Model-Based Battery Replacement Scheduling for Wireless Devices
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Solution Overview
Problem
Existing methods for determining the proper battery replacement schedule for wireless devices in process control systems are inadequate, often leading to premature or overdue replacements due to varying power consumption rates and lack of accurate usage pattern analysis.
Innovation Solution
A model-based system that predicts the operating life of a power source by processing data related to the device's operation, including usage patterns, safety ratings, and industry standards, to provide a tailored replacement schedule.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If average expected transmitter behavior and average shelf life formulas are used to determine battery replacement schedules, then the replacement process is simplified, but the accuracy of battery life prediction deteriorates leading to premature or overdue replacements
Solution Approach 1:
The patent changes from using static average parameters (average transmitter behavior, average shelf life) to dynamic parameters that reflect actual device usage patterns. The system monitors real-world operational data including transmission frequency, data packet size, environmental conditions, and power consumption to create customized battery life predictions for each device, thereby improving accuracy without significantly increasing operational complexity
Solution Approach 2:
The patent implements a feedback mechanism where actual battery performance data and usage patterns are continuously monitored and fed back into the prediction model. This allows the system to refine and adjust battery life predictions based on real-world performance, improving accuracy over time while maintaining an automated scheduling process
2Device complexity
If battery replacement is based on low voltage indicators, then the monitoring process is simplified, but the reliability of battery operation deteriorates due to inability to predict actual remaining useful life
Solution Approach 1:
The patent replaces the simple voltage threshold monitoring mechanism with a computational model that processes multiple operational parameters. Instead of relying solely on electrical voltage measurements, the system uses software-based prediction algorithms that analyze usage patterns, environmental factors, and historical performance data to estimate remaining battery life, thereby improving reliability while keeping the physical monitoring hardware simple
Solution Approach 2:
The patent performs preliminary analysis of battery degradation trends and usage patterns to predict future battery status before actual voltage thresholds are reached. This allows the system to alert users in advance of battery depletion based on projected performance rather than waiting for voltage indicators, improving operational reliability
3Ease of manufacture
If uniform battery replacement schedules are applied to all wireless devices, then maintenance logistics are simplified, but productivity deteriorates due to devices being taken offline unnecessarily or remaining operational beyond safe limits
Solution Approach 1:
The patent applies the principle of local quality by customizing battery replacement schedules for each individual device based on its specific usage characteristics, environmental conditions, and performance patterns. Instead of a uniform schedule applied to all devices, the system generates location-specific and device-specific replacement timelines, ensuring that each device is maintained at the optimal moment for its particular operational context, thereby maximizing overall system productivity
Data Source
AI summary
A model-based system and method for analyzing power source performance and optimizing operational costs are provided. Data from the power source (such as a battery) and/or a device associated with the power source is analyzed and processed to predict an operating life of the power source. This could allow, for example, a power source replacement schedule to be generated for the device. If the analysis indicates that abnormal conditions exist or that any user-defined alerts are warranted, a message could also be sent to an operator terminal. The system and method may continue to monitor the device and thus provide real-time data. The data may also be stored in memory, collected over time, and analyzed or used in various ways. The system and method thus provide a cost effective and reliable analysis of power source performance and any associated operational and replacement costs.