Study on extraction of thiophene from model gasoline with brønsted acidic ionic liquids

Brønsted acidic ionic liquids(ILs),N-methylimidazole hydrogen sulfate([HMIm]HSO_(4))and N-methylpyrrolidone hydrogen sulfate([HNMP]HSO_(4)),are synthesized and employed as extractants to extract thiophene from model gasoline(thiophene dissolved in noctane).The effect of extraction temperature,extraction time and volume ratio of ILs to model gasoline on desulfurization rates is investigated.Then,the optimal desulfurization conditions are obtained:the ratio of ILs to model gasoline is 1∶1,extraction temperature is 50℃ for[HMIm]HSO_(4)and 60℃ for[HNMP]HSO_(4),extraction time is 60 min.Meanwhile,the desulfurization rate of[HNMP]HSO_(4)for model gasoline is 62.8%,which is higher than that of[HMIm]HSO_(4)(55.5%)under optimal conditions.The reason is discussed on the basis of the interaction energy between thiophene and ILs at the B3LYP/6-311++G(d,p)level.Furthermore,the total desulfurization rate of[HNMP]HSO_(4)and[HMIm]HSO_(4)reaches 96.4%and 94.4%,respectively,by multistage extraction.Finally,the used ILs can be reused by vacuum drying,and their desulfurization rates are not significantly decreased after recycling 7 times in single-stage desulfurization.

Vehicular Electronic Image Stabilization System Based on a Gasoline Model Car Platform

Noise,vibration and harshness(NVH)problems in vehicle engineering are always challenging in both traditional vehicles and intelligent vehicles.Although high accuracy manufacturing,modern structural roads and advanced suspension technology have already significantly reduced NVH problems and their impacts;off-road condition,obstacles and extreme operating condition could still trigger NVH problems unexpectedly.This paper proposes a vehicular electronic image stabilization(EIS)system to solve the vibration problem of the camera and ensure the environment perceptive function of vehicles.Firstly,feature point detection and matching based on an oriented FAST and rotated BRIEF(ORB)algorithm are implemented to match images in the process of EIS.Furthermore,a novel improved random sampling consensus algorithm(i-RANSAC)is proposed to eliminate mismatched feature points and increase the matching accuracy significantly.And an adaptive Kalman filter(AKF)is applied to improve the adaptability of the vehicular EIS.Finally,an experimental platform based on a gasoline model car was established to validate its performance.The experimental results show that the proposed EIS system can satisfy vehicular performance requirements even under off-road condition with obvious obstacles.