Nano-scale coating wear measurement by introducing Raman-sensing underlayer

For gaining fundamental insight into coating wear mechanisms and increasing operational efficiency and automation degree of equipment in important application fields of coating techniques,it is of great importance to developing novel wear measurement techniques enabling nanoscale studies of coating wear in the running process,but this remains a significant challenge.Here,a facile strategy is reported to achieve accurate coating thickness quantification at nanoscale level,which is based on a bilayer structure:a top target layer of a-C:H(hydrogenated amorphous carbon)film is considered as a light attenuating and anti-wear layer while underlayer of silicon serves as Raman-sensing layer.Through constructing the relationship between the thickness of a-C:H and Raman intensity of attenuated silicon signal,the coating thickness quantification method is established and successfully applied to quantify coating wear in the friction process.This approach can effectively avoid remarkable errors caused by tribo-induced effects in the interface regions,demonstrating its advantage in error tolerance.Details about these tribo-induced effects are also elucidated by a combination of Raman spectroscopy,optical profilometer,EELS,and TEM.In particular,the proposed approach enables the possibility of measuring coating wear with oil film on top,which breaks an important limitation of existed wear measurement methods,i.e.,incapable of applying in oil-lubricated conditions.This approach can be used to quantify the wear condition of diverse target coatings and has the potential of online wear monitoring when combining a compact laser excitation and detection system.

Adaptive Fault-Tolerant Control During the Mode Switching for Electric Vehicle Dual-Mode Coupling Drive System

As a new drive system for electric vehicles,the dual-mode coupling drive system can automatically switch between centralized and distributed drive modes and realize two-speed gear shifting.Because the actuator’s displacement signal affects the mode-switching control,when failure occurs at the angle-displacement sensor,the mode-shifting quality is likely to drop greatly,even possibly leading to shift failure.To address the angle-displacement sensor failure and improve the reliability of the shift control,an adaptive fault-tolerant control method is proposed and verified.First,the effect of the output signal of the angle-displacement sensor in the mode-switching control process is analyzed.Then,an adaptive mode-switching fault-tolerant control method is designed based on the Kalman filter and fuzzy theory.Finally,the feasibility of the control effect is verified through simulations and vehicle experiments.The results indicate that the proposed method can effectively eliminate the signal noise of the angle-displacement sensor and successfully switch the modes when the sensor fails.It provides a reference for ensuring the working quality of similar electric drive systems under sensor failures.