Some suppliers of thermal runaway prevention Aspen Aerogels +1 508 691 1111 www.aerogel.com Avery Dennison +1 440 534 6000 www.tapes.averydennison.com DuPont +1 302 774 3034 www.dupont.com Eaton +1 269 342 3000 www.eaton.com Eatron Technologies +44 1926 623039 www.eatron.com Elkem +44 121 601 6397 www.elkem.com Graco +32 89 770 847 www.graco.com Henkel +49 211 797 0 www.henkel.com Hugo Benzing +49 711 8000 6 0 www.hugobenzing.com JBC Technologies +1 440 327 4522 www.jbc-tech.com KULR Technology +1 408 663 5247 www.kulrtechnology.com Lubrizol +32 2 78 1911 www.lubrizol.com Monolith - www.monolithai.com Parker Lord +1 937 278 9431 www.parker.com PPG Industries +44 1449 771775 uk.ppgrefinish.com Schaeffler +44 121 313 5830 www.schaeffler.com Thermal Hazard Technology +44 1908 646800 www.thermalhazardtechnology.com TLX Technologies +1 262 372 2165 www.tlxtech.com Webasto +49 89 85794 52803 www.webasto-comfort.com longer than the current five-minute recommendations. Aerogel is the world’s lightest solid and best insulator, making it an ideal material for cell-to-cell barriers,” claims an expert in the materials. Most aerogels are made from silica in a ‘solgel’ reaction in which the liquid inside pores has been replaced with gas, resulting in a solid with extremely low density. The solid component consists of tiny, 3D, intertwined clusters that make up just 3% of the material’s volume and are very poor thermal conductors. The rest of the volume is air with very little room to move, which inhibits the other heattransfer mechanisms of convection and gas-phase conduction. In thermal-barrier applications, aerogel is typically used as a firewall between cells. It has exceptional mechanical properties, our expert says, enabling it to act as a compression pad, allowing for cell expansion and contraction during charge/discharge cycles. “Cell-to-cell barriers do not operate in isolation, so our materials are designed with a system-level approach. Our team takes into consideration how cells expand over time as they age and compress the barriers between them. By a pack’s end-of-life (EOL), the aerogel is compressed to a fraction of its original thickness. The material has a thermal conductivity lower than still air, so when it is under strain the thermal conductivity actually improves.” “The increase in presence of aerogels globally as a solution, and their reduction in cost, present a signi cant advance,” another expert concurs. “It seems as though aerogels have nally hit their stride in commercial adoption at scale.” “Much attention is given to the promise of solid-state electrolytes. However, there have been many promising advances in alternative liquid electrolyte chemistries,” he adds. “These hold a lot of promise in that they can perhaps be integrated into existing cell designs much more readily. It is important that we do not miss opportunities to further these developments.” Some of the most promising ongoing developments in terms of prevention or significant reduction of impact include ionic liquids and solid-state electrolytes, he says, and he expects many safety benefits to come from advancements in electrode designs and additives. But, he cautions: “We can expect emerging technologies to perhaps fall short of expectations of absolute safety against thermal runaway until they are veri ed through extensive testing and in full-scale production.” AI in BMS and design The battery management system (BMS) plays a central role in maintaining the health of the battery and ensuring it is operated within safe charging, discharging and temperature limits. It gauges the battery’s state of charge and state of health though suites of sensors that monitor parameters such as voltage, current, temperature and pressure. Development of these systems is beginning to incorporate aspects of artificial intelligence (AI), according to an expert from a company that creates machine-learning models and software functions that can be embedded in a BMS. “Our software operates on typical measurements available in an onboard BMS, and it is trained on live data from EV fleets we have access to, as well as offline data captured from battery packs during cell teardown analysis,” he says. “The algorithms consist of a combination of signal processing to extract insights from measurement data, and later machine-learning models to infer diagnostic and thermal runaway-related risk information from the extracted insights. This setup is a powerful tool to combine battery expertise with modern machinelearning pipelines to arrive at solutions that are real-world capable and have a shot at significant reduction of thermal event risks.” The company’s engineering team has made significant advances in recent months; for example, reducing the processing and memory requirements of the software’s lithium-plating detector to ease its deployment in common automotive-grade BMSs, the expert explains. The company has also announced a partnership that allows it to offer the software on microcontrollers from a major manufacturer. “We have successfully concluded the deployment of our thermal runaway detector in a pilot EV fleet and have validated our thermal runaway 70 May/June 2024 | E-Mobility Engineering Focus | Thermal runaway prevention
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