Event Detection Battery Analysis with Predictive Capacity Alerts
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Solution Overview
Problem
Existing battery capacity testing methods for event detection systems are time-consuming, technically demanding, and prone to false readings, leading to costly and unplanned site visits, especially due to variations in battery performance characteristics from different manufacturers and deployment environments.
Innovation Solution
Implementing a controller to record battery characteristics at intervals and use a prediction model, such as an equivalent circuit model or machine-learning model, to predict when battery performance will exceed a threshold, allowing for remote, frequent, and accurate capacity measurements and alerts for timely replacement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional battery capacity testing methods are used, then battery performance can be measured, but the process is time-consuming and requires technical expertise leading to costly site visits
Solution Approach 1:
The patent replaces traditional manual battery capacity testing methods with an automated electronic system that uses the control panel's existing processor and communication interfaces. The system automatically applies standardized test loads, measures battery voltage responses, and calculates capacity without requiring physical site visits or manual intervention, thereby eliminating time loss while maintaining measurement accuracy.
Solution Approach 2:
The control panel performs battery capacity testing autonomously using its own processor, memory, and communication capabilities. The system automatically schedules tests, applies test loads through internal circuitry, records measurements, and generates reports without external assistance. This self-service approach eliminates the need for technician site visits while maintaining precise measurements.
2Measurement precision
If traditional battery testing is performed, then capacity can be assessed, but false readings occur due to manufacturer and environmental variations
Solution Approach 1:
The patent transforms battery capacity assessment from direct measurement to indirect calculation based on voltage response characteristics during standardized load tests. By measuring voltage decay rates and applying correction algorithms that account for temperature, age, and manufacturer variations, the system achieves consistent and accurate capacity assessments across diverse battery types and environmental conditions without false readings.
Solution Approach 2:
The system performs preliminary characterization of battery behavior by conducting standardized test sequences that capture voltage responses under controlled load conditions. These preliminary measurements establish baseline performance metrics and enable the development of manufacturer-specific and environment-specific correction factors, ensuring reliable capacity assessments across varying conditions.
3Reliability
If frequent battery monitoring is implemented, then timely replacement can be predicted, but system complexity increases
Solution Approach 1:
The patent leverages the control panel's existing multi-functional capabilities - using its processor for both event detection and battery analysis, its communication interfaces for both alarm signaling and test data transmission, and its power management circuitry for both system operation and battery testing. This universal approach enables frequent monitoring without adding dedicated monitoring hardware or increasing overall system complexity.
Solution Approach 2:
The system combines battery capacity testing with the control panel's existing operational functions by integrating test load application through the same power circuitry used for alarm devices and using the same communication protocols for transmitting both event data and battery status. This merging of functions enables continuous monitoring while avoiding duplicate components and maintaining system simplicity.
Data Source
AI summary
Devices, systems, and methods for battery analysis in an event detection system are described herein. In some examples, one or more embodiments include a processor to record a characteristic of a battery in a control panel of the event detection system at predetermined intervals, determine, by the processor via a prediction model using the recorded characteristics, a trend associated with an performance characteristic of the battery, and generate, by the processor, an alert based on the trend associated with the performance characteristic.