An electric aircraft for generating a yaw force includes a fuselage, a plurality of laterally extending elements secured to the fuselage, a plurality of lift components attached to the plurality of laterally extending elements, and at least a longitudinal thrust component attached to the plurality of laterally extending elements, wherein the longitudinal thrust component is configured to generate a yaw force.

An unmanned aerial vehicle traveling with an imaging device includes at least one memory and at least one processor which function as: an estimation unit configured to estimate an amount of power consumed by the imaging device and the unmanned aerial vehicle during a time period in which the imaging device and the unmanned aerial vehicle travel from a current location to a target position; and a control unit configured to execute control to give a predetermined notification based on a remaining amount of power of a power supply unit configured to supply power to the imaging device and the unmanned aerial vehicle, and an amount of power consumption estimated by the estimation unit.

A Smart Products Lifecycle Management (sPLM) system that is built upon the smart component data model and the NPD.sup.3 process model, is enabling engineers, data scientists, and other stakeholders to collaborate on a common platform to develop smart products. The sPLM system is validated by applying it to unmanned aircraft systems (UAS) development and operations, referred to as UsPLM. The UsPLM has shared lifecycle management functions that are provided as web services and can be applied to all digital models of UAS devices, software, autonomy functions, and missions. The individual models can be versioned, tracked, and be composed with other compatible models, if needed. The rule and scoring engines embedded in the UsPLM allow building and executing configuration rules, regulation rules, and various machine-learning models. This facilitates modular UAS architecture design so that the UAS has the flexibility to be reconfigured for various mission applications.

A flight pushback state monitoring method based on multi-modal data fusion comprises: 1, constructing a control intention recognition rule, and recognizing a pushback intention from a control instruction sent by a controller; 2, constructing a flight intention recognition model, extracting an aircraft action from a real-time monitoring video, and capturing a flight intention; and 3, constructing an intention alignment fusion rule, and judging whether control intention information conflicts with flight intention information; by fusing the control intention and the flight intention, the method can realize the following auxiliary functions: timely judging whether the aircraft follows the pushback instruction sent by the controller, if a captain does not act according to the control instruction or acts arbitrarily without a control instruction, giving an inconsistent alarm, and a function of monitoring the flight pushback state is implemented.

A power distribution controller for a hybrid aircraft is configured to continuously: obtain a state-of-charge (SoC) measurement for a battery of the hybrid aircraft; obtain a fuel level measurement for a secondary energy source of the hybrid aircraft; receive a control input indicating one of a throttle level or an operating mode for one or more motors of the hybrid aircraft; calculate a ratio of energy to source from each of the battery and the secondary energy source in order to operate the one or more motors of the hybrid aircraft based on the control input, the SoC measurement, and the fuel level measurement; and transmit a control signal that causes energy to be apportioned from the battery and the secondary energy source to the one or more motors based on the determined ratio.

Examples described herein provide a computer-implemented method that includes monitoring a hybrid electric turbine engine of an aircraft, the hybrid electric turbine engine including a first electric machine associated with a high speed spool and a second electric machine associated with a low speed spool. The method further includes receiving an indication of a failed electric machine, the failed electric machine being an electric machine on another hybrid electric turbine engine of the aircraft. The method further includes, responsive to detecting the failed electric machine, distributing power from one or more of the first electric machine or the second electric machine to a spool associated with the failed electric machine.

A method is provided for use in maintenance of a vehicle. The method includes an onboard computer including an onboard reasoner diagnosing a failure mode onboard the vehicle using an onboard diagnostic model. The onboard reasoner further determines a service recommendation of a service action to address the failure mode. The method also includes an off-board computer including an off-board copy of the onboard reasoner receiving a measure of fix effectivity of the service action as performed to address the failure mode. The off-board copy diagnoses the failure mode or an alternate failure mode, from the measure of fix effectivity of the service action, and using an off-board copy of the onboard diagnostic model. Responsive to diagnosis of the alternate failure mode, the off-board copy determines a maintenance recommendation of a maintenance action to address the alternate failure mode, and generating a maintenance message including the maintenance recommendation.

An engine-mounted component life cycle data tracking system is provided. The system includes a plurality of RFID tags associated with, positioned proximate to, and configured to transmit and store identification, repair history, and dynamic data regarding a different engine component of a plurality of engine components, wherein the dynamic data includes engine usage, component usage, and/or component fault information. The system further includes an aircraft-mounted controller that includes non-transient computer readable storage media. The controller is configured to: store identification and repair history data retrieved from the RFID tags in the storage media; store dynamic data for the plurality of engine components in the storage media after each engine cycle; and transmit dynamic data to the RFID tags after each engine cycle for storage. After each engine cycle, the aircraft-mounted controller includes in its storage media the identification, repair history and dynamic data for the plurality of engine component.

A remote sensor data acquisition system for an aircraft includes a plurality of remote sensors co-located onboard the aircraft and adapted to measure one or more aircraft-related parameters. A remote sensor interface is co-located with the plurality of remote sensors. The remote sensor interface includes a communication bus having a plurality of nodes to transmit data from the plurality of remote sensors. A plurality of subsystems are each adapted to receive data from the plurality of remote sensors simultaneously and in real time via the remote sensor interface. A remote sensor data acquisition method for an aircraft includes sensing one or more parameters onboard the aircraft via a plurality of remote sensors and transmitting sensor data from the plurality of remote sensors to a plurality of subsystems independently and in real time via a remote sensor interface.

A method of monitoring the condition of an aircraft landing gear shock absorber, the shock absorber including at least one spring chamber containing a gas, the method comprising taking a plurality of measurements of the gas pressure and temperature, each gas pressure and temperature measurement pair being taken of at the same instant relative to an operating cycle of the shock absorber; calculating, based on each pair of gas pressure and temperature measurements, a first value; storing the first value in a log; determining a value trend based on the log; and in response to determining that the value trend is outside a first range of values, generating a first notification signal.