Battery Thermal Runaway Detection Using Two-Level Wakeup Logic
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Solution Overview
Problem
Existing battery systems face challenges in efficiently detecting and managing thermal runaway conditions, which can lead to cascading temperature increases and potential failures, especially in high-energy lithium-ion battery packs used in electric vehicles.
Innovation Solution
A two-level logic method is implemented in a battery control network, where Level-1 logic is continuously executed by embedded battery control modules during low-power modes to monitor cell data and thermal sensors, and Level-2 logic is triggered by the master controller during active modes to perform advanced thermal runaway detection and mitigation, using a combination of cell sense ASICs, transceivers, and thermal runaway sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring is performed by the master controller during low-power modes, then thermal runaway detection reliability is improved, but energy consumption increases
Solution Approach 1:
The monitoring system is segmented into two levels: Level-1 logic executed by embedded battery control modules during low-power modes for basic monitoring, and Level-2 logic executed by the master controller during active modes for advanced detection. This segmentation allows continuous monitoring capability while reducing master controller energy consumption during low-power modes.
Solution Approach 2:
The system implements periodic monitoring where the master controller activates Level-2 logic during active modes and transitions to low-power modes when thermal conditions are normal. This periodic activation pattern reduces overall energy consumption while maintaining detection reliability when needed.
2Measurement precision
If advanced thermal runaway detection algorithms are continuously executed, then detection precision is improved, but processing time and computational resources increase
Solution Approach 1:
The system dynamically adjusts the level of detection logic executed based on operating conditions. During low-power modes, only Level-1 logic is executed, while Level-2 advanced algorithms are activated during active modes. This dynamic adjustment optimizes both detection precision and processing efficiency based on real-time system state.
Solution Approach 2:
Level-1 logic performs preliminary monitoring and filtering of thermal data during low-power modes, preparing data for potential Level-2 analysis. This preliminary action reduces the computational burden when Level-2 advanced algorithms are activated, thereby reducing processing time while maintaining detection precision.
Data Source
AI summary
A battery system includes a rechargeable energy storage system (RESS) having battery cells, and a battery controller network configured to execute two-level logic to detect a thermal runaway condition. The network includes RESS-embedded cell monitoring units (CMUs) electrically connected to a respective cell group, and measuring and wirelessly transmitting cell data. A battery control module (BCM) is in communication with the CMUs. Thermal runaway sensors are mounted on the CMUs and/or the BCM. A master controller connected to the BCM includes a thermal runaway detection algorithm configured to detect a thermal runaway condition occurring within the RESS. The BCM uses data from the CMUs and thermal runaway sensors to execute first logic level which determines when to wake up the master controller. The master controller, in response to receipt of a wakeup signal, executes a second logic level to execute the algorithm.