Autonomous EV Charging Port Alignment With Dynamic Camera Adjustment
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Solution Overview
Problem
Current charging systems for electric vehicles require manual intervention, leading to inefficient and tedious charging processes, as they lack the technical sophistication to accurately and efficiently establish physical connections between charging stations and vehicles.
Innovation Solution
A computerized framework utilizing an Automated Connection Device (ACD) with cameras and sensors, leveraging AI and machine learning algorithms, such as Convolutional Neural Networks, to autonomously identify and connect with the vehicle's charging receptacle, adjusting camera parameters for precise alignment and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual connection methods are used for charging EVs, then operational simplicity is maintained, but charging efficiency and productivity are reduced
Solution Approach 1:
The system enables autonomous charging where the ACD automatically connects to the EV charging port without human intervention. The robot navigates to the vehicle, positions the charging cable, and establishes the electrical connection independently, allowing the charging infrastructure to serve itself rather than requiring manual operation.
Solution Approach 2:
The patent replaces manual mechanical connection operations with an automated robotic system. The ACD uses computer vision, sensors, and controlled mechanical movement to perform the charging connection task that previously required human hands and coordination, substituting human-operated mechanical systems with automated ones.
2Measurement precision
If existing robot systems are used for autonomous charging, then manual intervention is reduced, but connection accuracy and reliability are insufficient
Solution Approach 1:
The system introduces multiple intermediary components between the ACD and the charging port to achieve precise alignment. These include computer vision cameras that capture images of the charging port, image processing algorithms that identify the target location, and sensor feedback systems that guide the robotic arm's movement, creating a multi-stage intermediary process that bridges the gap between rough positioning and precise connection.
Solution Approach 2:
The system employs dynamic adjustment mechanisms where the ACD continuously adapts its positioning based on real-time feedback from cameras and sensors. The robotic arm can make fine adjustments to its trajectory and the charging cable angle during the connection process, allowing the system to compensate for positioning errors and achieve accurate alignment despite initial uncertainties.
3Adaptability or versatility
If autonomous connection systems are implemented, then operational efficiency is improved, but adaptability to different EV models and environmental conditions is reduced
Solution Approach 1:
The ACD is designed with universal capabilities to handle multiple EV models and charging port types. The system uses image recognition technology that can identify different charging port configurations, and the robotic arm can adjust its movement patterns to accommodate various vehicle shapes and port locations, enabling a single system to serve multiple functions across different EV models without requiring model-specific configurations.
Solution Approach 2:
The system performs preliminary scanning and identification of the charging port and vehicle configuration before attempting the connection. The cameras capture images of the EV and its charging port in advance, allowing the system to plan its approach trajectory and cable routing in advance, which enables adaptation to different vehicle types without requiring complex real-time decision-making during the actual connection process.
Data Source
AI summary
The disclosed systems and methods provide a novel framework that provides mechanisms for a hands-free, autonomous electrical connection of an electric charger to an electric vehicle (EV), and subsequent charging. The disclosed framework utilizes an automated connection device (ACD) as an intermediary between the charger and the EV. The ACD is configured for automatically determining a precise location of the charging inlet on the EV and then automatically establishing an electrical connection with the EV so that the EV can receive a charge. The ACD performs the disclosed precise positional and directional navigation to the EV inlet based on deep neural network analysis of captured imagery of the inlet. In some embodiments, the images can be modified so as to highlight and/or assist the ACD's navigation towards to the inlet in order to maximize invariance.