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Inspired by the cross-section of a beetle’s elytron, hyperbolic lattice with double-layered feature has received increasing attention in recent years. This paper aims to investigate the compression behavior and energy absorption performance of a truss-based hyperbolic structure. The quasi-static compression simulation for the hyperbolic structure has been performed and validated with a compression test. Through compression simulation and test, the hyperbolic structure proved to show obvious twisting effect. To explore the influences of the geometric parameters in the mechanical properties of hyperbolic structure, this paper has designed 13 cells with varied rotation angle, height, and rod diameter, and investigated the mechanical properties of these configurations.

The origami structures have received increasing attention in recent years due to the high stiffness ratio and lightweight feature. This paper has proposed an origami-based honeycomb structure and investigated the mechanical properties of the structure. The compression response and energy absorption of the structure under quasi-static loading have been investigated experimentally and numerically. The numerical results closely matched the experimental results in terms of the compression force curve and deformation patterns. The effects of different structural parameters on the mechanical response and energy absorption characteristics were analyzed with the validated model. Finally, the comparative results show that the origami-inspired honeycomb structure, which is characterized by rotational folding mode under axial compression, has better performance in terms of mechanical response and energy absorption.

Due to the high center of gravity of medium-duty vehicles, rollover accidents can easily occur during high-speed cornering and lane changes. In order to prevent the deformation of the body structure, which would restrict the survival space and cause compression injuries to occupants, it is necessary to investigate methods for mitigating these incidents. This paper establishes a numerical model of right-side rollover for a commercial medium-duty vehicle in accordance with ECE R66 regulations, and the accuracy of the model is verified by experiment. According to the results, the material and size parameters of the key components of the right side pillar are selected as design variables. The response result matrix was constructed using the orthogonal design method for total mass, energy absorption, maximum collision acceleration, and minimum distance from the survival space.

Distributed drive electric vehicles (DDEVs), characterized by independently controllable torque at each wheel, redundant actuators, and highly integrated drive systems, are considered as the optimal platform for achieving intelligent driving with high safety and efficiency. This paper focuses on the trajectory tracking and lateral stability coordination control problems in high-speed emergency collision avoidance and autonomous lane change scenarios for DDEVs. A trajectory tracking control algorithm is proposed based on model predictive control (MPC) and coordinated optimization of distributed drive torques. The method adopts a hierarchical control architecture. Firstly, the upper-level trajectory planning layer calculates the lane change trajectory data. Based on the trajectory planning results, the middle-level controller designs a time-varying linear model predictive control method to solve the desired front wheel steering angle and additional yaw moment.

At present, the remote monitoring cloud platform of many automobile companies only displays the collected data information, and it does not fully mine the deep-level information of the data. This paper uses data mining and machine learning methods to build a driver's driving style and driving condition prediction and recognition model based on the historical driving information generated by the vehicle, so as to improve the supervision and safety of the driver and the vehicle by automobile companies and other automobile-related industries. First, 36 standard driving cycles are utilized to construct an initial operating condition block data set. Second, we obtain the feature variables of driving style and driving conditions through feature engineering, and two recognition model data sets use the principal component analysis (PCA) and clustering algorithm for data dimensionality reduction and cluster analysis.

In this paper, for the front wall of a certain automobile, the defects of drawing splits, excessive thinning and excessive springback in the sheet metal forming process are analyzed and predicted. The stamping process has been simulated. The influence of different technical parameters (blank holder force, stamping speed, die gap and friction coefficient) on the forming results was further investigated using the center composite experiment. Through preliminary finite element simulation, the main drawing defects and trimming springback were analyzed. The second-order response surface model was established to perform the multi-objective optimization design of the stamping process with a NGSA-II genetic algorithm. Based on the relevant simulation data, multiple springback compensations are performed on the die surface to reduce the final springback of the part to meet the requirements.

Thin-walled tubes have been mostly used in passive vehicle safety systems due to high crash energy absorption. The structures with negative Poisson’s ratio (NPR) property will contract to increase its stiffness. In this paper, a double-arrowed NPR structure is designed as a new energy-absorption filler for thin-walled tubes to apply as a novel crash energy absorber. Different beam thicknesses, angles and half cellular width are taken into account in the double-arrowed NPR filling tubes (DAFT) designing and the crashworthiness of the structures are analyzed by using validated nonlinear finite element method. The crashworthiness performances of DAFT are also compared with the singular NPR and hollow tube with the same outer dimension to show the efficiency of DAFT.

Regenerative braking is identified as an essential step toward extending cruising mileage for electric vehicle (EV). Braking energy recovery strategies usually focus on passenger EV and commercial EV is ignored. In this paper, an energy-efficient braking torque distribution strategy is proposed for a rear-axle drive commercial EV to improve braking energy recovery and safety. Firstly, the braking force distribution curve is determined referring to the EU braking law for commercial vehicle and the ideal braking distribution curve. Secondly, a novel braking torque distribution strategy is established adopting fuzzy control algorithm, where the ratio between hydraulic braking torque and regenerative braking torque is updated instantaneously according to vehicle velocity, braking strength and state of charge of battery. Then, the corresponding controller is synthesized on ideal braking condition and several classic cycles.

The design of aluminum foam reinforced thin-walled tubes has garnered much interest recently due to the high energy absorption capacity of these tubes. As a new kind of engineering composite material, aluminum foam can hugely increase the crashworthiness capacity without sacrificing too much weight. In this paper, axisymmetric thin-walled hollow tubes with four different kinds of cross-sections (circular, square, hexagonal and octagonal) are studied to assess their performance for crashworthiness problems. It is found that the tube with square cross-section has the best crashworthiness performance under axial impact. To seek optimal designs of square aluminum foam reinforced thin-walled tubes, a surrogate modeling technique coupled with a multi-criteria particle swarm optimization algorithm has been developed, to maximize specific energy absorption (SEA) and minimize peak crash force (PCF).

As is known to all, the modeling of vehicles and durability simulation is becoming more accurate and more compatible with physical testing, resulting in shortening of the analysis process, and a lower cost. It would be more advantageous in the future to simulate the full vehicle system before the physical testing. Thus, in the analysis of vehicle durability performance, the need for more precise rigid and flexible vehicle modeling and more precise external loadings acquisition method is increasing. In view of the typical difficulties faced in the vehicle multi-body dynamics (MBD) simulation and in the associated loading extraction, this paper proposes a method to achieve accurate external vehicle loadings by virtual simulation. This method is performed based on the physical testing and compensates for the imperfections in the MBD modeling, thus being able to improve the quality of fatigue life prediction (FLP).