Robotic EV Charging Coordination for Multi-Vehicle Factory Fleets
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Solution Overview
Problem
Efficiently managing the movement of multiple electric vehicles to charging stations for optimal charging in a manufacturing environment is resource and time-intensive.
Innovation Solution
A robotic charging system comprising a central control system that obtains vehicle, charging station, and robot data to efficiently navigate vehicles to available charging stations based on energy levels, selecting appropriate robots and stations for charging routines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual control methods are used to manage multiple electric vehicles at charging stations, then operational flexibility is maintained, but resource consumption and time requirements increase significantly
Solution Approach 1:
The system enables autonomous vehicles to self-report their energy levels and automatically navigate to charging stations based on their own needs. The robotic device autonomously performs charging operations without human intervention, allowing the system to serve itself and eliminating the need for manual management of multiple vehicles.
Solution Approach 2:
The patent replaces manual mechanical control with an automated control system that uses sensors, processors, and communication networks. The robotic charging device uses automated navigation and vehicle-to-infrastructure communication to substitute human-operated mechanical processes with electronic and automated systems.
2Adaptability or versatility
If multiple charging stations are deployed to serve all vehicles, then charging availability improves, but system complexity and resource consumption increase
Solution Approach 1:
The system dynamically assigns vehicles to charging stations based on real-time conditions such as vehicle energy levels, station availability, and route optimization. This dynamic allocation allows the system to adapt to changing conditions without requiring a fixed, complex infrastructure for every possible scenario.
Solution Approach 2:
The robotic charging device is designed to serve multiple charging stations and handle various vehicle types through a universal interface. This multi-functional capability allows a single robotic system to operate across multiple stations, reducing the need for station-specific equipment and simplifying the overall system architecture.
3Measurement precision
If vehicles are monitored continuously for energy levels, then charging timing accuracy improves, but data processing requirements and system complexity increase
Solution Approach 1:
Vehicles continuously monitor and report their energy levels in advance before reaching critical thresholds. This preliminary monitoring allows the system to plan charging assignments proactively, processing data in manageable increments rather than reacting to urgent situations, thereby reducing peak data processing loads.
Data Source
AI summary
A method includes obtaining vehicle data associated with the plurality of vehicles, obtaining charging station data associated with the plurality of charging stations, and obtaining robot data associated with the one or more robots. The method includes determining, based on the vehicle data, whether a given vehicle has a given amount of electrical energy that is less than a threshold amount of electrical energy. The method includes, in response to determining that the given amount of electrical energy is less than the threshold amount of electrical energy: selecting a given charging station based on the charging station data and a given robot based on the robot data, instructing the given vehicle and the given robot to navigate to the given charging station, and instructing the given robot to initiate a charging routine when the given vehicle and the given robot are proximate to the given charging station.