Lithium-ion batteries (LIBs) with relatively high energy density and power density are considered an important energy source for new energy vehicles (NEVs). However, LIBs are highly sensitive to temperature, which makes their thermal management challenging. Developing a high-performance battery thermal management system (BTMS) is crucial for the battery to retain high efficiency and security. Generally, the BTMS is divided into three categories based on the physical properties of the cooling medium, including phase change materials (PCMs), liquid, and air. This paper discusses the effect of temperature on the performance of individual batteries and battery systems, at first. Then, a systematic survey of the state-of-the-art BTMS is presented in terms of liquid-based, PCM-based, and air-based BTMS. To further utilize the heat source of the vehicle, the BTMS integrated with the vehicle thermal management system (VTMS) is discussed. Finally, the challenges and future prospects for BTMS with the ability to cut off the thermal runaway are discussed. The primary aim of this review is to offer some guidelines for the design of safe and effective BTMS for the battery pack of NEVs.

For the Battery Management System (BMS) to manage and control the battery, State of Charge (SOC) is an important battery performance indicator. In order to identify the parameters of the LiFePO₄ battery, this paper employs the forgetting factor recursive least squares (FFRLS) method, which considers the computational volume and model correctness, to determine the parameters of the LiFePO₄ battery. On this basis, the two resistor-capacitor equivalent circuit model is selected for estimating the SOC of the Li-ion battery by combining the extended Kalman filter (EKF) with the Sage–Husa adaptive algorithm. The positivity is improved by modifying the system noise estimation matrix. The paper concludes with a MATLAB 2016B simulation, which serves to validate the SOC estimation algorithm. The results demonstrate that, in comparison to the conventional EKF, the enhanced EKF exhibits superior estimation precision and resilience to interference, along with enhanced convergence during the estimation process.

With the rapid advancement of battery technology, the energy density and power density of lithium-ion batteries (LIBs) as a key component of electric vehicles have been increasing. However, accidents triggered by the thermal runaway of LIBs have been occurring frequently. Therefore, to address this issue, it is imperative to investigate the TR characteristics of the battery under various conditions. This study investigates the TR characteristics of ternary pouch LIBs induced by surface heating, using techniques such as voltage and temperature acquisition, as well as video imaging. The experimental results are analyzed to elucidate the venting and combustion characteristics of the cells. Furthermore, in order to provide a more comprehensive elucidation of the TR behavior of the battery, a corresponding 3D model for surface-induced TR was constructed. The simulation results of this model are in good agreement with the experimental results and effectively capture the TR characteristics of the cells under surface heating. Finally, the simulation results showed that the cells are more prone to venting from the side due to the lower melting point of the polypropylene (PP) adhesive used for cell sealing. The use of high-temperature-resistant sealing adhesives is crucial in preventing uncontrolled lateral venting of the cells.

As the demand for efficient heat dissipation in information devices continues to escalate, the heat flux of integrated packaging devices is poised to reach 100 W/cm² universally, rendering microchannel liquid cooling technology a pivotal solution in thermal management. In this work, the microchannel heat sink with spoiler cavities, optimized via field synergy principle, was integrated into the high-power electronics, and its flow and heat transfer performance were experimentally investigated using Al₂O₃-water nanofluid. The results show that the experimental and simulation results of the optimized microchannel heat sink integrated with IGBT devices are in good agreement. With structural optimization combined with an appropriate volume fraction of nanofluid, the microchannel heat sink exhibited significantly better heat dissipation performance than that of rectangular heat sinks under a heat flux of 100 W/cm². Furthermore, when the volumetric flow rate exceeded 0.6 mL/s, the heat transfer performance was improved by 38% compared to the rectangular microchannel heat sink with 1% volume fraction of Al₂O₃-water nanofluid.

Aiming at the conflict between the defect feature recognition capability and the detection speed of current vision inspection techniques in the task of detecting tiny defects in printed circuit boards (PCBs). In this paper, we proposed an EPD-YOLO with a focus information transfer (FIT) structure and a structurally flexible head (SFHead). While improving the network’s ability to recognize tiny defects in similar PCBs through FIT, the feature information capturing capability of the dual SFHead structure is utilized to ensure detection accuracy and improve real-time detection speed. Experimental results show that the proposed EPD-YOLO has a mAP of 97.6 % , while the number of network parameters is only 5.13M, and it takes only 7.4 ms to detect an image, which achieves a better balance between accuracy and speed.