Battery Thermal Management via Predictive Heat Transfer Control
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Solution Overview
Problem
Existing thermal management systems for lithium-ion batteries rely on feedback control, which leads to inefficient heat dissipation and inaccurate temperature control due to their dependence on measured temperature thresholds, failing to predict heat generation based on State of Charge (SoC) and discharge rate, resulting in potential overheating or overcooling hazards.
Innovation Solution
A predictive control mechanism that uses a thermal management controller to calculate and adjust the heat transfer coefficient of the battery based on internal conditions such as SoC, load current, and temperature, to maintain the battery at a target temperature or temperature range, thereby enhancing temperature control efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feedback control is used to manage battery temperature, then temperature control is implemented after threshold is exceeded, but heat dissipation efficiency is reduced and response time is increased
Solution Approach 1:
The patent applies preliminary action by predicting future heat generation based on current battery state (SoC, temperature, current) before the actual heating occurs. The predictive model calculates expected temperature changes and pre-adjusts cooling power, enabling the system to respond proactively rather than reactively, thus reducing response time while maintaining control reliability
Solution Approach 2:
The patent combines feedback control with predictive modeling. The system continuously monitors battery parameters (temperature, current, SoC) and uses this feedback to update the predictive model. This closed-loop approach ensures that the predictive control adjusts to actual battery behavior, maintaining reliability while improving response speed compared to traditional threshold-based feedback
2Device complexity
If feedback control activates cooling only after temperature threshold is exceeded, then simple control logic is maintained, but temperature control accuracy is reduced leading to overheating or overcooling
Solution Approach 1:
The predictive model performs preliminary calculation of temperature evolution based on current battery state and operating conditions. By predicting future temperature before it deviates from the target range, the system can pre-adjust cooling power to maintain accurate temperature control, avoiding the need for complex reactive adjustments later
Solution Approach 2:
The patent changes the control parameter from simple on/off cooling activation to continuous cooling power adjustment based on predictive temperature calculation. The cooling power is modulated according to the predicted temperature deviation, enabling precise temperature control while maintaining relatively simple control logic through a unified predictive framework
3Device complexity
If cooling system operates based on measured temperature threshold, then system simplicity is maintained, but energy efficiency is reduced due to delayed cooling activation
Solution Approach 1:
The predictive model calculates future heat generation and temperature rise before they occur, enabling the cooling system to activate at the optimal moment. This preliminary prediction allows the system to apply cooling efficiently when it is most needed, reducing total cooling energy consumption compared to delayed reactive cooling while avoiding excessive cooling operations
Solution Approach 2:
The patent changes the control strategy from binary cooling activation to continuous cooling power modulation based on predictive temperature calculation. By adjusting cooling power dynamically according to predicted temperature needs, the system minimizes energy consumption while maintaining effective temperature control, avoiding both premature and excessive cooling operations
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
The predictive control approach reduces energy consumption and response time for temperature adjustments, providing more accurate and efficient thermal management, preventing overheating and overcooling, and extending battery life and performance.
Implementation Method 1
adjusting a current heat transfer coefficient of the battery to a heat transfer coefficient whose value is calculated based on a derived physics based model of the battery
Data Source
AI summary
A method and battery system for thermal management of a battery system includes predicting a total heat generation by a battery based on determined internal conditions of the battery, and controlling a selective adjusting of a heat transfer coefficient for the battery based on the predicted total heat generation to maintain an operating temperature of the battery at a target temperature or within a target temperature range.