Wireless Power Pairing Using Quality Metrics and Dynamic Reassignment
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Solution Overview
Problem
Current wireless power transmission systems lack an efficient method to optimize pairings between wireless power transmission systems (WPTSs) and wireless power receiver clients (WPRCs), as existing solutions do not effectively evaluate and adjust pairings based on changing conditions such as position, orientation, power needs, and delivery capabilities.
Innovation Solution
Implementing a pairing quality metric analyzer (PQMA) within WPRCs or WPTSs to determine and adjust pairings based on position, orientation, and power-related metrics, ensuring optimal wireless power delivery by selecting the most suitable WPTS for each WPRC, even in dynamic environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wireless power transmission systems use fixed pairing methods, then system complexity is reduced, but power delivery efficiency deteriorates due to inability to adapt to changing conditions
Solution Approach 1:
The patent implements dynamic pairing by continuously monitoring position and orientation information of WPRCs and automatically adjusting pairings based on real-time conditions. The system transitions from static to dynamic pairing management, where pairings are not fixed but adapt continuously to optimize power delivery efficiency while maintaining manageable complexity through automated decision-making algorithms.
Solution Approach 2:
The system employs feedback mechanisms by monitoring pairing quality metrics, position changes, orientation changes, and power delivery performance. This feedback loop enables the system to evaluate current pairing effectiveness and automatically initiate re-pairing operations when optimization opportunities are detected, thereby improving power delivery efficiency without requiring complex manual intervention.
2Productivity
If the system continuously monitors and adjusts pairings based on position and orientation, then power delivery optimization improves, but computational complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing position and orientation thresholds that trigger pairing evaluations. Instead of continuously processing all possible optimization scenarios, the system sets up predetermined conditions and only initiates complex processing when these conditions are met, thereby reducing overall computational complexity while maintaining effective power delivery optimization.
Solution Approach 2:
The patent utilizes parameter changes by monitoring specific thresholds in position and orientation data. When these parameters change beyond predetermined thresholds, the system triggers pairing re-evaluation. This approach converts continuous monitoring into discrete event-driven processing, significantly reducing computational complexity while preserving the ability to optimize power delivery when actually needed.
3Reliability
If pairing decisions are made based on multiple metrics (position, orientation, power needs, delivery capability), then pairing quality improves, but the time required for decision-making increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing weighting factors and decision rules for each pairing metric (position, orientation, power needs, delivery capability). When a pairing evaluation is triggered, these pre-defined parameters are immediately applied without requiring complex real-time calculations, thereby maintaining high pairing quality while minimizing decision-making time.
Solution Approach 2:
The system implements self-service by having WPRCs and WPTS autonomously evaluate pairing quality using pre-configured metrics and automatically execute pairing decisions without external intervention. This autonomous decision-making process, guided by predetermined rules, enables rapid pairing optimization based on multiple metrics simultaneously, reducing the time loss associated with manual or centralized decision-making.
4Adaptability or versatility
If the system re-evaluates pairings upon detecting events (position changes, orientation changes, power need changes), then adaptability improves, but the frequency of pairing changes and system instability increases
Solution Approach 1:
The patent applies beforehand cushioning by implementing hysteresis thresholds and minimum time intervals between pairing changes. When events trigger pairing re-evaluation, the system checks whether the change exceeds a cushioning threshold and whether sufficient time has elapsed since the last pairing change. This prevents minor fluctuations from causing excessive pairing changes, maintaining system stability while preserving adaptability to significant environmental changes.
Data Source
AI summary
Described herein are embodiments of apparatuses and methods for optimizing pairing of a wireless power transmission system (WPTS) with a wireless power receiver client (WPRC) in a localized system. A current WPTS-WPRC pairing and at least one alternate WPTS-WPRC pairing are assessed and the WPTS-WPRC pairing is updated based on associated pairing quality metrics. In this way, a system of many WPTSs and WPRCs will approach an Epsilon equilibrium such that no WPRC would be significantly better served by being paired with a different WPTS.