Wireless Charging Pad Alignment for Urban Air Mobility
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Solution Overview
Problem
Efficient wireless charging of urban air mobility vehicles is hindered by the need for precise alignment between the wireless power receiver and transmitter, which is challenging due to the dynamic and autonomous nature of these vehicles, especially in urban environments with limited infrastructure.
Innovation Solution
A method and system for aligning wireless power transceivers using various sensors, including GPS, ultrasonic sensors, cameras, and LiDAR, to adaptively select and drive the alignment process based on the vehicle's state and environment, enabling efficient charging by pairing with user devices and smart keys for primary and fine alignments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If wireless charging is implemented for urban air mobility vehicles, then charging convenience is improved, but alignment precision between power transmitter and receiver deteriorates due to dynamic vehicle movement
Solution Approach 1:
The system performs preliminary alignment actions by predicting the vehicle's future position based on current movement state (speed, direction) and pre-adjusting the power transmitter's beam direction and focus before the vehicle arrives at the charging position. This proactive alignment ensures precise power transfer despite vehicle dynamics.
Solution Approach 2:
The system continuously monitors vehicle position, movement state, and power transfer efficiency, then dynamically adjusts the power transmitter's beam parameters in real-time. This closed-loop feedback mechanism maintains alignment precision by compensating for vehicle movement and environmental disturbances during charging.
2Measurement precision
If multiple sensors are used for alignment, then alignment precision is improved, but device complexity increases
Solution Approach 1:
The alignment system is divided into multiple independent sensor modules, each responsible for specific measurement tasks (positioning, orientation, distance). This modular segmentation allows selective activation of sensors based on operational conditions, reducing overall system complexity while maintaining precision.
Solution Approach 2:
The system employs sensors with multi-functional capabilities that can perform multiple measurement tasks simultaneously. For example, certain sensors can provide both positioning and orientation data, reducing the total number of sensors needed while maintaining alignment precision.
3Use of energy by moving object
If adaptive sensor selection is implemented, then energy consumption is reduced, but control complexity increases
Solution Approach 1:
The sensor activation strategy dynamically adapts to current operational conditions such as vehicle movement state, environmental factors, and charging phase. The system transitions between different sensor configurations based on real-time requirements, optimizing energy consumption while managing control complexity through condition-based logic.
Data Source
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AI summary
The present disclosure relates to an in-place alignment method for wireless charging of an urban air mobility and a device and a system therefor. A wireless charging method includes acquiring location information of a supply device for supplying wireless power, moving an urban air mobility to the supply device based on the location information, performing pairing with a user equipment (UE) based on a distance from the urban air mobility to the supply device, aligning a wireless power receiving pad of the urban air mobility and a wireless power transmitting pad of the supply device based on a control signal of the paired UE, and charging a battery of the urban air mobility by receiving wireless power from the supply device. The present disclosure maximizes a wireless charging efficiency and minimizes a power waste by quickly and accurately aligning pads of the urban air mobility and the supply device.