Electric Aircraft Wireless Charging With Coil Alignment Authentication
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Solution Overview
Problem
Optimization of the recharging process for electric aircraft onboard battery systems poses challenges due to complexities in aligning and authorizing the charging process.
Innovation Solution
An electric vehicle charger equipped with a transmitter coil, proximity sensor, and computing device that aligns and authorizes charging through induction and authentication using a machine learning model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual alignment and authorization procedures are used for wireless charging, then device complexity is reduced, but productivity and charging efficiency deteriorate due to time-consuming operations
Solution Approach 1:
The system performs preliminary actions by pre-aligning the transmitter and receiver coils using proximity sensors and machine learning models before charging begins. The authentication process is also initiated in advance through communication between the charger and vehicle systems, ensuring that all preparatory steps are completed before the actual charging starts, thereby improving charging speed without requiring complex real-time adjustments during charging.
Solution Approach 2:
The system enables self-service through automated alignment and authorization processes. The machine learning model automatically adjusts coil positions based on sensor data, and the authentication system independently verifies vehicle identity and charging eligibility without manual intervention. This automation improves productivity while the self-adjusting nature of the system actually reduces operational complexity despite adding automated components.
2Productivity
If automated alignment using proximity sensors and machine learning is implemented, then productivity improves, but device complexity increases due to additional sensors and computing requirements
Solution Approach 1:
The computing device in the charger performs multiple functions: it runs the machine learning model for alignment, processes authentication data, controls the transmitter coil positioning, and manages communication with the vehicle system. By consolidating these diverse functions into a single multi-functional computing device, the system achieves high alignment efficiency while avoiding the complexity of multiple separate specialized components.
Solution Approach 2:
The machine learning model acts as an intermediary that processes raw sensor data from proximity sensors and translates it into precise alignment commands for the transmitter coil. This intermediary layer simplifies the overall system architecture by providing a unified intelligence layer that coordinates between sensors, actuators, and control systems, thereby improving alignment efficiency while managing complexity through abstraction.
3Loss of time
If authentication and identification processes are automated, then productivity improves by reducing manual authorization time, but device complexity increases due to additional computing and communication requirements
Solution Approach 1:
The system merges the authentication and identification processes into a single integrated workflow. The computing device simultaneously handles vehicle identification through sensors, authentication of the vehicle's charging eligibility, and authorization of the charging session. This consolidation reduces the total time required compared to sequential manual processes while managing complexity by combining multiple functions into one coordinated system rather than adding separate independent systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates efficient and automated alignment and authorization of electric aircraft charging, enhancing the recharging process by ensuring proper coil alignment and secure charging operations.
Implementation Method 1
The transmitter coil is configured to wirelessly conduct a current in a receiver coil using induction
Data Source
AI summary
An electric vehicle charger, comprising: a transmitter coil electrically connected to an energy source and configured to inductively couple to a receiver coil on the electric vehicle; a proximity sensor configured to generate alignment data regarding the receiver coil on the electric vehicle and the transmitter coil; and a computing device that is communicatively connected to the proximity sensor, wherein the computing device is configured to: identify the electric vehicle using an authenticated identification datum from the electric vehicle; align the transmitter coil with the receiver coil as a function of the alignment data; and initiate charging of the electric vehicle as a function of the authenticated identification datum.