным ГТД

Линейная адаптивная бортовая математическая модель двигателя для повышения надежности систем автоматического управления авиационным ГТД

A Current-Controlled PCB Integrated MEMS Tilt Mirror

Introduction: MEMS Tilt Mirror - a miniature planar micro-mirror that can experience a 1-D or 2-D tilt in response to a control signal. Commonly used technologies- electrostatic, piezoelectric, electrothermal bimorph. Applications - laser beam steering, interferometers, dynamic signal analyzers, opticcal cross-connect switches. This paper describes the design, key features and applications of a System On Chip (SOC) ASIC (Application Specific Integrated Circuit) that has been developed under an Air Force SBIR program. The SOC device has been implemented by Honeywell International using their High Temperature SOI (Silicon On Insulator) Process. The objective of the Air Force SBIR program {1} was to investigate the potential for use of available High Temperature SOI technology devices for aerospace propulsion control system applications. Several prototype designs implemented by Embedded Systems LLC (ES-LLC) using available SOI devices identified significant limitations in the performance capability and level of integration. The diversity of propulsion system interfacing requirements demanded generic solutions so that they could be deployed in multiple applications without changes. The available devices were also not affordable due to the limited size of the market for this technology. It was therefore decided to develop a generic, reconfigurable SOC chipset {2} that could be implemented using Honeywell's HT200 Family of ASIC Gate Arrays. The paper will describe the architecture and key features of the SOC chipset solution which can be reconfigured to interface with most typical aerospace control system sensors and actuators. The SOC chipset captures all of the necessary functions required to interface with sensors such as RTD (resistance Temperature Detectors), Strain Gauges (SG) and thermocouples (TC), mass flow, speed and LVDT (Linear Variable Differential Transducer) position. The excitation circuitry required to power these interfaces is embedded in the chipset and can be reconfigured as required. The SOC chipset also contains all of the pre- and post-processing functions to convert electrical signals into digital words and send them on a data bus under the control of a host microprocessor. The SOC chipset can be powered from a Mil-Std 704F compliant power source or a conditioned DC power source. The SOC chipset when combined with other external devices can be implemented as a “Smart Node” for localized management of sensors and actuators as a part of a distributed architecture or used as a scalable building block in a more complex function such as a FADEC (Full Authority Digital Engine Control). The SOC chipset thus completes the set of all High Temperature SOI Integrated circuits required for implementation of typical Smart Nodes. It is believed that the versatility of the SOC chipset makes it a well suited, affordable, scalable building block for not only aerospace controls but also for diverse applications such as down-hole drilling, energy exploration, wind farms etc. where high temperature electronics is required.

A System On Chip (SOC) ASIC chipset for Aerospace and Energy Exploration Applications

This paper describes the design, key features and applications of a System On Chip (SOC) ASIC (Application Specific Integrated Circuit) chipset which was developed by Embedded Systems LLC as a part of the Smart Node based distributed control system architecture under an Air Force SBIR (Small Business Innovative Research) program {4}. The analog part of the SOC chipset has been implemented by Honeywell International under a subcontract using their high temperature SOI (Silicon On Insulator) Process. The complete chipset is expected to be available in early 2015. The key feature of the SOC chipset is that it is a reconfigurable and scalable building block that can be used to interface with most typical aerospace control system sensors and actuators. The SOC chipset captures all of the necessary functions required to power and interface with sensors such as RTD (Resistance Temperature Detectors), Strain Gauges (SG), Thermo Couples (TC) and transducers for measuring mass flow, speed, position or angle. The SOC chipset also contains all of the pre- and post-processing functions to convert electrical signals into digital words and send them on a data bus under the control of a host microprocessor. Finally, the SOC chipset contains PWM (Pulse Width Modulation) circuitry required to interface with external drives for actuators, motors, shutoff Valves etc. The SOC chipset can be powered from a Mil-Std-704F compliant power source or a conditioned DC power source. The chipset can be combined with other devices, such as memory, processor and A to D Converter to implement a high temperature capable Smart Node for localized management of sensors and actuators as a part of a distributed architecture or used as a scalable building block in a more complex function such as a FADEC (Full Authority Digital Engine Control). It is believed that the versatility of the SOC chipset makes it a well suited, affordable, scalable building block for not only aerospace controls but also for diverse applications such as down-hole drilling, energy exploration, wind farms etc. where high temperature electronics and /or high level of miniaturization is required.

Technological Change from Analog to Digital

Abstract: Brusoni, Prencipe, and Pavitt (2001) posited that the digitization of aircraft engine control systems in the early 1980s caused loose organizational coupling. During this period, the number of control parameters indeed increased significantly with the introduction of full authority digital engine control (FADEC). However, during the period categorized by Brusoni et al. (2001) as the (analog) generation, digital technologies such as analog electronic and supervisory controls were gradually introduced. Moreover, with regard to technological changes in aircraft turbofan engines and control systems, technological improvements in engine power systems were evident in the 1960s and 1970s in terms of the bypass ratio, overall pressure ratio, and turbine inlet temperature. Although engine power systems witnessed negligible technological innovation in the 1980s, control systems improved as the number of control parameters increased due to the advent of FADEC. Subsequently, in the 1990s, great technological strides were made in engine power systems. Hence, technological changes in engine power systems and control systems always occurred alternately. Brusoni et al.'s claim that the decline in organizational coupling was due to the even rate of technological change in engines and control systems or the predictability in their interdependence miss the mark in light of the transition history of engine and control systems.Keywords: analog (hydromechanical), digital, aircraft engine control system, technological imbalance1. IntroductionBrusoni, Prencipe, and Pavitt (2001) categorized aircraft engine control systems from the 1950s to the 1970s as hydromechanical (analog) and those from the 1980s to the 1990s as digital. Brusoni et al. (2001) described the scope for change in the organizational structure and knowledge of three companies1 from the perspective of the evolution of control system technology. However, they barely mentioned the change in control system technology from analog to digital, nor did they focus on the changes in the engine power systems, which are associated with changes in control system technology. Referencing Brusoni et al.'s arguments, this study focuses on the transition of engine control systems from analog to digital and the associated technological changes in the power systems in order to review the technologies analyzed by Brusoni et al.2. Technological Change of Engine Control System:From Hydromechanical to DigitalBrusoni et al. (2001) focused on the control systems of aircraft turbofan and turbojet engines. A turbojet engine comprises an air intake, a fan/compressor, combustion chamber, turbine, afterburner, and tail nozzle. The pilot adjusts the position of the throttle lever to achieve the required thrust. The engine control system provides the necessary thrust by receiving the lever position as input and adjusting the fuel flow, thereby accelerating or decelerating the engine's revolutions per minute (RPM). Furthermore, it confirms whether the thrust corresponds with the pilot's intention and maintains the required thrust levels (Yoshinaka, 2010).Compared with the digital system, the analog system could control only a limited number of items. The following section discusses the evolution of jet engine control technologies based on Endoh (2004), Sugiyama (2004), Sono (2008), and Yoshinaka (2010).2.1. Hydromechanical controlThe jet engine was first adopted as a source of thrust in aircrafts in the 1930s. Simple mechanical fuel controls comprising cams and levers were used in reciprocating engines, which constituted the majority at the time. The control required by jet engines was comparatively complex, and the existing technology was inadequate. Even in the case of early post-war turbojet engines, variables of fuel flow or bleed valve could only be controlled. Subsequently, advances in the level of precision and miniaturization in the areas of mechanics and oil hydraulics led to progress in the control technologies of aircraft engines. …

An Adaptive Threshold Algorithm Based on Satisfactory Filtering Principle

In this paper, the problem of designing a adaptive threshold for Fault diagnostic in Full Authority Digital Engine Control system that are subject to environmental disturbances and various input is investigated. According to aero-engine small deviation linearization model, state matrix perturbation model with "soft boundary" pseudo normal distribution is built. The proposed algorithm bases on satisfaction filtering principle. Linear matrix inequality (LMI) method is applied to get upper bound of residual. With the residual distribution probability model and the target false alarm rate, the optimal threshold is determined. The proposed algorithm is then applied to sensor fault detection on a turbofan aero-engine. Simulation results demonstrate and validate the performance and capability of the adaptive threshold algorithm.

한국형기동헬기 임무컴퓨터 비행필수기능 설계

Avionics system tends to be designed to have the integrated architecture, and it is getting difficult and complex to verify the flight-critical function because of sophisticated structure. In Korean Utility Helicopter, mission computer acts as the MUX Bus Controller to handle the data from both communication, identification, mission/display and survivability equipment inside Mission Equipment Package and aircraft subsystems such as fuel system and electrical system while it is interfacing with Automatic Flight Control System and Full-Authority Digital Engine Control via ARINC-429 bus. The Flight Displays which is classified as flight-critical function in aircraft is implemented on Primary Flight Display after mission computer processes data from AFCS in order to generate graphics. This paper defines the flight-critical function implemented in mission computer for KUH, and presents the static and dynamic test procedures which is performed on System Integration Laboratory along with Playback Recorder prior to flight test.

Application of wireless sensor networks to aircraft control and health management systems

Use of fly-by-wire technology for aircraft flight controls have resulted in an improved performance and reliability along with achieving reduction in control system weight. Implementation of full authority digital engine control has also resulted in more intelligent, reliable, light-weight aircraft engine control systems. Greater reduction in weight can be achieved by replacing the wire harness with a wireless communication network. The first step towards fly-by-wireless control systems is likely to be the introduction of wireless sensor networks (WSNs). WSNs are already finding a variety of applications for both safety-critical and nonsafety critical distributed systems. Some of the many potential benefits of using WSN for aircraft systems include weight reduction, ease of maintenance and an increased monitoring capability. This paper discusses the application of WSN for several aircraft systems such as distributed aircraft engine control, aircraft flight control, aircraft engine and structural health monitoring systems. A brief description of each system is presented along with a discussion on the technological challenges. Future research directions for application of WSN in aircraft systems are also discussed.

EMI suppression in an aircraft cooling vent

Digital avionics systems are increasingly under threat from external electromagnetic interference (EMI). The same avionics systems require a thermal cooling mechanism and one method of providing this is to mount an air vent on the body of the aircraft. For the first time, a nacelle-mounted air vent that may expose the flight critical full authority digital engine controller (FADEC) to high intensity radiated fields (HIRF) is examined. The reflection/transmission characteristics of the vent are reported and the current shielding method employed is shown to provide a low shielding level (5 dB at 18 GHz). A new design has been proposed, providing over 100 dB of attenuation at 18 GHz. To the authors' knowledge this is the first time this shielding method has been applied to aircraft air vents.

항공기 엔진제어시스템 인증기술 개발

The aircraft gas turbine engines with the Electronic Engine Controls(EEC) had been developed to save fuel and enhance their performance in the early days, and had employed the health monitoring function in the Full Authority Digital Engine Controls(FADEC) to improve their reliability. This has led to an increasing demand for the certification technology of these controls. The design and certification issues of power supply, aircraft supplied data, failure modes, software verification/validation, and lightning requirements need to be addressed. This paper presents the design considerations and the certification techniques applied to the electronic engine controls. And it is believed that this paper will be basis to establish a requirement in Korean Airworthiness Standard.

Training Levels and Methodologies for Glass Cockpit Training in Collegiate Aviation

Training Levels and Methodologies for Glass Cockpit Training in Collegiate Aviation

Optimal self-diagnosis policy for FADEC of gas turbine engines

FADEC (full authority digital engine control) is widely adopted for gas turbine engine controllers. The advancement of microelectronics produces high speed general purpose programmable logic controllers (PLC) with low price. When they are adopted for FADEC, we can expect high cost performance engine controllers. However, these PLCs were originally developed for ordinary industrial machinery controllers and PLC makers prohibited their use as gas turbine controllers because of their low reliability. Engine makers should give some measures to hold enough reliability when they apply PLCs for FADEC. In this paper, a FADEC is self-diagnosed at the n th control calculations. Introducing an expected cost until self-diagnosis and an expected cost per unit time, optimal policies which minimize them are discussed. Numerical examples are finally given.

Fuzzy Fuel Flow Selection Logic for a Real Time Embedded Full Authority Digital Engine Control

The control logic of the modern full authority digital engine control is comprised of many control loops, each of which has a specific purpose. Typical control loops include (but are not limited to) a high or low rotor speed governor, an acceleration and deceleration loop, and various limiting loops for temperature, speed, fuel flow, and rate of change of fuel flow. The logic that determines which of these loops is “in control” at any particular time has a history of being very simplistic. This selection logic is usually nothing more that a cascade of minimum and maximum selection logic gates. Since this logic is so simplistic, the control engineer often has to “fine-tune” the compensator design for each loop, in order to achieve proper performance.