Autonomous Charging Robot Control for Reliable EV Coupling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Charging robots face challenges in accurately recognizing electric vehicles, coupling charging cables, and decoupling them, leading to malfunctions and impacting consumer demand for electric vehicles.
Innovation Solution
A charging robot control apparatus and method that determines a vehicle's parking state by identifying the vehicle type and position, using CCTV and LiDAR sensors, and controls the robot to charge the vehicle autonomously, applying offsets to ensure stable operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a charging robot is used to charge electric vehicles, then automation and convenience are improved, but recognition accuracy and coupling reliability deteriorate
Solution Approach 1:
The system performs preliminary recognition and verification of the vehicle's parking state before initiating charging. The control apparatus determines whether the vehicle is properly positioned and recognizable before the robot attempts coupling, preventing failed operations and improving reliability through advance validation.
Solution Approach 2:
The system continuously monitors the charging process and vehicle state, using feedback from sensors and recognition systems to adjust robot positioning and coupling actions. This closed-loop control ensures reliable coupling by responding to real-time conditions and correcting deviations from the expected charging sequence.
2Ease of operation
If the charging robot autonomously determines parking state, then manual intervention is reduced, but measurement precision deteriorates
Solution Approach 1:
The control apparatus integrates multiple sensing and recognition functions into a single system that can identify vehicle presence, determine parking state, and guide the charging robot. This multi-functional approach maintains precision by combining complementary technologies (image recognition, sensor data) rather than relying on a single imperfect method.
Solution Approach 2:
The control apparatus acts as an intermediary between the autonomous robot and the vehicle, processing recognition data and making determination decisions. This intermediate layer enhances measurement precision by filtering, validating, and interpreting raw sensor data before acting on it, reducing errors from direct autonomous operation.
3Stability of the object's composition
If the robot arm position is adjusted with offset, then charging stability is improved, but system complexity increases
Solution Approach 1:
The system adjusts the robot arm position by applying offset values to coordinate transformations. This parameter adjustment approach improves charging stability by compensating for positioning errors and variations in vehicle placement, achieving precise coupling through mathematical corrections rather than mechanical modifications.
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
Enhances the accuracy and stability of charging processes, reducing errors and improving user experience by enabling autonomous charging without manual intervention.
Implementation Method 1
receive a parking position of the target vehicle, the parking position being determined by a light detection and ranging (LiDAR) sensor
Data Source
AI summary
A charging robot control apparatus can include a memory storing computer-executable instructions and at least one processor that accesses the memory and executes the instructions. The at least one processor determines a parking state of a target vehicle by means of a vehicle type of the target vehicle and a parking position of the target vehicle, based on identifying the target vehicle, controls a charging robot to charge the target vehicle, based on determination that the parking state is a state in which the charging robot is able to charge the target vehicle, and controls the charging robot to disconnect a connection between a charger and the target vehicle, based on a state of charge (SOC) of the target vehicle.