Vehicle interior noise is an important factor affecting ride comfort. To reduce the noise inside the vehicle at the vehicle body design stage, a finite element model of the vehicle body must be established. While taking the first-order global modal of the body-in-white, the maximum sound pressure level of the target point in the vehicle, the body mass, and the side impact conditions into account, the thickness of the body panel as determined via sensitivity analysis is treated as the input variable, and the sample is determined by following the Hamersley experimental design. Specifically, the Elman neural network predicts the noise value in the vehicle, and a vehicle body structure optimization method that comprehensively considers NVH performance and side impact safety is established. The prediction errors of the Elman neural network algorithm were within 3%, which meets the prediction accuracy requirements. To achieve satisfactory restraint performance, the maximum sound pressure level of the target point in the vehicle is reduced by 5.92 dB, and the maximum intrusions of the two points on the B-pillar inner panel are reduced by 31.1 mm and 33.71 mm, respectively. The side impact performance is improved while the noise inside the vehicle is reduced. This study provides a reference method for multidisciplinary research aiming to optimize the design of vehicle body structures.

The influence of low-pressure environment on centrifugal fan’s flow and noise characteristics was studied experimentally and numerically. A testbed was established to conduct the experimental test on the performance of a centrifugal fan, and the characteristic curve and power consumption curve of the fan under different pressure were obtained. Then the simulation model of the centrifugal fan was established, which was used to simulate the working process of centrifugal fan under different negative pressures. The results showed that the total pressure and static pressure of the fan decrease with the decrease of the ambient pressure. The total and static pressures of the fan under 60 kPa pressure condition decreased by 42.3% and 38.3%, respectively, compared with those of fan under the normal pressure. The main reason for this phenomenon is that the decrease of the environmental pressure leads to the decrease of air density. Besides, with the drop of environmental pressure, the sound pressure and sound power of the fan noise decreases.

The green wave coordinated control model has evolved from the basic bandwidth maximization model to the multiweight approach to an asymmetrical multiband model and a general signal progression model with phase optimization to improve the operational efficiency of urban arterial roads and reduce driving delays and the amount of exhaust gas generated by vehicles queuing at intersections. However, most of the existing green wave models of arterial roads are based on a single phase pattern and little consider the optimization of the combination of multiple phase patterns. Initial queue clearing time is also considered at the green wave progression line in the time–space diagram, which leads to a waste of green light time. This study proposes a coordination control optimization method based on an asymmetrical multiband model with phase optimization to address the abovementioned problem. This model optimizes four aspects in the time–distance diagram: phase pattern selection, phase sequence, offset, and queue clearing time. Numerical experiments were conducted using the VISSIM micro traffic simulation tool for intersections along Kunlunshan South Road in Qingdao, and the effect of green wave coordination was evaluated using hierarchical analysis and compared with the signal-timing schemes generated by the four models: the multiweight approach, the improved multiweight approach, an asymmetrical multiband model, and a general signal progression model with phase optimization. The results show that an asymmetrical multiband model with phase optimization obtains a total bandwidth of 314 s in both directions. In the outbound direction, average number of stops, average travel speed, average travel time, and average delay time improve by 16%, 7.9%, 17.9%, and 15.6%, respectively. In the inbound direction, they improve by 43.7%, 16.1%, 40.7%, and 36%, respectively. Polluting gas emissions and fuel consumption improve by 17.9%. The applicability of the optimization method under different traffic flow conditions is analyzed, and results indicate a clear control effect when the traffic volume is moderate and the turning vehicles on the feeder roads are few. This work can provide a reference for the optimization of subsequent arterial signal coordination and also has indirect significance for environmental protection to a certain extent.

For the serrated heat transfer surface, the heat transfer and flow properties are investigated with external vibration excitation using numerical simulation method. By using the dynamic grid to realize the vibration of the fin wall, the impacts of frequency, amplitude, wind velocity and ambient temperature on vibration-strengthened heat transfer are investigated. The results show that vibration impacts the temperature distribution around the fin, interferes with the flow of air, causes the air to form a certain angle with the fin wall, thus preventing the development of the boundary layer and achieving strengthened heat transfer. The impact of amplitude on vibration-strengthened heat transfer is smaller than that of frequency, and low wind velocity is more favorable to the role of vibration-strengthened heat transfer, and the change of ambient temperature has less impact. Compared with the stationary condition, wall vibration can improve the average heat transfer coefficient by up to 66.6%.

The dust-collection system, as the core of a sweeper vehicle, directly inhales dust particles on the pavement. The influence of variable operational conditions on particle-separation performance was investigated using computational fluid dynamics (CFD) Euler–Lagrange multiphase model. The particle-separation performance efficiency and retention time were used to evaluate the dust-collection efficiency. The uniform design (UD) and multiple regression analysis (MRA) methods were employed to predict and optimize the effects of reverse-blowing flow rate, pressure drop, and traveling speed on separation efficiency. The results indicated that the dust-collection performance initially increased and then decreased with increasing reverse-blowing flow rate. As the pressure drop increased, there was an increase in total dust-collection efficiency. However, the efficiency decreased with increasing traveling speed. The regression model showed that the proposed approach was able to predict the particle collection efficiency accurately. In addition, the optimum operational conditions were obtained, namely a reverse-blowing flow rate of 2100 m³/h, a traveling speed of 5 km/h, and a pressure drop of 2400 Pa. The maximum particle-separation efficiency was 99.10%, which showed good agreement with the experimental results.

Preload optimization is very important for ultrasonic motors’ design and application. In this paper, a novel method for a traveling-wave rotary ultrasonic motor is proposed. Firstly, based on linear regression and the analytic hierarchy process (AHP), the mapping between the drive characteristics, mechanical characteristics, speed stability, and preload of the traveling-wave-type rotary ultrasonic motor was established. Then, the characteristic curves of stalling torque, no-load speed, maximum efficiency, and speed stability with the change of preload method were measured with a new test platform. Finally, three traveling-wave rotary ultrasonic motors with optimized preload were used in a cooperative manipulator for validation. The experimental results showed that when the preload was optimized from 200 N to 310 N, the stalling torque of the motor increased by 20.7%, the maximum efficiency increased by 15.3%, the standard deviation of the speed decreased by 53.8%, and the no-load speed decreased by 5.5%. Therefore, it can be seen that the new preload optimization approach can significantly improve the performance indexes of ultrasonic motors and meet the practical requirements of direct-drive cooperative manipulators in engineering applications. The new preload optimization method offers advantages in motor output performance compared to conventional methods.