In the field of automobile development, sufficient structure strength is the most basic objective to be accomplished. Typically, method of strength analysis could be divided into static strength and dynamic strength. Analysis of static strength constitutes the major part of the development, but the supplement of dynamic strength is also dispensable to assure structural integrity. This paper presents a methodology about analyzing the impact strength of body structure based on a Multi-body Dynamics (MBD) and Finite Element Analysis (FEA) combined method. Firstly, the full vehicle MBD model consists of Curved Regular Grid (CRG) road model, Flexible Ring Tire (FTire) model and dynamic deflection-force bump stop model was built in Adams/Car. Next, Damage Initiation and Evolution Model (DIEM) failure criteria was adopted to describe material failure behavior. Besides, six groups of specimens including tensile, R5, R20, shear, T-shear and punch were designed to identify parameters of the DIEM model. Then, misuse condition test on the Impact road was conducted by test vehicle equipped with Six-Axes Wheel Force Transducer (WFT) and corresponding experimental data were correlated with MBD simulation results to check the accuracy. Finally, an explicit dynamic analysis of body was performed in Abaqus to investigate the structural misuse behavior. On the whole, simulation results of loads and structure response are in good accordance with experiment. Noticeable plastic deformations on the top mount area of body were observed and macroscopic fracture generated on the ribs of upper mounting seat was very close to that of real failure state.

This study is aimed at investigating the influence of skull fractures on traumatic brain injury induced by blunt impact via numerous studies of head–ground impacts. First, finite element (FE) damage modeling was implemented in the skull of the Total HUman Model for Safety (THUMS), and the skull fracture prediction performance was validated against a head–ground impact experiment. Then, the original head model of the THUMS was assigned as the control model without skull element damage modeling. Eighteen (18) head–ground impact models were established using these two FE head models, with three head impact locations (frontal, parietal, and occipital regions) and three impact velocities (25, 35, and 45 km/h). The predicted maximum principal strain and cumulative strain damage measure of the brain tissue were employed to evaluate the effect of skull fracture on the cerebral contusion and diffuse brain injury risks, respectively. Simulation results showed that the skull fracture could reduce the risk of diffuse brain injury risk under medium and high velocities significantly, while it could increase the risk of brain contusion under high-impact velocity.

In this paper, the energy absorption characteristics of CFRP (Carbon Fiber Reinforced Polymer) laminates with different fiber modules under normal and oblique impacts are studied. The quasistatic basic mechanical properties test and low-speed drop weight impact test are carried out, and the inner damage is detected by C-scan. The material model includes the inter-laminar material model and the intra-laminar material model. The latter material model is calculated by the micro-mechanical method. The homogeneous method is used in each finite element calculation time step, and the cohesive element is used between the layers. The results of simulation and experimental are close. The impact angles of six fiber modulus composite laminates are evaluated by the four impact angles of 0 degrees, 10 degrees, 20 degrees and 30 degrees. The impact parameters, such as maximum contact force and contact time, are found linearity changes along with the impact angle and fiber modulus. However energy absorption presents a non-linear relationship to impact angle and fiber modulus. It is found that the reason is caused by the intra-laminar mechanical behavior. For the T300 CFRP, when the impact angle is less than 20 degrees, the energy absorption differs by only 3%, and the impact angle has little effect on energy absorption.

Unidirectional carbon fiber composite material is one of the most common types of composites employed in vehicles, and its bending performance plays an important role in crash safety, especially in side pole impact. This study aimed to redesign one of the most important components of the side structure of a vehicle, the rocker panel, with unidirectional carbon fiber composite material. Our results show that it is not easy to acquire the same bending performance as that of a steel rocker panel by merely replacing it with carbon fiber material and increasing the wall thickness. Therefore, reinforcements were employed to improve the bending performance of the carbon fiber rocker panel, and a polypropylene reinforcement method achieved a weight reduction of 40.7% compared with high-strength steel.

In engineering design optimization, the usage of hybrid metamodels (HMs) can take full advantage of the individual metamodels, and improve robustness of the predictions by reducing the impact of a poor metamodel. When there are plenty of candidates, it is difficult to make decisions on which metamodels to choose before building an HM. The decisions should simultaneously take into account of the number, accuracy and diversity of the selected metamodels. To address this problem, this research developed an efficient decision-making framework based on partial least squares for metamodel screening. A new significance index is firstly derived from the view of fitting error in a regression model. Then, a desirable metamodel combination which consist of only the significant ones is subsequently configured for further constructing the final HM. The effectiveness of the proposed framework is demonstrated through several benchmark problems.

为提升某乘用车型仪表板和中控箱系统的碰撞吸能性,搭建了适用于LS-DYNA求解器的有限元仿真分析模型.基于达朗贝尔动力学原理推导了碰撞加速度计算公式,分别从金属支架结构形式、内饰造型以及内饰零件刚度角度进行碰撞加速度优化.仿真和试验结果表明,优化后的仪表板和中控箱系统碰撞加速度明显降低,吸能性满足国家标准要求.

Dynamic mechanical loading, e.g. impact, is one of the major catastrophic factors that trigger short-circuit, thermal runaway, or even fire/explosion consequences of lithium-ion batteries (LIBs). In this study, the mechanical integrity and electrical coupling behaviors of lithium-ion pouch cells under dynamical loading were investigated. Two types of experiments, namely compression and drop-weight tests, are designed and conducted. The state-of-charge (SOC) and loading rate dependencies of batteries, as well as their coupling effect, are examined. Furthermore, the interaction between force response and electrical behavior of battery is investigated through real-time monitoring of voltage change during loading. Experiments on LiCoO2 lithium-ion pouch cells show that the higher SOC and loading rates increases battery structure stiffness. In addition, loading rate intensifies battery structure stiffening with the SOC effect. Results indicate that the deformation and material failure of battery component together determine the electrical behavior of battery. Higher loading rate leads to faster voltage drop and more severe internal short-circuit. This short-circuit discharging process in turn affects the force response in dynamic loading. Results may provide useful insights into the fundamental understanding of electrical and mechanical coupled integrity of LIBs and lay a solid basis for their crash safety design.

Metamodel based robustness design is commonly used to mitigate the consequences of variability without removing its underlying sources. However, uncertainties introduced by metamodels should be properly addressed before conducting design optimization. In addition, the measurable data uncertainties from physical tests and computer simulations are also unneglectable. Relevance Vector Regression (RVR) is a probability model based on the Bayesian learning framework. It shows potential in estimating the prediction uncertainty. This paper proposes an alternative RVR based robustness design procedure considering the design variables uncertainty, data uncertainty and metamodeling uncertainty. Based on the fundamental theory of RVR, simplified expressions of the response mean and variance is derived for robustness design accounting for three kinds of uncertainties. The formulation of RVR based robustness design is then built. Double loop Monte Carlo sampling is used to solve this optimization problem. An engineering example is used to demonstrate the proposed method and comparative studies are conducted between the proposed method and traditional robustness design.

507 Lithium-ion batteries are currently widely used in various industries, including automotive industry. Thus, the study of battery mechanical integrity subject to dynamic loading is critical for vehicle safety, which still remains rare. In this paper, first of all, by taking the advantage of previous efforts on quasi-static mechanical experiments on lithium-ion batteries, a new battery... /react-text react-text: 508 /react-text

Zn2SnO4-based anode materials have recently attracted considerable attention due to their high capacity and low price for lithium-ion batteries. However, their performance is affected by temperature and temperature-dependent characters have not been investigated sufficiently. In this regard, we tested the electrochemistry performance of Co-doped Zn2SnO4–graphene–carbon (Co–ZTO–G–C) nanocomposite anode at various temperatures (−25, 25 and 60°C) and analyzed the main limitations and improvements of its low- and high-temperature behavior. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) results demonstrated that severe concentration polarization, the absence of Zn2SnO4/Zn(Sn) redox couple and large charge-transfer resistance Rct limited its low-temperature performance. Further electrochemical performance analysis indicated that the doped Co could effectively decrease Rct of the nanocomposite and improve its capacity at low temperature. It also suggested that graphene and carbon layer contributed to maintaining its capacity during high-temperature cycles. Field emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD) results revealed that the performance degeneration of the nanocomposite at elevated temperature was mainly attributed to severe volume expansion/contraction of Zn2SnO4 nanoparticles and destruction of Zn2SnO4 cubic structure. The XRD results also showed that the cubic structures of Zn2SnO4 at all temperatures were destroyed after cycling, which led to cyclic performance degeneration of the Co–ZTO–G–C nanocomposite.

Vehicle crashes are one of the leading causes of catching fires in electrical vehicle accidents, while the mechanical intrusion caused failure of battery which is the most common cause of these fires. In order to reduce the risk of catching fires in electrical vehicle accidents, the crash failure threshold of battery module, which could be offered as an important design parameter in CAE analysis of battery systems’ safety, is needed to be well studied. So a test program based on drop tower was designed. A series of dynamic impact tests were performed in length direction, width direction, and thickness direction. Punch force, displacement of punch, as well as the voltage of the battery module were measured. Results showed that impact directions have great influences on mechanical characteristics, electric voltage, and crash failure threshold of battery module.

Lithium-ion batteries (LIBs) are now widely applied to electric vehicles, such that the inevitable mechanical abuse safety problem during possible vehicle accidents has become a prominent barrier. This study initially proposes a multiphysics computational framework model that couples mechanical, thermal, and electrochemical models to describe the complete process for a single 18650 LIB cell subjected to abusive mechanical loading from initial deformation to the final thermal runaway. The designed experiments reveal the proposed model’s suitable agreement with the established multiphysics model. Parametric studies in terms of governing factors, such as state of charge, loading speed, and deformation displacement, are conducted and discussed. These studies reveal the underlying mechanism for the mechanical abuse safety of LIBs. This model can lay a solid foundation to understand the electrochemical and mechanical integrity of LIBs, as well as provide critical guidance for battery safety designs.

驾驶员在驾驶过程中不可避免会接受二次任务，紧急工况下注意力的分散危及生命安全。本文通过分析驾驶员手持电话与微信语音两种通信方式下的避撞反应能力实验，对驾驶员生理特性变化进行了详细分析。有八名测试者参与了模拟器实验，限定时速保持在50-70km/h.实验所采集的心率，皮肤电信号，和呼吸灯生理指标均可表征不同紧张程度下的驾驶员精神负荷状态。结论表明两种接听方式工况下精神负荷上升，微信语音任务高于手机接听任务，各参数变化特征可为前方防碰撞系统参数修改提供一定的理论依据。