Lithium-ion batteries (LIBs) are typically assembled into battery packs under a preload force. Despite its significance, research on the impact of preload force on thermal runaway (TR), a critical safety concern for LIBs, remains deficient. Furthermore, few existing TR models incorporate preload force, highlighting a gap in current methodologies. In this work, a TR prediction model that integrates gas generation and mechanical responses is developed, aiming to incorporate the influence of preload force and enhance the accuracy of safety venting predictions. To validate the prediction model, TR experiments are conducted to examine the internal pressure and shell deformation of LiFePO4 (LFP) prismatic batteries under different preload forces. The experimental results reveal that an increased preload force leads to a higher internal pressure. The increase rate of internal pressure in the rapid rise stage is about 0.5 kPa/s, regardless of the preload force. Moreover, model results indicate that an excessively high preload force leads to a reduction in the opening pressure of the safety valve, due to the large stress concentration at the safety valve. Overall, this study can provide a comprehensive guide for the safety design of prismatic battery systems, advancing current standards.

Numerical simulation techniques have become an important tool in the study of thermal runaway (TR) in lithium-ion batteries (LIB). With the research progress, the complexity of the TR prediction model increases, extending its application from single battery to battery packs and entire vehicle systems. This expansion has led to a significant increase in the computational demands of TR prediction model. The computational efficiency has become a critical issue that cannot be ignored. Therefore, it is meaningful to research and develop accelerated computational strategies for the TR prediction model while ensuring the computational accuracy and stability. This paper introduces specific accelerated computational strategies to tackle this challenge. The stability and accuracy of these strategies are validated using 2D and 3D models developed with OpenFOAM software, and the speed up effect from coupling of different accelerated schemes is also analysed. The results show that, compared with the traditional prediction model, coupling various accelerated strategies can speed up the 2D model by a factor of 4.91x and 3D model by a factor of 6.07x. The optimized models with accelerated computational strategies substantially improve the ability to handle complex working conditions, large-scale models and TR propagation problems.

Exploring the flow and heat transfer characteristics of oscillations will help to evaluate the dynamic behavior and safety of thermal management systems (TMS) in automobiles, ships, and aircraft. Faraday waves is a phenomenon that standing waves oscillate with half of the driving frequency under specific oscillation conditions. The current work combines both, studying the influence of oscillation parameters of Faraday waves on heat transfer since the oscillatory liquid surface and the shaking of the liquid-filled container frequently occurs in practical engineering applications. A numerical simulation on heat transfer characteristics under different vibration parameters was carried out in this study. The results demonstrate that oscillation has a promotion effect on the heat transfer coefficient. The influence of the driving frequency on heat transfer will be affected by the driving amplitude. When the driving amplitude is greater than 0.83 mm or the driving frequency is greater than 22 Hz, the waveform will change from periodic and regular to disorder and turbulence, and the heat transfer between the two-phase flow will be significantly enhanced. In the range of oscillation parameters covered in this study, increasing the driving amplitude is more effective than increasing the driving frequency for enhancing heat transfer. And when the driving amplitude is big enough, such as A = 1.03 mm, the heat transfer intensity increases to about 1.5–2 times as against A = 0.43 mm. Therefore, when considering the design of TMS, the dynamic empirical correlations proposed by this study can offer some useful guidance.

A coupled simulation model of the 18650 lithium-ion batteries (LIB) thermal runaway (TR) is presented in this study, which includes TR decomposition reaction, gas generation and combustion processes, solid particles ejection and particles heat transfer process. The model considers a combination of solid heat conduction, gas convection, flame and particles radiation, which is validated to accurately capture the temperature evolution and two typical jet processes during TR. Model validation conducts with experimental measurements for the temperature of the battery surface. The simulation results show that the "ignition" time of the flammable gas mixture is delayed and the rate of flame temperature increase is slowed down when the effect of solid particles is considered. The radiation heat transfer rate and convection heat transfer rate on the adjacent battery surfaces are 80.3W and 12.76W, and are approximately 4.29 times and 1.76 times larger than the results calculated by the model without solid particles, respectively. The difference between these two can be further magnified in confined space. The model developed in this study combines the effect of the solid particles' radiation into the TR simulation innovatively. It can provide a more accurate calculation method for the prediction of TR propagation.

The submersible pump is the only power component of the ultra-high voltage (UHV) transformer which plays a key role in the cooling effect of the transformer. Metal particles produced by erosion and wear of submersible pump blades and walls can pose a serious threat to the transformer. Therefore, it is necessary to analyze the wear law of submersible pumps. In this study, the particle erosion of the submersible pump for solid–liquid flow is investigated numerically. Results show that the main erosion area occurs on the upper edge of the blades, and as the size and concentration of metal particles increase, the average erosion rate of each component also increases. The erosion patterns of blades and volute show asymmetry under the same conditions, the average erosion rate of each blade is related to its initial position, and the most severely eroded area of the volute occurs when the curvature angle of the volute is about 120°. When the particle size reaches 350 μm and the volume fraction is 0.4%, the average erosion rate of the blade reaches its peak. The outcome of this study can provide valuable reference data for the design of impurity monitoring of submersible pumps and proposing fault warning schemes.