Non-Rechargeable IoT Battery Life Estimation Using Temperature
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Solution Overview
Problem
Existing methods for estimating the remaining life of non-rechargeable batteries in IoT devices, such as lithium thionyl chloride batteries, are either power-consuming due to the use of discrete integrated processing components or inaccurate due to flat voltage discharge curves, making it difficult to predict battery failure in remote IoT devices.
Innovation Solution
Estimate remaining battery life by determining battery capacity usage based on environmental temperature during active and sleep modes, along with self-discharge, without relying on voltage measurements or fuel gauges, using temperature and duration information to calculate remaining capacity and life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discrete integrated processing components (fuel gauges) are used to estimate battery life, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent extracts the battery life estimation function from the device's main processing components. Instead of using a fuel gauge integrated into the device's processor, the system uses temperature sensors and environmental data collected by the device to estimate battery life remotely through a management server, eliminating the need for power-intensive integrated processing components.
Solution Approach 2:
The patent introduces a management server as an intermediary between the IoT device and the battery life estimation process. The server receives temperature and duration data from the device, performs calculations using battery discharge characteristics, and returns estimated battery life without requiring the device itself to perform power-intensive processing.
2Ease of operation
If voltage measurements are used to estimate battery life, then ease of operation is improved, but measurement precision deteriorates due to flat voltage discharge curves
Solution Approach 1:
The patent changes the measurement parameter from voltage to temperature. Instead of relying on voltage readings that remain flat throughout the battery discharge cycle, the system uses temperature data combined with known battery discharge characteristics to calculate remaining capacity, achieving both simplicity and accuracy.
Solution Approach 2:
The patent substitutes the voltage measurement approach with a thermal-based estimation method. By using temperature sensors and environmental data rather than voltage measurements, the system overcomes the limitation of flat voltage discharge curves while maintaining operational simplicity.
3Use of energy by moving object
If temperature-based estimation without fuel gauges is used, then use of energy is reduced, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent extracts the complex calculation logic from the device and places it in the management server. The device only collects simple temperature and duration data, while the server performs the complex battery discharge calculations using stored characteristic data, significantly reducing device processing requirements.
Solution Approach 2:
The patent uses pre-stored battery discharge characteristics and temperature-to-capacity conversion data in the management server. These pre-calculated lookup tables and models eliminate the need for real-time complex simulations on the device, reducing processing complexity while maintaining accuracy.
Data Source
AI summary
A method for estimating a remaining battery life of a non-rechargeable battery of an Internet of Things (IoT) device. The method includes determining an amount of battery capacity used by the IoT device while the IoT device was operating in an active mode, an amount of battery capacity used by the IoT device while the IoT device was operating in a sleep mode, and an amount of self-discharge of the non-rechargeable battery while the IoT was deployed based on temperatures of environments in which the IoT device was located. The method further includes determining an estimated remaining battery life of the non-rechargeable battery based on an initial capacity of the non-rechargeable battery, the amounts of battery capacity used by the IoT device while the IoT device was operating in the active mode and the sleep mode, and the amount of self-discharge of the non-rechargeable battery while the IT was deployed.