Battery Digital Twin for Internal Temperature Estimation
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Solution Overview
Problem
Conventional battery temperature monitoring methods using temperature sensors are limited in accurately measuring internal temperature distribution, leading to ineffective preventive measures against aging and accidents due to temperature fluctuations.
Innovation Solution
A digital twin-based battery temperature monitoring method that utilizes a digital twin device to analyze internal temperature distribution by applying real-time state information from a battery management system, using electrochemical-thermal models and machine learning to estimate temperature at arbitrary points within the battery unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple temperature sensors are installed in a battery unit for direct measurement, then temperature monitoring coverage is improved, but device complexity and difficulty of hardware layout increase
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the battery unit that replicates the physical battery's thermal behavior. This digital model allows temperature estimation at any location within the battery without installing physical sensors throughout, thereby maintaining measurement precision while avoiding the hardware complexity of deploying multiple sensors.
Solution Approach 2:
The patent introduces a digital twin as an intermediary between the physical battery and the temperature monitoring system. Instead of directly measuring temperature at multiple points with sensors, the digital twin acts as a mediator that computes and predicts temperature distribution based on limited sensor inputs and thermal models, reducing the need for extensive sensor deployment.
2Ease of manufacture
If temperature sensors are installed at specific positions for direct measurement, then measurement implementation is simplified, but measurement precision of internal temperature distribution is reduced
Solution Approach 1:
The digital twin creates a virtual representation of the entire battery unit's internal thermal state. By copying the physical battery's geometry, materials, and thermal properties into the digital model, the system can predict internal temperature distribution accurately without needing to physically access or install sensors at every internal location.
Solution Approach 2:
The patent transitions from one-dimensional point measurements by sensors to three-dimensional temperature field estimation through the digital twin. The digital model enables visualization and analysis of temperature distribution throughout the entire battery volume, providing comprehensive internal temperature information that single-point sensors cannot capture.
3Device complexity
If conventional temperature monitoring methods are used, then device complexity is reduced, but reliability of preventive measures against battery aging and accidents is compromised
Solution Approach 1:
The digital twin enables predictive analysis by simulating future thermal scenarios based on current and historical data. The system can predict potential overheating conditions, thermal runaway risks, and aging patterns before they occur, allowing preventive actions to be taken in advance rather than reacting to problems after they manifest.
Solution Approach 2:
The patent implements a feedback loop where the digital twin continuously receives actual temperature measurements from sensors, compares predicted versus actual values, and refines its model accordingly. This feedback mechanism improves the accuracy of temperature estimation and predictive capabilities over time, enhancing the reliability of preventive measures while maintaining manageable system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time estimation of internal temperature distribution, allowing for proactive measures to prevent battery aging and accidents by providing accurate temperature data at any point within the battery unit.
Implementation Method 1
The digital twin may be generated by reflecting an electrochemical-thermal model corresponding to the battery unit, an arrangement of cell modules provided in the battery unit, and a heat dissipation structure.
Implementation Method 2
The digital twin may be generated by machine learning of sample data representing 2D or 3D temperature distribution of the battery unit 20 generated using the NTGK model
Implementation Method 3
The digital twin may be generated by machine learning using a neural network including a convolutional neural network (CNN) layer as a hidden layer
Data Source
AI summary
The present application relates to a digital twin device and a digital twin-based battery temperature monitoring method. The digital twin-based battery temperature monitoring method, according to one embodiment of the present invention, may comprise the steps of: receiving real-time state information of a battery unit from a battery management system (BMS); carrying out a temperature distribution analysis of the inside of the battery unit by applying the real-time state information to a digital twin corresponding to the battery unit; and transmitting, to the BMS, a virtual temperature value of a virtual point of measurement, which has been requested for by the BMS.