This paper presents a novel multi-objective coordinated adaptive cruise control (ACC) algorithm based on a model predictive control (MPC) framework which can comprehensively address issues regarding longitudinal car-following performance, lateral stability, as well as vehicle safety. During the car-following, vehicle dynamics, illustrating the forces acting on the tire contact patches, are established. To simplify the tightly coupled dynamics system, a state-feedback based disturbance decoupling method is employed, by which longitudinal and lateral dynamics can be completely decoupled. Furthermore, the traditional MPC control with a constant weight matrix will probably not be able to solve time-varying multi-objective coordinated optimization issues, especially in transient scenarios. A weight coefficient self-tuning strategy is therefore suggested by which the weight coefficient for each sub-objective can be adjusted automatically with the change of traffic scenarios, accordingly improving the overall car-following performance. The simulations show that the control algorithm utilizing the suggested self-tuning strategy reaps significant benefits in terms of longitudinal car-following performance, while at the same time maintaining a small lateral stability error range.

Micro-Pirani vacuum sensors usually operate at hundreds of microwatts, which limits their application in battery-powered sensor systems. This paper reports a diode-based, low power consumption micro-Pirani vacuum sensor that has high sensitivity. Optimizations to the micro-Pirani vacuum sensor were made regarding two aspects. On the one hand, a greater temperature coefficient was obtained without increasing power consumption by taking advantage of series diodes; on the other hand, the sensor structure and geometries were redesigned to enlarge temperature variation. After that, the sensor was fabricated and tested. Test results indicated that the dynamic vacuum pressure range of the sensor was from 10⁻¹ to 10⁴ Pa when the forward bias current was as low as 10 μA with a power consumption of 50 μW. Average sensitivity was up to 90 μV/Pa and the sensitivity of unit power consumption increased to 1.8 V/W/Pa. In addition, the sensor could also work at a greater forward bias current for better sensor performance.

Wafer bonding of a silicon carbide (SiC) diaphragm to a patterned SiC substrate coated with aluminum nitride (AlN) film as an insulating layer is a promising choice to fabricate an all-SiC capacitive pressure sensor. To demonstrate the bonding feasibility, a crystalline AlN film with a root-mean-square (RMS) surface roughness less than ~0.70 nm was deposited on a SiC wafer by a pulsed direct current magnetron sputtering method. Room temperature wafer bonding of SiC-AlN by two surface activated bonding (SAB) methods (standard SAB and modified SAB with Si nano-layer sputtering deposition) was studied. Standard SAB failed in the bonding, while the modified SAB achieved the bonding with a bonding energy of ~1.6 J/m². Both the microstructure and composition of the interface were investigated to understand the bonding mechanisms. Additionally, the surface analyses were employed to confirm the interface investigation. Clear oxidation of the AlN film was found, which is assumed to be the failure reason of direct bonding by standard SAB.