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Variable inter-vehicle distances influence significantly the wind resistance of platoon vehicles due to the sheltering of airflow. Accurate air drag estimation is extremely important for platoons in scenarios like energy-oriented driving and high-precision tracking. Most aerodynamic researchers have performed qualitative analysis of wind resistance for equally inter-spaced platoons, while the quantitative description of wind resistance variation with coupled inter-vehicle distances is rare. In addition, data measured through offline wind tunnel experiments, Computational Fluid Dynamics (CFD) simulations, or road tests via fuel consumption calibration for a period of time is unsynchronized, which may be unconvincing for real air drag estimation on road. Aiming at the quick and accurate approximation of platoon wind resistance, this paper proposes a novel and universal modeling strategy combining offline CFD simulation, online air drag observation, and real-time parameter identification. The variation characteristics of air drag with distance of a longitudinal platoon consisting of three homogeneous C-class Notchback cars are analyzed by CFD simulation. With appropriate data processing, a well-designed basis function is summarized. Then a novel wind resistance separation method combining Back-Propagation Neural Network (BPNN) and Extended State Observer (ESO) is proposed. Using the observed data stored in experience memory, the hybrid optimization method via particle swarm optimization (PSO) and gradient descent with momentum (GDM) is employed to identify the model parameters toward high accuracy and global optimality. Results of Hardware-In-the-Loop (HIL) experiment show that the proposed modeling strategy realizes effective real-time observation and accuracy description; the developed approximation model can describe the platoon wind resistance with continuous and coupled inter-vehicle distances, with the RMSE less than 11.4%.

In this research, thermoplastic polyimide (TPI) were welding via friction stir spot welding (FSSW) in order to evaluate the feasibility of the technology. The welding tool with a tri-flute pin was used for keeping the welding effectiveness. The effect of the rotation speed and dwell time on the microstructure and shear strength was studied. The results shows that the number of gap defects between the shoulder affect zone and the pin affect zone decreased with the increase of the rotation speed. The boundary of the shoulder affect zone and the pin affect zone was no clear when increasing the dwell time from 10 s to 20 s. Long dwell time could increase the mixing time and reduce the materials viscosity, which made the structure was denser. The maximal shear strength was obtained 85.5% of the base materials. The differential scanning calorimetry (DSC) results indicated that the melting behaviour of different regions was no obvious difference. It indicated that FSSW had a feasible and potential technology to join the high temperature resistant engineering plastics.

In this paper, friction stir spot welding (FSSW) technology was introduced to join 7075 Al alloy to polyimide (PI) sheets. The effects of the FSSW parameters and laser textures on the microstructure and tensile shear load of the Al/PI joint were studied. The optimum FSSW parameters were the rotation speed of 2400 r/min, the plunge depth of 0.4 mm, the dwell time of 20 s, and the plunge speed of 10 mm/min. The tensile shear load of the joint increased owing to the laser textures in the Al alloy surface. Cross-sections showed that the mechanical locking was found between the Al alloy and PI. The XPS results revealed that no chemical bond were formed at the welding interface after laser textures. The joining mechanism of Al 7075 and PI was main the mechanical locking.