CNNLSTM Battery Temperature Prediction for Thermal Runaway Warning
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Solution Overview
Problem
Current energy-storage power stations face challenges in reliable temperature monitoring due to single-point data from multiple temperature probes, leading to unreliable thermal runaway detection and potential false alarms, posing safety risks.
Innovation Solution
A thermal-runaway warning method and system utilizing a CNNLSTM-based temperature predicting model that collects and normalizes data from multiple temperature measuring devices, trains a model to predict battery module temperatures, and issues warnings based on predicted values and error thresholds, ensuring timely alerts for potential thermal abuse or runaway.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple temperature probes are used to monitor battery modules, then temperature monitoring coverage is improved, but measurement reliability deteriorates due to single-point data limitations and false alarms
Solution Approach 1:
The patent transitions from single-point temperature measurement to three-dimensional temperature field reconstruction. Multiple temperature probes distributed throughout the battery module measure temperatures at different spatial positions, and these measurements are used to reconstruct the complete temperature distribution field, enabling comprehensive monitoring coverage while maintaining high reliability through multi-point data fusion.
Solution Approach 2:
The patent introduces a temperature predicting model as an intermediary between raw temperature probe data and thermal runaway detection. The model processes and fuses data from multiple temperature probes, predicting temperatures at unmonitored locations and providing a comprehensive temperature assessment that improves detection reliability beyond what individual probes can achieve.
2Device complexity
If single-point temperature data from multiple probes is used, then device complexity is reduced, but measurement precision deteriorates leading to false alarms
Solution Approach 1:
The patent combines data from multiple temperature probes with a temperature predicting model to create a comprehensive temperature assessment system. By merging multiple single-point measurements and using the model to predict temperatures at unmonitored locations, the system achieves high measurement precision across the entire battery module while maintaining relatively simple probe deployment.
3Ease of operation
If traditional temperature monitoring based on single-point data is used, then ease of operation is improved, but reliability of thermal runaway detection deteriorates
Solution Approach 1:
The temperature predicting model operates autonomously, automatically processing temperature probe data and generating comprehensive temperature field information without requiring manual intervention. The system self-adjusts and continuously monitors, maintaining ease of operation while significantly improving detection reliability through intelligent data processing and prediction capabilities.
Data Source
AI summary
A thermal-runaway warning method, system, and terminal for a power station are provided. The method comprises: obtaining collected data of a battery module comprised in the power station, wherein the collected data comprises collected temperature values of the battery module collected by temperature measuring devices; normalizing the collected data to obtain a standard dataset; training a CNNLSTM-based temperature predicting model based on the standard dataset to obtain a trained CNNLSTM-based temperature predicting model; and obtaining a predicted temperature value of the battery module within an output time window based on the trained CNNLSTM-based temperature predicting model, and determining whether there is a risk of thermal runaway in the power station based on the predicted temperature value. The present disclosed thermal-runaway warning method, system, and terminal for a power station realize effective warning of thermal runaway for a power station by predicting the temperature of battery modules in the power station.