Central Control System for Autonomous Vehicle Fuel Management
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Solution Overview
Problem
Existing systems for managing fuel levels in autonomous vehicles, such as electric vehicles, face inefficiencies due to reliance on user input and lack of comprehensive environmental data, leading to suboptimal resource consumption and potential errors in real-time environmental monitoring.
Innovation Solution
A computer-implemented control system that generates control signals for remotely-located interaction units via a wide-area communications network, processing requests for control parameters based on environmental requirements by classifying external and local environmental parameters, calculating their impact, and adjusting resource usage accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user input is used to control system operation, then system adaptability to user preferences is improved, but system reliability and operational efficiency deteriorate due to human error and incomplete information
Solution Approach 1:
The system performs self-monitoring of environmental conditions and self-adjustment of operational parameters without requiring continuous user input. The central control system automatically detects environmental changes and modifies system operation accordingly, enabling the system to serve itself while maintaining user preference alignment through automated decision-making
Solution Approach 2:
The system implements continuous feedback loops where environmental sensors monitor conditions in real-time, the central control system processes this information, and operational parameters are automatically adjusted based on the feedback. This closed-loop control ensures the system responds dynamically to environmental changes while maintaining reliability through automated correction of operational deviations
2Productivity
If local changes are made by users to optimize system operation, then local operational efficiency may be improved, but overall system performance deteriorates due to lack of comprehensive system information
Solution Approach 1:
The central control system serves multiple functions simultaneously: it monitors environmental conditions, processes data from multiple sources, makes operational decisions, and coordinates system-wide operations. This multi-functional approach ensures that local optimizations do not conflict with overall system performance, as the central system maintains a holistic view and coordinates all operational changes
3Productivity
If automated control systems are implemented, then operational efficiency is improved, but system complexity increases requiring more sophisticated monitoring and control mechanisms
Solution Approach 1:
The control system is segmented into distinct functional modules: environmental sensors for data collection, a central control unit for processing and decision-making, and actuators for implementation. This modular segmentation reduces overall system complexity by allowing each component to be designed, tested, and maintained independently while working together to achieve automated control
Data Source
AI summary
A computer-implemented control system for generating control signals for controlling one or more remotely-located interaction units via a wide-area communications network is described. The control system comprises: a request interface processor for receiving a request for a control signal of a requested control parameter (RCP) relating to a specified environmental requirement (SER) from one of the one or more remotely-located interaction units; the request including: a current value of the RCP, a specified value of the SER; and current values of one or more local environmental parameters (local CERs) related to the SER.