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In order to study the fast filling problem of large-capacity on-board hydrogen storage tank for highway passenger cars, a computational fluid dynamics (CFD) simulation model of 134L large-capacity hydrogen storage tank was established. By simulating different pre-cooling temperatures and mass flow rates, the temperature distribution and thermal transmission in the tank were observed. Due to the large ratio of length to diameter of the hydrogen tank, the temperature distribution is extremely uneven during the whole filling process, and the high temperature area is mainly concentrated in the tank tail. And the heat transfer between the gas and the tank wall is not obvious under the low and constant mass flow rate. The temperature rise process during the whole filling process under different mass flow conditions was simulated to satisfy the highest safe temperature limit.

Faced with intricate traffic conditions, the single sensor has been unable to meet the safety requirements of Advanced Driver Assistance Systems (ADAS) and autonomous driving. In the field of multi-target tracking, the number of targets detected by vision sensor is sometimes less than the current tracks while the number of targets detected by millimeter wave radar is more than the current tracks. Hence, a multi-sensor information fusion algorithm is presented by utilizing advantage of both vision sensor and millimeter wave radar. The multi-sensor fusion algorithm is based on centralized fusion strategy that the fusion center takes a unified track management. At First, vision sensor and radar are used to detect the target and to measure the range and the azimuth angle of the target. Then, the detections data from vision sensor and radar is transferred to fusion center to join the multi-target tracking with the prediction of current tracks.