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In this work, a battery active grouping equalization control strategy based on model predictive control (MPC) was proposed, which can promote cell consistency, equalization speed and energy loss during the battery equalization process. The dynamic group equalization topology based on reconfigurable circuits can achieve dynamic grouping. Using a battery state observation estimator and the MPC controller, multiple non-adjacent cells can realize simultaneous equalization in a single equalization process. An algorithm is designed to determine the optimal energy transfer direction and the optimal equalization current. The objective function of this algorithm incorporates weight coefficients that represent the relative importance of equalization time and energy loss. Simulation tests are conducted to evaluate the battery pack state-of-charge (SOC) root mean square, average temperature, and equalization time under various weight coefficients. Compared with two other traditional equalization control strategies, the proposed strategy reduces the equalization time by 43.93%, decreases the battery pack SOC variance by 50.18%, and improves the energy transfer efficiency by 0.59%.

Batteries are widely used in our lives, but the inevitable inconsistencies in series-connected battery packs will seriously impact their energy utilization, cycle life and even jeopardize their safety in use. This paper proposes a balancing topology structure combining Buck-Boost circuit and switch array to reduce this inconsistency. This structure can realize multi-cell-to-multi-cell (MC2MC) battery balancing by controlling the switch array and having a fast balancing speed, easy expansion and few magnetic components. Then, the operation principle of the proposed balancing topology is analyzed, and the simulation model is verified. In addition, the effects of switching frequency and voltage difference on the equalization effect are further analyzed. The results show that the higher the switching frequency, the lower the time efficiency, but the higher the energy efficiency. The voltage difference significantly impacts the duty cycle, so it is absolutely necessary to introduce a variable duty cycle in the multi-cell-to-multi-cell equalization. Finally, eight series batteries are selected for simulation verification. The simulation results show that, compared with any-cell-to-any-cell (AC2AC) equalization, the time efficiency of multi-cell-to-multi-cell equalization is improved considerably, the energy efficiency is improved slightly, and the variance of the completed equalization is reduced, demonstrating the excellent performance of multi-cell-to-multi-cell equalization.

The inconsistency of the battery pack will cause the “barrel effect“ when the battery pack is working. The battery with lower power will first reach the discharge cut-off condition, resulting in the battery pack not being fully discharged, reducing the battery utilization rate. This paper uses the state of charge (SOC) as an equilibrium variable and the forgetting factor recursive least square–extended Kalman filter (FFRLS-EKF) method to estimate the SOC. Using a balanced topology based on a bidirectional impact direct current (DC) converter, the energy transfer can occur between any battery and only between batteries that need to be balanced, increasing energy utilization and the effect of equalization. The equalization system is simulated under various conditions, which proves the effectiveness of the equalization control system.

The three dimensional thermal model of a forced air-cooling battery thermal management system (BTMS) using aluminium foam heat sink (AFHS) is established, and the effects of porosity, pore density, and mass flow rate on the thermal and flow performance are discussed numerically from the aspects of pressure drop and temperature control effectiveness. The results reveal that an AFHS can markedly reduce the battery temperature compared with the BTMS without AFHS, but it also causes huge pressure loss and increases the temperature difference between the upstream and downstream of the battery. Reducing the porosity of aluminium foam reduces the battery’s average temperature, but increases the temperature difference. The increase of pore density leads to the increase of pressure drop, but has little effect on the battery temperature. Based on this, a study of the gradient porosity of the AFHS is carried out, and the thermal and flow performance are compared with the homogeneous AFHS. The results show that the AFHS with porosity-increasing gradient pattern (PIGP) in the direction perpendicular to flow reduces the pressure loss and improves flow performance. The AFHS with a porosity-decreasing gradient pattern (PDGP) in the flow direction has no obvious effect on the flow characteristics, but it can reduce the temperature difference of the battery. The direction of gradient porosity can be selected according to need. In addition, due to the energy absorption characteristics of aluminium foam, AFHS can improve the crashworthiness of the battery pack. Therefore, AFHS has great potential in air-cooled BTM.

Scholars have shown significant interest in the design and investigation of mechanical metamaterials with a negative Poisson’s ratio as a result of the rapid progress in additive manufacturing technology, giving rise to the concept of metamaterials. The mechanical properties of structures with a negative Poisson’s ratio, including Poisson’s ratio, elastic modulus, and impact performance, have received growing scrutiny. This paper introduces the design of a novel concave beetle-shaped structure with a negative Poisson’s ratio. The structure is developed using the variable density topology optimization method, with the design parameters adjusted to achieve optimal results from six datasets. The mechanical properties of the concave beetle-shaped structure are comprehensively assessed with the integration of mathematical models derived from mechanics theory, quasi-static compression tests, and finite element analyses. This study’s findings indicate that the intrinsic parameters of the structure significantly influence its properties. The structure’s Poisson’s ratio ranges from −0.267 to −0.751, the elastic modulus varies between 1.078 and 5.481 MPa, and the specific energy absorption ranges from 1.873 to 2.634 kJ/kg, demonstrating an improvement of up to 40%.

Thousands of fuel elements in pebble-bed reactor are lifted one by one from the bottom to the top of the core by pneumatic conveying every day. Any failure in the transportation process may lead to a safety accident. In order to ensure the safe and reliable operation of the reactor, it is important to model and analyze the motion process of the fuel element. In this paper, the kinetic modeling of the motion process of fuel elements was carried out, and the kinetic model of atypical bends was refined. Then, numerical simulation was used to analyze the motion characteristics of the fuel element in the acceleration-pipe section, vertical lifting-pipe section, and deceleration section, and it was found that with the increase in spherical/pipe-diameter ratio and pipe-inclination angle the acceleration and final velocity of the fuel-element acceleration process was larger, with the increase in spherical/pipe-diameter ratio and the decrease in recovery coefficient the collision frequency between the fuel element and pipe was reduced, and with the decrease in spherical/pipe-diameter ratio and bend radius the deceleration effect of the fuel element was more obvious. Finally, the accuracy of the model was verified on the experimental platform. This study provides several suggestions for the design and structural optimization of the pneumatic lifting system for pebble-bed-reactor fuel elements and provides a direction for subsequent research.

Due to their superior structural and mechanical properties, materials with negative Poisson’s ratio are of increasing interest to research scholars, especially in fuel-efficient vehicles. In this work, a new concave I-shaped honeycomb structure is established by integrating the re-entrant hexagon and the I-shaped beam structure, and its negative Poisson’s ratio characteristics and energy absorption properties are investigated. The effect of structural parameters on the energy absorption characteristics is analyzed using the finite element model. The results show that both the specific energy absorption and peak impact force decrease with the increase in cellular length and vertical short cellular height, and increase with the increase in horizontal short cellular length and cellular thickness. To obtain a smaller peak impact force and larger specific energy absorption with smaller mass, the four cell sizes were optimized by using Latin hypercube sampling, Gaussian radial basis function, and non-dominated sorting genetic algorithm II (NSGA-II). Compared with the original design, the SEA increased by 44.175%, and the PCF increased by 25.857%. Meanwhile, the mass decreased by 31.140%. Hence, the optimal structure has better crashworthiness.

In order to solve the noise reduction problem of acoustic emission signals with cracks, a method combining Complementary Ensemble Empirical Mode Decomposition (CEEMD) and wavelet packet (WPT) is proposed and named CEEMD-WPT. Firstly, the single Empirical Mode Decomposition (EMD) used in the traditional CEEMD is improved into the WPT-EMD with a more stable noise reduction effect. Secondly, after decomposition, the threshold value of the correlation coefficient is determined for the Intrinsic Mode Function (IMF), and the low correlation component is further processed by WPT. In addition, in order to solve the problem that it is difficult to quantify the real signal noise reduction effect, a new quantization index “principal interval coefficient (PIC)” is designed in this paper, and its reliability is verified through simulation experiments. Finally, noise reduction experiments are carried out on the real crack acoustic emission dataset consisting of tensile, shear, and mixed signals. The results show that CEEMD-WPT has the highest number of signals with a principal interval coefficient of 0–0.2, which has a better noise reduction effect compared with traditional CEEMD and Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). Moreover, the statistical variance of CEEMD-WPT is evidently one order of magnitude smaller than that of CEEMD, so it has stronger stability.

Simultaneous Localization and Mapping (SLAM) in dynamic environments remains a significant challenge for autonomous systems. To address this, a series of dynamic SLAM methods have been studied, including semantic-based and geometry-based models. Although these methods are effective, they usually incur substantial computational costs or sacrifice the overall accuracy of the model. In this work, an enhanced system built upon ORB-SLAM3 is proposed. It integrates lightweight YOLOv8-tiny object detection and IMU-based epipolar geometry for dynamic object detection, and leverages logit probability fusion to dynamically update the likelihood of a feature point being on a moving object. In addition, we put forward an adaptive thresholding strategy that gauges the level of scene dynamics by considering Inertial Measurement Unit (IMU) acceleration fluctuations, geometric outlier ratio, and the count of detected objects, so as to classify feature points effectively. Comprehensive experiments on the TUM dataset demonstrate that this method achieves significant effectiveness in both accuracy and robustness in dynamic scenarios.

Heat dissipation and collision safety are key factors affecting the safety of power battery systems. However, existing research on battery system safety only focuses on one aspect, with limited studies simultaneously addressing heat dissipation and collision safety. Therefore, this paper presents a gradient porosity aluminum foam battery module (GPAF-BM) with high heat dissipation efficiency and excellent crashworthiness by utilizing the enhanced heat transfer capability and good energy absorption characteristics of gradient open-cell aluminum foam (OCAF). To further improve its comprehensive performance, the heat dissipation efficiency and crashworthiness of the GPAF-BM are strictly optimized with multiple objectives. Additionally, to improve the efficiency of approximate model modeling, a new hybrid scaling multi-fidelity (NHSMF) approximate model construction method is proposed, which effectively improves the prediction accuracy of the model with a small sample size. Finally, the third-generation nondominant sorting genetic algorithm (NSGA-III) and normal boundary intersection (NBI) method are employed to ascertain the optimal solution. Compared to the original design, the optimized maximum intrusion displacement of the battery (Dmax) is 22.29% lower and the maximum battery temperature (Tmax) is reduced by 0.49 °C, the pressure drop of the (ΔP) decreased from the original design of 129.71 Pa to 115.53 Pa, a decrease of 10.93%. These improvements effectively enhance both the heat dissipation efficiency and crashworthiness of GPAF-BM.