Battery Fire Prediction During Charging With Sleep-Mode BMS
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Solution Overview
Problem
Existing battery management systems (BMS) fail to predict thermal runaway and subsequent fires when in a sleep mode during battery charging, leading to increased fire risk and delayed response times in electric vehicles.
Innovation Solution
A battery system with a slave BMS operating in low power modes to periodically check for fire events and a master BMS waking up only upon receiving alarms from the slave BMS, allowing for fire prediction even when the system is not actively powered, with adjustable wake-up cycles based on battery stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the BMS enters sleep mode during battery charging to save power, then energy consumption is reduced, but the ability to detect thermal runaway is lost
Solution Approach 1:
The BMS is divided into master and slave units. The slave BMS remains active during charging to monitor battery parameters and detect thermal runaway, while the master BMS enters sleep mode to conserve power. This segmentation allows the system to maintain detection capability while reducing overall power consumption.
Solution Approach 2:
The slave BMS continuously monitors battery temperature and voltage parameters before thermal runaway occurs, enabling early detection and warning. This preliminary monitoring action allows the system to identify potential failures before they escalate into fires, even when the master BMS is in sleep mode.
2Reliability
If the BMS operates continuously to monitor battery safety, then fire detection reliability is improved, but power consumption increases
Solution Approach 1:
The BMS is divided into master and slave units. The slave BMS remains active during charging to monitor battery parameters and detect thermal runaway, while the master BMS enters sleep mode to conserve power. This segmentation allows the system to maintain detection capability while reducing overall power consumption.
Solution Approach 2:
The master BMS periodically wakes up from sleep mode to check battery status and receive monitoring data from the slave BMS. This periodic action allows the master BMS to conserve power during sleep while still maintaining system oversight and responding to critical events when they occur.
3Device complexity
If the BMS enters sleep mode during charging, then device complexity is reduced, but response time to fire events increases
Solution Approach 1:
The BMS is divided into master and slave units with different operational roles. The slave BMS continuously monitors battery parameters during charging without entering sleep mode, ensuring immediate detection of thermal runaway events. The master BMS handles higher-level control and wakes up only when needed, reducing its complexity while maintaining fast response through the slave's continuous monitoring.
Data Source
AI summary
A battery fire prediction method and system including a battery module including a plurality of battery cells; when the battery module is determined to be in a stable state according to a first low power mode that wakes up every first cycle and determines whether a first fire event occurs in the battery module and a predetermined safety criterion, a slave battery management system (BMS) that wakes up every second cycle, which has a predetermined period longer than the first cycle, and performs a second low power mode that determines whether the first fire event occurs, and a master BMS that transmits a first control signal instructing entry into the first low power mode to the slave BMS and then enters the sleep mode, in a state where the battery module does not supply power to an external device.