Autonomous EV Charging Alignment Using Inlet Pose and Vehicle Positioning
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Solution Overview
Problem
Existing autonomous charging systems struggle to efficiently align and mate vehicle charging connectors with varying vehicle inlet features and parking positions, leading to potential damage and inefficiencies.
Innovation Solution
An autonomous charging device (ACD) utilizes vehicle inlet feature parameters and positioning data to determine a pose strategy, employing a robotic arm and computer vision, optimizing the alignment and mating process through a predetermined model that includes neural networks and algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual charging connection methods are used, then operational simplicity is maintained, but charging efficiency and user convenience deteriorate due to required manual intervention
Solution Approach 1:
The autonomous charging device performs self-positioning, self-alignment, and self-mating operations without human intervention. The robotic arm autonomously navigates to the vehicle, positions the charging connector, and executes the mating process, enabling the system to serve itself and eliminating the need for manual charging connection
Solution Approach 2:
The patent replaces manual mechanical operations with an automated robotic system equipped with sensors, computer vision, and control algorithms. The robotic arm with gripper substitutes human hands, while vision systems and positioning sensors replace human perception and decision-making, achieving autonomous charging connection
2Adaptability or versatility
If autonomous charging systems use fixed alignment strategies, then device complexity is reduced, but adaptability to varying vehicle inlet features and parking positions deteriorates
Solution Approach 1:
The system employs dynamic adaptation by adjusting its alignment and mating strategies in real-time based on detected vehicle inlet features and parking positions. The robotic arm dynamically modifies its trajectory, positioning, and insertion force according to the specific vehicle configuration, enabling versatile handling of different vehicle types and parking scenarios
Solution Approach 2:
The system performs preliminary detection and planning by capturing images of the vehicle inlet, identifying its features and position before executing the mating operation. This advance assessment allows the system to pre-calculate the optimal alignment strategy and adjust the robotic arm's path accordingly, ensuring adaptability without requiring complex real-time adjustments during insertion
3Measurement precision
If visual determination of inlet pose is performed without prior information, then measurement independence is maintained, but measurement precision and alignment accuracy deteriorate
Solution Approach 1:
The system receives and processes vehicle information (such as inlet features and positioning data) before performing visual determination of the inlet pose. This preliminary data acquisition and processing enables the vision system to focus its analysis on specific regions and features, significantly improving measurement precision while reducing the overall time required for pose determination
Solution Approach 2:
The system uses received vehicle information as feedback to guide and refine the visual determination process. By comparing expected inlet positions and features with actual visual data, the system can iteratively improve pose accuracy, resolving the trade-off between measurement precision and time consumption
4Manufacturing precision
If connector alignment is performed without considering vehicle positioning parameters, then operational simplicity is maintained, but manufacturing precision and mating accuracy deteriorate
Solution Approach 1:
The system introduces vehicle positioning parameters as an intermediary layer between the robotic arm and the vehicle inlet. These parameters (such as vehicle location, orientation, and inlet position) serve as a bridge that translates complex spatial relationships into actionable alignment instructions, enabling precise connector positioning without requiring direct complex geometric calculations
Data Source
AI summary
A method for controlling an autonomous charging device (ACD), the ACD configured to manipulate a vehicle charging connector and determine a pose of a vehicle charging inlet, and based on such pose determination, mating the charging connector into the vehicle charging inlet. The method comprises receiving information about the vehicle, wherein said information comprises at least one of an inlet feature parameter and a vehicle positioning parameter, acquiring at least one of a preset inlet pose determination strategy and a preset mating strategy by inputting the received vehicle information into a predetermined model, and controlling the ACD based, at least partly, on the acquired preset inlet pose determination strategy and/or preset mating strategy. The vehicle information can be received prior to a visual determination of the inlet pose.