Constant spacing-based platooning systems cannot guarantee string stability if platoon members only use the preceding vehicle's information. To meet string stability specification, leader-predecessor-follower (LPF) platooning systems are proposed to incorporate the information of both the preceding vehicle and the platoon leader into the control loop. However, string stability of LPF platooning systems is very sensitive to communication and sensing delays. Even a delay of 5 milliseconds may render LPF platooning systems string-unstable. This paper focuses on a new approach to deal with communication and sensing delays in LPF platooning systems. A semi-constant spacing policy that synchronizes delayed measurements of system states obtained from different sources is proposed. This spacing policy aims at tracking the past information of the preceding vehicle to gurantee string stability. Moreover, the delay-synchronizing LPF platooning system puts the same requirements on controller parameters as the nominal LPF platooning system that is not affected by communication and sensing delays. Thus, control gains of the delay-synchronizing LPF platoon can be designed without considering delays.

There is a high demand for the implementation of metallic nanoparticle (NP) sintering technology for die attach in high-power electronics. The performance of this technology is superior to that of the technology involving the use of lead-free solders. Although Cu NP paste is potentially a low-cost material, it faces the challenge of oxidation during sintering. This may result in a significant deterioration of the mechanical, thermal, and electrical properties. Therefore, there are limited studies on the in-air sintering of Cu NP pastes. The present study demonstrated the in-air pressure-assisted low-temperature sintering of a commercial Cu NP paste. Furthermore, the sintering was performed without using a protective atmosphere, unlike that in most of the previously reported investigations. The sintering behavior was investigated at three levels of temperatures (200–240 °C) and five levels of pressures (5–25 MPa). The joints that were sintered at high temperatures and pressures exhibited condensed microstructures and high bonding strengths. High sintering temperatures accelerated the diffusion between Cu NPs, while high sintering pressure facilitated the removal of evaporated organic compounds and the air between NPs. This not only facilitated sintering but also prevented the oxidation of Cu. The optimal sintering conditions promoted the formation of 3D connections between the Cu NPs, thereby increasing the shear strength of the sample. The samples that were sintered at 240 °C and 10 MPa experiences the highest increase in the shear strength, furthermore, the microstructures were optimized under this condition. The shear strength of 28.1 ± 8.47 MPa was achieved under this condition, which satisfied the requirements for die attach in high power electronics applications, moreover, the sintering process was moderate and cost-effective. Therefore, the optimal sintering temperature and pressure for the in-air sintering of the Cu NP paste was concluded to be 240 °C and 10 MPa, respectively. The results indicated that in-air sintering with pressure assistance can be applied for die attach in the high-power electronics.

In this research, an optimal control-based Cooperative Adaptive Cruise Control (CACC) system is proposed. The proposed system is able to enforce a target time gap between platoon members and is formulated in the space domain instead of the time domain which is adopted by most optimal control-based CACC systems in the past. By having this change, its robustness against communication failure is greatly improved and thus minimum safety headway buffer is reduced which leads to better mobility. In addition, third-order vehicle dynamics are modeled into the proposed control in order to improve control precision when implemented in the field. Local stability and string stability are theoretically proven. The proposed system is evaluated by simulation. Results reveal that the proposed CACC system outperforms the state-of-the-art mathcal {H}_infty synthesis-based controller and linear feedback-based controller. The benefit of fuel consumption reduction ranges from 0.35% to 16.11%, while the benefit of CO2 emission ranges from 0.48% to 12.40%. Furthermore, the proposed CACC improves local stability from 11.03% to 25.90%, and string stability by up to 23.82%. The computation speed of the proposed method is 1.26 ms (with prediction horizon as 1.5 s and resolution as 0.1 s) on a regular laptop which indicates the proposed system's potential to be applied in real-time.

This study presents an experimental investigation of fatigue properties of cement paste at the microscale. A strong size dependence is found for the flexural fatigue life of the cement paste specimen. Microscopic observations on the fractured surfaces suggest that there is a higher density of nano-scale cracks generated during the fatigue loading compared to the static fracture. However, the fatigue damage evolution is found to be very slow and small even under high stress levels. The development of residual deformation for cement paste can be explained by the combined effects of viscoelastic deformation and fatigue cracking growth.

Communication delay is detrimental to the performance of cooperative adaptive cruise control (CACC) systems. In this paper, we incorporate communication delay explicitly into control design and propose a delay-compensating CACC. In this new CACC system, the semi-constant time gap (Semi-CTG) policy, which is modified on the basis of the widely-used CTG policy, is employed by a linear feedback control law to regulate the spacing error. The semi-CTG policy uses historical information of the predecessor instead of its current information. By doing so, communication delay is fully compensated, which leads to better stability performance. Three stability properties—local stability, string stability, and traffic flow stability—are analyzed. The local stability and string stability of the proposed CACC system are guaranteed with the desired time gap as small as the communication delay. Both theoretical analysis and simulation results show that the delay-compensating CACC has better string stability and traffic flow stability than the widely-used CACC system. Furthermore, the proposed CACC system also shows the potential for improving traffic throughput and fuel efficiency. Robustness of the proposed system against uncertainties of sensor delay and vehicle dynamics is also verified with simulation.

A cooperative lane-changing (CLC) motion planning algorithm for partially connected and automated environment is proposed in this study. Unlike conventional motion planner whose goal is merely enabling driving maneuver, this proposed algorithm takes one step further in terms of reducing oscillation and shockwave caused by lane change, hence improves transport mobility. The proposed motion planner is designed as a model predictive control which is solved by a dynamic programming-based numerical solution method. Since longitudinal automation is much more accessible than lateral automation, the motion planner requires only longitudinal automation in order to keep the design practical. The proposed motion planner is evaluated against the human driver. Sensitivity analysis is conducted in terms of the initial headway of the receiving gap. The results demonstrate that the motion planner reduces oscillation by 0.1%−9.4%. The variation is due to the changes in initial headway of receiving gap. The computation time is around 17-21 milliseconds showing great potential to be applied in real time.

Cooperative Adaptive Cruise Control (CACC) in previous researches typically refers to the linear controller with a gap policy. The system could not be designed to fulfill multiple objectives. This inspires the concept of optimal control based CACC in this paper. The basic procedure of the proposed controller is to gather the information collected by each vehicle to the computation unit first, then plan the trajectory of all the followers by solving an optimal control problem, and dispatch the optimal motion command to each vehicle at last. This paper models CACC under optimal control framework. A numerical approach inspired by dynamic programming is adopted to solve the control problem. The stability of the proposed controller is thoroughly investigated in terms of both local stability and string stability. To verify the concept of controller, solution, and the analysis about stability, simulation is carried out. The simulation verifies that the numerical method is effective with respect to computation time. Both theoretical analysis and simulation proved that the proposed optimal control based CACC is both local stable and string stable. The low computation burden, local stability, and string stability together guarantee the future implementation of the proposed controller.