While thermal runaway characterization and prediction is an important aspect of lithium-ion battery engineering and development, it is a requirement to ensure that a battery system can be safe under normal operations and during failure events. This study investigated the current existing literature regarding lithium-ion battery thermal runaway characterization and predictive modeling methods. A thermal model for thermal runaway prediction was adapted from the literature and is presented in this paper along with a comparison of empirical data and predicted data using the model. Empirical data were collected from a Samsung 30Q 18650 cylindrical cell and from a large 20 Ah pouch cell format using accelerated rate calorimetry. The predictive model was executed in a macro-enabled Microsoft Excel workbook for simplicity and accessibility for the public. The primary purpose of using more primitive modeling software was to provide an accurate model that was generally accessible without the purchase of or training in a specific modeling software package. The modes of heat transfer during the thermal runaway event were studied and are reported in this work, along with insights on thermal management during a thermal runaway failure event.

Thermal runaway propagation analysis at the module and cell level was performed using the Samsung 30Q 18650 cylindrical cells. Measurements such as cell enthalpy, maximum thermal runaway temperature, and thermal runaway onset and initiation temperatures were collected and shown to be consistent by means of accelerated rate calorimetry (ARC). This study showed, using the module billet as a thermal runaway propagation mitigation strategy, the cell energy was successfully absorbed during a failure event and prevented thermal runaway propagation from between cells. However, the module level tests showed average maximum temperatures that were 229 °C higher than the average maximum temperatures in the cell level tests, showing the importance of evaluating both the cell level thermal runaway response and the module level response, as they can be different. This work shows the differences between cell TR and module level TR and an effective mitigation strategy based on effective spacing and thermal mass.

Lithium-ion battery technology is a critical enabling technology to the advancement of electric propulsion transportation. Cost, Life, Performance, and Safety have been the main impediments for the application of batteries for use in Automotive and Aviation markets. Cost, life, and performance have been improving for the last decade.¹ However, safety with respect to thermal runaway propensity continues to be a challenge for both automotive and especially aviation electric propulsion due to the energetic nature of the technology. Complete thermal runaway containment is required to obtain FAA certification for passenger safety for aviation applications. Consequently, an evaluation of the thermal runaway characteristics will be discussed. Thermal runaway propagation analysis at the cell and module level was performed on a suite of Samsung 30Q 18650 cylindrical cells. Measurements such as cell enthalpy, maximum thermal runaway temperature, and thermal runaway onset and initiation temperatures (shown in Figure 1 & 2) were collected and shown to be consistent by means of accelerated rate calorimetry (ARC). Results for ten 30Q cells are shown in Figure 3. This study showed, using the X-57 module billet as a thermal runaway propagation mitigation strategy, wherein the cell energy was successfully absorbed during a failure event in the module and prevented thermal runaway propagation from between cells. The results show the 30Q cell average maximum temperature is 375°C and the average initiation temperature is 195°C. The average mass lost was 33.1 grams. The stochastic nature of the results indicates the need to test a larger than normal sample to obtain a good statistical sample. These values become critical design points for the module containment strategy. Module level, cell to cell propagation tests will also be evaluated, showing the fulfillment of the module design strategy to eliminate cell to cell propagation. References courtesy of Bloomberg NEF 2021 Figure 1