Autonomous Vehicle Charging Subsystem with Cloud-Network Integration
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Solution Overview
Problem
Current autonomous vehicle systems lack an integrated platform for user-free, semi-autonomous battery charging, which is essential for efficient routine maintenance and user convenience.
Innovation Solution
A system comprising a user interface, an autonomous vehicle (AV) with processing circuitry, and a cloud-connected network of charging stations, allowing for continuous battery charge monitoring, recommendation of charging stations, reservation of charging ports, navigation to the station, and secure authentication for wireless or conductive charging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If autonomous vehicle systems implement integrated semi-autonomous charging platforms, then user convenience and operational efficiency are improved, but system complexity increases
Solution Approach 1:
The charging system is divided into distinct functional modules: monitoring module that tracks battery charge levels, recommendation module that identifies suitable charging stations, reservation module that secures charging ports, and navigation module that guides the vehicle to the station. Each module operates independently but coordinates through a centralized control system, reducing overall system complexity while maintaining user convenience.
Solution Approach 2:
The system performs preliminary actions by continuously monitoring battery charge levels and pre-identifying suitable charging stations before the vehicle actually needs charging. The reservation module secures charging ports in advance, and navigation is prepared beforehand, allowing the vehicle to execute charging tasks autonomously without user intervention at the moment of need.
2Productivity
If the system performs continuous battery monitoring and autonomous charging navigation, then productivity is improved, but use of energy increases
Solution Approach 1:
The battery monitoring system operates periodically rather than continuously, checking charge levels at predetermined intervals or when threshold values are approached. The autonomous navigation and charging execution occur periodically when needed, rather than consuming energy continuously, thus maintaining productivity while reducing overall energy consumption.
Solution Approach 2:
The system incorporates feedback mechanisms where battery charge level data is continuously fed back to the control system, which then triggers navigation and charging actions only when necessary thresholds are reached. This feedback-driven approach ensures the vehicle performs charging tasks efficiently without wasteful energy consumption during normal operation.
3Adaptability or versatility
If the system integrates cloud-connected charging station networks, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system is designed with universal communication protocols and interfaces that can interact with multiple types of charging stations across different networks. The recommendation module can identify and accommodate various charging station types (conductive, inductive, different power levels), making the system adaptable to diverse charging infrastructure without requiring separate specialized systems for each station type.
Data Source
AI summary
The present disclosure relates to a system and methods for autonomous charging of an autonomous vehicle. Specifically, the present disclosure describes an autonomous vehicle subsystem configured to evaluate vehicle charge, identify possible charging stations, interact with a user to confirm a charging station, navigate to the selected charging station, and initiate and receive of a charge from a charging port at the charging station. User interaction may be vehicle-driven or user-driven.