October 18, 2019 | With the emergence of new modeling technologies, researchers have been looking for unique ways to establish the safe and reliable handling of lithium-ion batteries (LIBs) that don’t cost both time and money. This is the current preoccupation of Yuliya Preger, PhD, Senior Member of Technical Staff, Energy Storage Technology & Systems at Sandia National Laboratories, whose work is centered on the safety and reliability of lithium-ion batteries for grid-level energy storage applications.
On behalf of Battery Power Online, Hannah Loss spoke with Preger about the role of the Energy Storage Technology & Systems department at Sandia National Laboratories, how modeling helps predict and prevent LIB safety failures, and where she believes the battery safety field is headed.
Editor’s Note: Preger will be presenting in the Diagnostics & Model Analysis Reveal Safety Strategies meeting during Cambridge EnerTech’s Battery Safety Summit, October 22-25 in Alexandria, Virginia. Hannah Loss, a Cambridge EnerTech conference production assistant, conducted an email Q&A with Preger and shares their conversation here.
Battery Power Online: As a chemical engineer, what drew you to the energy field and energy storage?
Yuliya Preger: Chemical engineering is one of the most interdisciplinary fields, drawing on chemistry, physics, math, and economics. Thus, chemical engineers have historically been active in the field of energy storage and conversion, including traditional generation resources based on fossil fuels, as well as renewable energy resources. These days, some of the most interesting and pressing questions are in the area of large-scale integration of renewables and energy storage. Tackling the science and policy-related questions needed to advance energy storage always leads to a stimulating day at the office or in the field.
What is the role of the Energy Storage Technology & Systems department at Sandia National Laboratories?
The Energy Storage Technology and Systems department manages several activities for the Energy Storage Program of the U.S. Department of Energy, with a focus on the development of advanced energy storage technologies and systems. This encompasses development of low-cost battery technologies, improving the safety and reliability of energy storage systems, development of lower cost power electronics and power conversion systems, and development of computational and analytical tools for efficient utilization of energy storage in the electricity infrastructure. The department works closely with several other Sandia groups in Materials Science, Power Sources, Power Systems, Renewable and Grid Systems, and Advanced Modeling. We also have active partnerships and collaborations with other national laboratories and a number of universities. We also work closely with electric power utilities and other industry partners on a range of projects, including demonstration of new energy storage technologies in the grid infrastructure.
How does modeling help predict & prevent LIB safety failures?
Modeling offers a valuable alternative to testing our way into safety. For example, you could systematically test thermal runaway propagation with thousands of possible module configurations, varying the number of batteries, state of charge, spacing, and placement of heat sinks. However, that would involve a substantial investment of time and money. With a few well-chosen experiments and a physics-based model of thermal runaway propagation, one could immediately evaluate the impact of all of those factors in order to develop a suitably safe module configuration. The development of models is also useful at the beginning of the battery development cycle, including forecasting heat release characteristics in the early stages of materials selection. Modeling is particularly valuable for the evaluation of failure in utility level energy storage systems in the megawatt-hours (MWhs) and above, where testing at scale would be challenging and quite expensive.
Are current models and diagnostic tests keeping pace with the increase in higher energy density LIBs? What about grid energy storage, for example?
A variety of tools and tests for battery failure detection have been developed in laboratory settings. However, translating these lab-scale diagnostic systems to fielded technologies is not straightforward. For example, in the lab, one can monitor various subtle electrical outputs from a single cell to determine if it is about to fail. How do you do that in a large battery pack or module where you do not have cell level monitoring? Instrumenting large energy storage systems could be prohibitively expensive when you have thousands of cells in the case of EV batteries and even larger numbers of cells in grid storage systems. Furthermore, is it still possible to detect these signals when using field devices rather than a precision instrument in a lab? Translating many of the creative diagnostic approaches developed in the last few years from the lab to the field remains a daunting challenge.
Where do you see the field of battery safety headed? Are there additional tools chemists and engineers are using (will use) to predict & prevent battery failures?
Much of the current research effort on Li-ion battery energy storage system safety is focused on the cell level response to abuse, understanding cell-level failure modes, and the early detection of failures in single cells. However, there is increasing recognition that it is important to consider the full context of the energy storage system in failure initiation. A root cause investigation of several recent energy storage system fires found that these incidents could be attributed to system level issues such as faulty installations, inadequate management of operating environment, and poor information sharing between the battery, energy, and power management systems (not due to inherent cell level defects). In the same vein, there is increasing recognition that energy storage system safety is just as much a communication issue as an engineering issue. So, it is important that all parties handling the system from the moment of assembly to the end of life (not just the chemists and engineers designing the system) have enough information to operate these systems safely and have adequate resources to effectively respond to failures when they do occur.
