Abstract:
An electric aircraft according to an embodiment of the present invention comprises: a fuselage equipped with a power means, a front spar and a rear spar extending from the fuselage to an end of a wing, and a plurality of ribs extending from the rear spar to the front spar and coupled to the front spar and the rear spar, in which a plurality of solid state batteries are mounted in a plurality of individual spaces partitioned by the front spar, the rear spar, and the plurality of ribs, respectively, and the front spar and the rear spar are used as members for serial connection of the plurality of solid state batteries, and the plurality of ribs are used as members for parallel connection of the plurality of solid state batteries.
Abstract:
A solar propelled aircraft which has a wing having solar cell modules mounted therein includes: first solar cell modules which are positioned in a wing or a tail wing of the aircraft and receive solar energy directly from the sun; second solar cell modules which are positioned in a main wing or a tail wing of the aircraft and supplied with directed energy from the earth; and rotating shafts which rotate the first solar cell modules and the second solar cell modules so that the first solar cell modules and the second solar cell modules correspond to each other in both directions. The first solar cell module at the upper surface obtains solar energy from the sun, and the second solar cell module at the lower surface obtains directed energy transferred from the earth.
Abstract:
A method for detecting anomalies in a swarm system comprises: collecting first movement data from multiple vehicles moving as a swarm in a first scenario; generating first training data based on positioning data and second training data based on multi-channel inertial sensor data from the first movement data; training a first learning model using the first training data and multiple second learning models using the second training data for each vehicle; receiving real-time second movement data from vehicles moving as a swarm in a second scenario; generating first input data based on positioning data from the second movement data; inputting the first input data into the first learning model to detect abnormal vehicles in real-time; generating second input data for abnormal vehicles based on inertial sensor data from the second movement data; and inputting the second input data into the corresponding second learning model to identify abnormal channels in the inertial measurement unit of abnormal vehicles.
Abstract:
An electric aircraft according to an embodiment of the present invention comprises: a fuselage equipped with a power means, a front spar and a rear spar extending from the fuselage to an end of a wing, and a plurality of ribs extending from the rear spar to the front spar and coupled to the front spar and the rear spar, in which a plurality of solid state batteries are mounted in a plurality of individual spaces partitioned by the front spar, the rear spar, and the plurality of ribs, respectively, and the front spar and the rear spar are used as members for serial connection of the plurality of solid state batteries, and the plurality of ribs are used as members for parallel connection of the plurality of solid state batteries.