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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.

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.

In order to reflect the actual power consumption of logistics electric vehicles in a city, sample real vehicle road data. After preprocessing, the short-stroke analysis method is used to divide it into working blocks of no less than 20 seconds. Based on principal component analysis, three of the 12 characteristic parameters were selected as the most expressive. K-means clustering algorithm is adopted to obtain the proportions of various short strokes, according to the proportion, select the short stroke with small deviation degree to combine, and construct the driving cycle, it has the characteristics of low average speed, high idle speed ratio and short driving distance. AVL-cruise software builds the vehicle model and runs the driving cycle of urban logistic EV. Compared with WLTC, the difference in power consumption is 34.3%, which is closer to the actual power consumption, the areas with the highest motor speed utilization are concentrated only in the idle area.

The front end structure is an important role in protecting the vehicle and passengers from harm during the collision. Increasing its protective capacity can be achieved by increasing the thickness or replacing high-strength materials. Most of the current research is analyzed separately from these two aspects. This paper proposes a multi-objective optimization method based on weighting factor analysis, which combines material and thickness selection. Firstly, the optimized components are determined based on the 100% frontal collision simulation results. Secondly, six thicknesses and two materials of the front part of the vehicle body are selected as design variables to construct an orthogonal test design. In this paper, a weight-based multi-factor optimization method is used to numerically analyze the response results obtained by orthogonal experiments. Analyze the impact of each factor on the optimization goal to select the most reliable optimization.

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).