The failure mechanism of square lithium iron phosphate battery cells under vibration conditions was investigated in this study, elucidating the impact of vibration on their internal structure and safety performance using high-resolution industrial CT scanning technology. Various vibration states, including sinusoidal, random, and classical impact modes, were tested to simulate real-world usage scenarios. The findings demonstrate that different vibration conditions exert varying degrees of influence on the battery cells. Despite experiencing slight deformation and displacement after exposure to vibrations, their overall performance remains stable, with no significant safety hazards detected. Moreover, it was observed that while the side gap increases due to the partial absorption of impact load by both the battery cells and connection components, the bottom gap remains unchanged. This study holds immense significance in enhancing electric vehicle safety and reliability, while providing a scientific foundation for future optimization designs of lithium iron phosphate batteries.

Quick-replacement battery technology has the advantages of eliminating mileage issues, extending battery life and reducing cost. The battery box plays an important role in carrying and protecting the on-board battery pack. However, fatigue life has not been well-established in changeable operating environments and driving conditions; hence, this knowledge gap is the focus of this paper. Here, SolidWorks (SolidWorks, Waltham, MA, USA) was used to establish a three-dimensional model of a quick-replacement battery box for electric vehicles, OptiStruct software (Altair, Detroit, MI, USA) was used for sweep frequency and random vibration analyses, and random vibration fatigue analysis was carried out using Ncode software (ANSYS, Pittsburgh, PA, USA). The quick-replacement battery box structure was then optimized according to the analysis results and lightweight targets. The results of sweep frequency and random vibration analyses showed that the maximum stress of a quick-replacement battery box is 39.058 Mpa. Compared with the allowable stress of the DC01 material at 150 Mpa, a significant margin is still present. The results of random vibration fatigue analysis showed that the minimum service life of a quick-replacement battery box is 5.740 × 10¹⁰, which meets the design requirements. Following optimization design, the maximum stress of a quick-replacement battery box was 71.197 Mpa, still meeting the allowable stress of the DC01 material at 150 Mpa and effectively alleviating the stress concentration. Furthermore, the optimized quick-replacement battery box was approximately 4 kg lighter. Therefore, optimization of the quick-replacement battery box is feasible and necessary. The results provide great theoretical and engineering significance for the design and optimization of quick-replacement battery boxes for electric vehicles.

The objective of this paper was to investigate and design a novel vertical- and horizontal-arm independent suspension system aimed at enhancing the autonomous obstacle-crossing capabilities of unmanned ground platforms in complex, unstructured environments such as mountainous regions, hills, and mining areas. By thoroughly considering factors such as the suspension structure design, changes in the centroid position, distribution of driving forces, and dynamic stability analysis, we proposed an innovative suspension structure. An unmanned ground platform model equipped with this suspension system was developed using ADAMS and MATLAB/Simulink. Subsequently, a joint simulation was conducted to validate the performance of the suspension system. The results indicated that the unmanned ground platform could successfully traverse vertical steps up to 370 mm high and trenches measuring up to 600 mm wide. Furthermore, when confronted with intricate obstacles including vertical barriers, trenches, and side slopes, the platform demonstrated exceptional traversing capabilities. In conclusion, the proposed suspension system significantly enhances both the obstacle-surmounting ability and the terrain adaptability of unmanned ground platforms while providing crucial technical support for their deployment in complex unstructured environments.

In order to counter the problems of cracks and large area fractures in the welding points of quick-replacement battery boxes for electric vehicles (which may lead to the concentration of stress), in this study, a fatigue analysis of the welding points, based on a load spectrum, was used to predict welding points’ fatigue and improve the structural life of quick-replacement battery boxes. Firstly, a model of the quick-replacement battery box was established in SolidWorks software; secondly, the welding points’ fatigue was analyzed using the Optistruct module of HyperMesh software, and the topology of the quick-replacement battery box was optimized according to the results of the analysis; finally, for testing purposes and to achieve a lighter weight and an improved structural life, the fatigue of the welding points of the optimized battery box was analyzed. The results of the analysis showed that the force of the quick-replacement battery box was primarily concentrated at the connection between the middle bottom plate and the partition. Additionally, retaining the number of welding points at the hanging ear was shown to be beneficial for maintaining stiffness during electric vehicle operation; however, the number of welding points at the partition connection could be appropriately reduced. Before optimization, the maximum fatigue damage values of the welding points were 2.763 × 10⁻⁶, 3.833 × 10⁻⁶, and 6.728 × 10⁻⁶, respectively, satisfying the criteria of fatigue damage to the welding points. After optimization, the fatigue damage values of the welding points in the quick-replacement battery box were significantly reduced to 4.431 × 10⁻⁸, 4.562 × 10⁻⁸, and 8.885 × 10⁻⁸, respectively, compared with their pre-optimized levels. Consequently, the stress concentration was alleviated effectively, thereby meeting the conditions for fatigue damage. These results have important theoretical and engineering significance for the design and optimization of quick-replacement battery boxes for electric vehicles.

Reliable state estimation is critical for the safe operation of second-life battery systems but is severely hindered by significant parameter heterogeneity arising from diverse historical aging conditions. Traditional static models struggle to adapt to such variability, while online identification methods are prone to divergence under dynamic loads. To overcome these challenges, this paper proposes a Dual-Anchor Adaptive Fusion Framework for robust State of Charge (SOC) estimation and State of Health (SOH) soft-sensing. Specifically, to establish a reliable physical baseline, an automated Dynamic Relaxation Interval Selection (DRIS) strategy is introduced. By minimizing the fitting Root Mean Square Error (RMSE), DRIS systematically extracts high-fidelity parameters to construct two “anchor models” that rigorously define the boundaries of the aging space. Subsequently, a residual-driven Bayesian fusion mechanism is developed to seamlessly interpolate between these anchors based on real-time voltage feedback, enabling the model to adapt to uncalibrated target batteries. Concurrently, a novel “SOH Soft-Sensing” capability is unlocked by interpreting the adaptive fusion weights as real-time health indicators. Experimental results demonstrate that the proposed framework achieves robust SOC estimation with an RMSE of 0.42%, significantly outperforming the standard Adaptive Extended Kalman Filter (A-EKF, RMSE 1.53%), which exhibits parameter drift under dynamic loading. Moreover, the a posteriori voltage tracking residual is compressed to ~0.085 mV, effectively approaching the hardware’s ADC quantization limit. Furthermore, SOH is inferred with a relative error of 0.84% without additional capacity tests. This work establishes a robust methodological foundation for calibration-free state estimation in heterogeneous retired battery packs.

This study systematically investigated the structural damage and electrochemical performance changes in 18650 cylindrical lithium-ion batteries under multiple impacts through a 10 kg drop-hammer impact test. The experimental results showed that as the state of charge (SOC) increased from 25% to 75%, the battery’s stiffness increased and its impact resistance improved, but the electrolyte leakage intensified, with a higher risk of leakage at high SOCs. An increase in the impact force led to enhanced voltage fluctuations and a continuous increase in deformation. After an impact of 500 mm, the voltage decreased about 0.02 V, while after an impact of 1000 mm, it dropped about 0.04 V. Axial impacts caused a sudden voltage drop to 1.96 V, resulting in permanent failure; compared with planar impacts, cylindrical surface impacts are more likely to cause compression in the middle and warping at both ends, significantly increasing the risk of internal short circuits. CT scans revealed that the battery porosity can reach up to 3.09% under high impact energy, and the deformation rate can reach 28.39%. The research results provide a quantitative experimental basis for the impact-resistant design and safety assessment of power batteries.