Battery Performance Prediction Model for Extreme Temperature Environments
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Solution Overview
Problem
Existing battery performance prediction methods are inadequate for extreme temperature environments and low discharge rates, particularly in seismic exploration, where batteries experience significant capacity decay and mechanical stresses, leading to unreliable performance and safety issues.
Innovation Solution
A method and system that characterize battery performance by integrating environmental condition data, such as temperature, with operating parameters using a performance model, which includes location-specific information and sensor data to predict battery capacity, lifetime, and health, enabling accurate performance evaluation beyond standard operating parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If battery testing is performed within predetermined parameters or designed operational specifications, then testing can be completed in a reasonable time frame, but the prediction accuracy for extreme temperature environments and low discharge rates is insufficient
Solution Approach 1:
The patent applies preliminary action by conducting accelerated aging tests and capacity cycling tests at extreme temperatures and low discharge rates before actual deployment. This preliminary characterization of battery behavior under extreme conditions allows for the development of correction factors and performance models that can predict battery life in seismic exploration environments without requiring extensive field testing.
Solution Approach 2:
The patent utilizes parameter changes by systematically varying temperature parameters (from −40°C to +60°C) and discharge rate parameters (from 0.003C to 1C) during testing phases. By characterizing battery performance across this expanded parameter space, the invention creates a comprehensive performance model that can accurately predict battery behavior in extreme conditions without requiring exhaustive testing of every possible scenario.
2Adaptability or versatility
If batteries are used in extreme cold temperatures below −20°C, then seismic exploration can be conducted in remote locations, but capacity decay is significantly accelerated
Solution Approach 1:
The patent implements feedback by continuously monitoring battery temperature, charge state, and performance metrics during operation in extreme environments. This real-time feedback is used to adjust operational parameters and apply temperature-specific correction factors to capacity predictions, allowing the system to adapt to actual battery behavior and maintain reliable performance estimates despite extreme cold temperatures.
Solution Approach 2:
The patent applies dynamics by creating a dynamic performance model that adjusts battery capacity predictions based on real-time environmental conditions and usage patterns. Rather than using static capacity values, the system continuously updates performance predictions based on actual temperature profiles, discharge rates, and aging effects observed during deployment in extreme cold environments.
3Duration of action of moving object
If low discharge rates of a few mA are used in seismic data acquisition devices, then extended operation is possible, but testing duration must be significantly extended to obtain useful results
Solution Approach 1:
The patent applies preliminary action by conducting accelerated capacity cycling tests at higher discharge rates to establish baseline aging characteristics, then using mathematical models to extrapolate performance at the actual low discharge rates of seismic devices. This approach allows the invention to predict long-term battery life at ultra-low discharge rates without requiring years of actual field testing.
Solution Approach 2:
The patent uses an intermediary approach by introducing performance models and correction factors that bridge the gap between accelerated test conditions and actual low-rate operational conditions. These intermediary models translate results from accelerated testing at higher discharge rates into accurate predictions for the actual low discharge rate applications, eliminating the need for extremely long testing durations.
Data Source
AI summary
A method of determining battery performance information indicative of a performance of a battery in a device is disclosed, the method including: receiving environmental condition information indicative of environmental conditions of the device during a usage period; receiving operating parameter information indicative of one or more operating parameters of the battery during the usage period; and determining the battery performance information based at least in part on: the environmental condition information, the operating parameter information, and a performance model corresponding to the battery.