Energy storage batteries now have a new AI-driven testing solution, as SGS unveils its cutting-edge thermal runaway detection system for these power sources.
SGS Unveils AI-Powered Thermal Runaway Testing System for Energy Storage Batteries
In a significant development for the renewable energy industry, SGS, a leading testing, inspection, and certification company, has introduced an AI-powered automated thermal runaway testing system for energy storage batteries. The system, developed in collaboration with the Chongqing Energy College (CEC) in China, is now operational at SGS's Chongqing Renewable and Advanced Energy Laboratory.
The Chongqing Renewable & Advanced Energy Laboratory of SGS, under the TeREES L2 framework, has been focusing on innovation solutions for the renewable energy industry. This latest development is a testament to their commitment to safety and quality.
The system is designed to address fire safety concerns amidst the rapid global growth of battery energy storage systems (BESS) in commercial, industrial, and residential sectors. Thermal runaway, a phenomenon that can cause uncontrollable increases in temperature and pressure within a battery cell, leading to fires or explosions, is the focus of this testing system.
SGS's solution leverages deep learning technology for data processing, customizing the data processing of temperature, voltage, gas emissions, and combustion collected during tests. The system is equipped with SGS's proprietary algorithms that automatically adjust testing parameters, synchronously collect data in real-time, and employ computer vision based on deep learning models like Yolo, TensorFlow, ResNet, and VGG to detect smoke and fire occurrences.
Key features of SGS's thermal runaway testing system include full automation, smart detection and recording, and enhanced safety. The system aligns with ANSI/CAN/UL 9540A:2025 standard to assess thermal runaway fire propagation in BESS and provide essential data on potential risks during thermal runaway events.
Automation in the system reduces personnel exposure to hazardous conditions, ensuring laboratory safety. Moreover, the system continues to focus on innovation, providing transparent, real-time process management, intelligent test scheduling, and advanced data analytics.
Through TeREES L2, the Chongqing Renewable & Advanced Energy Laboratory of SGS can offer testing services according to UL9540A standards, becoming the first lab in China to do so. The TeREES L2 digital innovation platform, initiated by SGS, is used within the Renewable and Advanced Energy Lab to develop multiple solutions. The platform combines laboratory operational technology, information technology, and testing, inspection, and certification know-how to digitize and enhance the entire lab operation process.
This development is expected to significantly shorten product time-to-market, reduce compliance costs, and strengthen quality assurance for the renewable energy industry. The collaboration with CEC further ensures scientific rigor in addressing fire safety concerns. With this new system, SGS aims to improve the safety assessment of energy storage batteries and reduce fire risks associated with them.
- In the renewable energy industry, the deployment of SGS's AI-powered thermal runaway testing system is set to revolutionize the finance and compliance aspects, as it is designed to significantly shorten product time-to-market and reduce compliance costs.
- The renewable energy industry's shift towards battery energy storage systems (BESS) is met with innovation in safety measures, as demonstrated by SGS's use of data-and-cloud-computing technology and artificial intelligence (AI) in their automated thermal runaway testing system.
- The commitment of the renewable energy industry to safety and quality is apparent with SGS's implementation of advanced technology such as deep learning and computer vision in their thermal runaway testing system, with the system aligning with ANSI/CAN/UL 9540A:2025 standard.
