A system for predicting degradation of a battery for use in an electric vehicle id presented. The system includes a computing device communicatively connected to at least a pack monitor unit, wherein the at least a pack monitor unit is configured to detect a battery pack datum of a plurality of battery modules incorporated in a battery pack. The computing device is further configured to receive the battery pack datum as a function of the at least a pack monitor unit, generate, as a function of the battery pack datum, a battery pack model associated with the battery pack of the electric vehicle, and determine a battery degradation prediction as a function of the battery pack datum and the battery pack model.

Systems and vehicle are provided. A vehicle system for a vehicle includes: a trajectory selection module configured to select a potential vehicle path relative to a current vehicle movement condition; a trajectory movement condition module configured to estimate a modeled movement condition of the vehicle along the potential vehicle path; a limit comparison module configured to determine whether the modeled movement condition violates vehicle limits; and a violation indicator module configured to generate an indication of impending violation.

The application relates to an aircraft, a method, an apparatus and a computer readable storage medium for controlling the aircraft with at least one sensor arranged thereon, the method including detecting a motor state of the aircraft, acquiring at least one sensing data of the at least one sensor, and controlling the aircraft to perform a startup operation or a shutdown operation according to the motor state and the at least one sensing data, so that the aircraft can be autonomously controlled to perform the startup operation or the shutdown operation, and the user experience is improved.

A method includes obtaining sensor data captured by a sensor of an aircraft during a power up event. The sensor data includes multiple parameter values, each corresponding to a sample period. The method further includes determining a set of delta values, each indicating a difference between parameter values for consecutive sample periods of the sensor data. The method further includes determining a set of quantized delta values by assigning the delta values to quantization bins based on magnitudes of the delta values. The method further includes determining a normalized count of delta values for each quantization bin. The method further includes comparing the normalized counts of delta values to anomaly detection thresholds. The method further includes generating, based on the comparisons, output indicating whether the sensor data is indicative of an operational anomaly.

A method includes obtaining sensor data captured by a sensor of an aircraft during a power up event. The sensor data includes multiple parameter values, each corresponding to a sample period. The method further includes determining a set of delta values, each indicating a difference between parameter values for consecutive sample periods of the sensor data. The method further includes determining a set of quantized delta values by assigning the delta values to quantization bins based on magnitudes of the delta values. The method further includes determining a normalized count of delta values for each quantization bin. The method further includes comparing the normalized counts of delta values to anomaly detection thresholds. The method further includes generating, based on the comparisons, output indicating whether the sensor data is indicative of an operational anomaly.

The system, configured for being on board an aircraft, includes a probe for collecting samples of contrail, a chamber for collecting the samples, a collecting conduit for conducting the samples from the collecting probe the collecting chamber and at least one device for measuring at least one parameter characterizing the samples in the collecting conduit while they are conducted from the collecting probe to the collecting chamber. By virtue of the system, it is not necessary to use a second aircraft that follows the aircraft for collecting samples of contrail.

The aircraft take-off awareness system predicts and informs the pilot about where on the runway certain safety speeds will be achieved. A processor coupled to receive inertial data from the aircraft computes an aircraft weight estimate based at least in part upon the inertial data. The processor then computes a future acceleration prediction based on the computed aircraft weight estimate. Using the future acceleration prediction, the processor then computes the position of various warning reference distances corresponding to predicted positions on the runway at which said certain safety speeds will be achieved. The processor generates a display that it dynamically updates as the reference distances change as the aircraft proceeds down the runway during take-off or aborted take-off.

The aircraft take-off awareness system predicts and informs the pilot about where on the runway certain safety speeds will be achieved. A processor coupled to receive inertial data from the aircraft computes an aircraft weight estimate based at least in part upon the inertial data. The processor then computes a future acceleration prediction based on the computed aircraft weight estimate. Using the future acceleration prediction, the processor then computes the position of various warning reference distances corresponding to predicted positions on the runway at which said certain safety speeds will be achieved. The processor generates a display that it dynamically updates as the reference distances change as the aircraft proceeds down the runway during take-off or aborted take-off.

An electrical architecture of an aircraft includes a plurality of primary generators each associated with a propulsion engine of the aircraft, a plurality of primary electrical networks each associated with a primary generator in nominal operating mode, a single-part secondary electrical network, an electrical energy accumulation device connected directly to the secondary network, a first electrical energy converter arranged between the secondary electrical network and a first of the primary electrical networks, allowing energy to be transferred from the first of the primary electrical networks to the secondary electrical network, the first electrical energy converter being intended to supply electrical energy to the electrical energy accumulation device in nominal operating mode, a second electrical energy converter arranged between the secondary electrical network and a second of the primary electrical networks, allowing energy to be transferred from the secondary electrical network to the second of the primary electrical networks.

Flight equipment according to an embodiment of the present invention includes: an aerial vehicle having a body and at least one rotor held on the body; a plurality of supporters mounted to the aerial vehicle and supporting a protective member stretched therebetween so as to surround an outside of the body; a support information detection unit configured to detect support information indicating a support state of the protective member; and a mounting state determiner configured to determine whether the support state of the protective member is suitable or unsuitable, based on a value detected by the support information detection unit.