Connected Object Runtime Prediction for Renewable Power Variability
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Solution Overview
Problem
Connected objects powered by renewable energy sources face challenges in managing energy consumption due to unpredictable energy production, often requiring oversizing of energy production or storage capacities to avoid failure, which is not satisfactory for all applications.
Innovation Solution
A method and system for predicting the operating time of connected objects with batteries by measuring energy stored, instantaneous energy consumption, and ambient energy availability, allowing for precise estimation of lifespan and implementation of adaptive actions such as modifying energy consumption modes, data backup, or alerting when the predicted operating time is insufficient for tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If energy production or storage capacities are oversized to reduce failure risk, then reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent implements dynamic adjustment of energy consumption modes based on real-time operating time predictions. The connected object adapts its energy usage patterns according to predicted battery lifespan and renewable energy availability, replacing static oversized capacity designs with dynamic operational adjustments. This resolves the contradiction by maintaining reliability through adaptability rather than through fixed oversizing of energy capacities.
Solution Approach 2:
The system changes operational parameters (energy consumption modes, task scheduling, communication frequency) based on predicted operating time and energy availability. Instead of changing physical parameters like battery size or panel area, the patent modifies operational characteristics to achieve reliable operation with appropriately sized energy components, thereby reducing device complexity while maintaining reliability.
2Duration of action of stationary object
If energy production or storage capacities are oversized to ensure continuous operation, then duration of action is improved, but loss of energy increases
Solution Approach 1:
The patent applies partial action by adjusting energy consumption to match actual needs rather than maintaining constant high-capacity operation. The system performs tasks at reduced intensity or delays non-critical operations when energy is scarce, avoiding the energy waste associated with oversized capacity operation while still achieving required operating durations for critical functions.
Solution Approach 2:
The system implements periodic monitoring and adjustment of energy consumption patterns based on predicted operating time. Energy-intensive tasks are scheduled periodically when energy availability is favorable, and consumption modes are adjusted in periodic cycles to optimize the balance between operating duration and energy efficiency, reducing overall energy waste compared to continuous high-power operation.
Data Source
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AI summary
This method for predicting the operating time (DF) of a connected object (100) includes: - a step (E20) of obtaining an instantaneous quantity of energy consumed (ECi) by the connected object (100); - a step (E40) of obtaining at least one instantaneous quantity of energy (EA, EPi) dependent on an ambient energy (EA), and which can be used to power said connected object (100); - a step (E70) of obtaining a remaining lifetime (DV) of the connected object (100) as a function of said quantities (EPi, ECi); - a step (E80) of obtaining said predicted operating time (DF) of the connected object (100) as a function of said remaining lifetime (DV); and - a step (E100) of implementing at least one action taking into account (E90) said predicted operating time (DF).