Browse Topic: Avionics
The scope of this SAE Aerospace Information Report (AIR) is to discuss factors affecting visibility of aircraft navigation and anticollision lights, enabling those concerned with their use to have a better technical understanding of such factors, and to aid in exercising appropriate judgment in the many possible flight eventualities
Aerospace manufacturers are leveraging multicore processors and modularity to design smarter cockpit displays and avionic computers that are smaller and capable of supporting more applications from a single line replaceable unit (LRU). Some are also starting to embed more of the processing required to enable cockpit display applications within the display itself, rather than having it enabled by an associated LRU. The development of new electric vertical takeoff and landing (eVTOL) aircraft and avionics companies changing their approach to the development of safety critical computers and aircraft networking technologies are some of the aerospace industry factors driving this design trend. In the U.S., the Department of Defense (DoD) embracing the Modular Open Systems Approach (MOSA) across the purchase of all new aircraft technologies is influencing design changes in cockpit displays and aircraft computers as well
The intent of this AIR is twofold: (1) to present descriptive summary of aircraft nosewheel steering and centering systems, and (2) to provide a discussion of problems encountered and “lessons learned” by various airplane manufacturers and users. This document covers both military aircraft (land-based and ship-based) and commercial aircraft. It is intended that the document be continually updated as new aircraft and/or new “lessons learned” become available
Over the last decade, a government-industry effort to advance the use of modern computer processors and networks in spacecraft avionics systems has quietly been making its own gains in industry adoption and a re-thinking of the way next generation spacecraft electronic systems could be designed in a less costly and more interoperable way. Spacecraft avionics systems are all of the electronic instruments, components, computers and subsystems that control primary spaceflight flight and data communications functionality
Recent advancements of electric vertical take-off and landing (eVTOL) aircraft have generated significant interest within and beyond the traditional aviation industry, and many novel applications have been identified and are in development. One promising application for these innovative systems is in firefighting, with eVTOL aircraft complementing current firefighting capabilities to help save lives and reduce fire-induced damages. With increased global occurrences and scales of wildfires—not to mention the issues firefighters face during urban and rural firefighting operations daily—eVTOL technology could offer timely, on-demand, and potentially cost-effective aerial mobility capabilities to counter these challenges. Early detection and suppression of wildfires could prevent many fires from becoming large-scale disasters. eVTOL aircraft may not have the capacity of larger aerial assets for firefighting, but targeted suppression, potentially in swarm operations, could be valuable. Most
This SAE Aerospace Standard (AS) defines minimum performance standards (MPS) for fuel flowmeters, fuel flow indicators, and fuel flow transmitters. The fuel flow indicators and transmitters are intended for use in 14 CFR Part 23, 25, 27, and 29 aircraft equipped with reciprocating and turbine engines. Multiple function displays are not within the scope of this SAE Aerospace Standard (refer to AS6296
This SAE Aerospace Information Report (AIR) provides the hydraulic and flight-control system designer with the various design options and techniques that are currently available to enhance the survivability of military aircraft. The AIR addresses the following major topics: a Design concepts and architecture (see 3.2, 3.5, and 3.6) b Design implementation (see 3.3, 3.6, and 3.7) c Means to control external leakage (see 3.4) d Component design (see 3.8
This Technical Governance is part of the SAE UCS Architecture Library and is primarily concerned with the UCS Architecture Model (AS6518) starting at Revision A and its user extensions. Users of the Model may extend it in accordance with AS6513 to meet the needs of their UCS Products. UCS Products include software components, software configurations and systems that provide or consume UCS services. For further information, refer to AS6513 Revision A or later. Technical Governance is part of the UCS Architecture Framework. This framework governs the UCS views expressed as Packages and Diagrams in the UCS Architecture Model
This aerospace recommended practice provides a framework and suggested procedures or values for requirements for the design, performance, and test of hydraulically powered servoactuators for use in aircraft flight control systems. The original version of this document was intended for military usage: consequently, the requirements still often reflect such use. However, the basic requirements of this ARP may and should be applicable to commercial usage as well, provided that appropriate considerations are given for the applicable FAR/JAR 25 regulations, hydraulic fluids, and environmental conditions
Over the past few decades, aircraft automation has progressively increased. Advances in digital computing during the 1980s eliminated the need for onboard flight engineers. Avionics systems, exemplified by FADEC for engine control and Fly-By-Wire, handle lower-level functions, reducing human error. This shift allows pilots to focus on higher-level tasks like navigation and decision-making, enhancing overall safety. Full automation and autonomous flight operations are a logical continuation of this trend. Thanks to aerospace pioneers, most functions for full autonomy are achievable with legacy technologies. Machine learning (ML), especially neural networks (NNs), will enable what Daedalean terms Situational Intelligence: the ability to understand and make sense of the current environment and situation but also anticipate and react to a future situation, including a future problem. By automating tasks traditionally limited to human pilots - like detecting airborne traffic and identifying
With the advancement of automotive industries, the need for wireless connectivity between vehicle and smartphone is increasing. To meet the demand for wireless connectivity, Bluetooth plays a vital role. Testing Bluetooth systems is challenging and complex when development cycles of the system involve multiple partners. The system under test must fulfil consumers expectation of Bluetooth functionality paired with their personal devices. Despite many advances and existence of a few reliable systems, hardware limitation, and lack of standardization in Bluetooth test system are some of the prolonged issues. Throughout the course, various capabilities and existing traditional Bluetooth testing system practice were researched, which majorly at a system level (Black box). The gap of such testing is the escape of defect which involves the interoperability of multiple profiles like AVRCP, HFP, and A2DP. This paper focuses on a reliable testing approach which is based on packet level testing
Advanced flight control system, aviation battery and motor technologies are driving the rapid development of eVTOL to offer possibilities for Urban Air Mobility. The safety and airworthiness of eVTOL aircraft and systems are the critical issues to be considered in eVTOL design process. Regarding to the flight control system, its complexity of design and interfaces with other airborne systems require detailed safety assessment through the development process. Based on SAE ARP4754A, a forward architecture design process with comprehensive safety assessment is introduced to achieve complete safety and hazard analysis. The new features of flight control system for eVTOL are described to start function capture and architecture design. Model-based system engineering method is applied to establish the functional architecture in a traceable way. SFHA and STPA methods are applied in a complementary way to identify the potential safety risk caused by failure and unsafe control action. PSSA with
The presence of a slung-load during the flight of a quadrotor generates swing effects that can greatly influence the dynamics of the quadrotor. These effects have the potential to threaten the stability of the system’s attitude. This study presents a disturbance compensation strategy that is designed based on the utilization of an adaptive harmonic extended state observer (AHESO) in order to solve this problem and achieve precise attitude control. To derive the aforementioned algorithm, a comprehensive mathematical model for the quadrotor-slung-load system is built. The periodic features of disturbance are derived by considering the movement of the slung-load. Subsequently, by taking the periodic features of the disturbances into account, the AHESO for accurate disturbance estimation is designed. In this observer, an online frequency estimator for the harmonic disturbances is introduced. Lyapunov theory is introduced to examine the stability of the AHESO. In addition, backstepping
This standard defines the requirements used by the Plan owner to develop a DMSMS Management Plan, hereinafter referred to as the Plan. The requirement to develop a DMSMS Management Plan could come from a number of different sources, such as a contractual or customer requirement or a desire by the Plan owner to document their standard process. The process described in the Plan is intended to mitigate DMSMS risks and resolve DMSMS issues on ADHP equipment provided by the Plan owner. Development of a plan that conforms to the technical requirements detailed in Section 3 ensures that the Plan owner meets the requirement of a DMSMS, or obsolescence management plan, required by industry standards, government regulations, and/or other contractual flow-down requirements, such as: a EIA-STD-4899, Standard for Preparing an Electronic Components Management Plan b AS5553, Counterfeit Electronic Parts; Avoidance, Detection, Mitigation, and Disposition c DFARS 252.246-7007, Contractor Counterfeit
Machine learning is used for the research and development of ITS services and the rider assistance for on-road motorcycle racing. Meanwhile, rider assistance systems for off-road motorcycles have yet to be developed, partly due to the complexity of the measurement conditions, as described in the previous paper. This research aims to create a reliable AI which is capable of classifying typical jump behaviors in off-road riding by machine learning to create a rider assistance system for off-road motorcycles. Motorcycle manufacturers and certain research institutes use motion sensors to collect data, but the data is obtained from a limited number of vehicles and riders. The creation of a rider assistance system requires a large amount of validation data. Furthermore, it is desirable to achieve the target with data that can be measured in mass-produced vehicles, which will make it possible to collect data even from general users. In addition, recent machine learning models are black boxes
Recent advances in the operation of advanced CMOS processes for extremely high-speed and high dynamic range analog-to-digital (ADC) and digital-to-analog (DAC) data converters has led to their use in directly sampling microwave and even millimeter wave signals. Typically, in these applications, minimal pre or post-conditioning stages separate the ADCs and DACs from the antenna or, for Active Electronically Steered Arrays (AESA) antenna elements. This results in an extremely compact and flexible system solution and this has enabled a generation of fully digital phased arrays that are capable of being dynamically reconfigured to perform a multitude of functions
Artificial intelligence (AI) has become prevalent in many fields in the modern world, ranging from vacuum cleaners to lawn mowers and commercial automobiles. These capabilities are continuing to evolve and become a part of more products and systems every day, with numerous potential benefits to humans. AI is of particular interest in autonomous vehicles (AVs), where the benefits include reduced cognitive workload, increased efficiency, and improved safety for human operators. Numerous investments from academia and industry have been made recently with the intent of improving the enabling technologies for AVs. Google and Tesla are two of the more well-known examples in industry, with Google developing a self-driving car and Tesla providing its Full Self-Driving (FSD) autopilot system. Ford and BMW are also working on their own AVs
Recent advances in the operation of advanced CMOS processes for extremely high-speed and high dynamic range analog-to-digital (ADC) and digital-to-analog (DAC) data converters has led to their use in directly sampling microwave and even millimeter wave signals. Typically, in these applications, minimal pre or post-conditioning stages separate the ADCs and DACs from the antenna or, for Active Electronically Steered Arrays (AESA) antenna elements. This results in an extremely compact and flexible system solution and this has enabled a generation of fully digital phased arrays that are capable of being dynamically reconfigured to perform a multitude of functions
The challenge faced by flight software engineers at the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder became evident when tasked with developing the onboard software for NASA's new Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Reflected Solar mission. The goal of measuring Earth-reflected sunlight with an accuracy of 0.3 percent (k=1), surpassing existing sensors by five to tenfold, from an instrument mounted beneath the International Space Station (ISS), produced a complex set of requirements. The avionics needed to balance multiple functions, including a high-rate control law, numerous hard real-time deadlines, interfaces with half a dozen external subsystems, and management of commands, telemetry and fault protection, all while capturing high-resolution science images at 15 frames per second. Ensuring uninterrupted operation within the unforgiving environment of low-Earth orbit necessitated the software run on
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