公开(公告)号：US20240309999A1

公开(公告)日：2024-09-19

申请号：US18605923

申请日：2024-03-15

Applicant: Beijing Institute of Technology

Inventor： Jianwei Li ,  Chonghao Yan ,  Xinming Wan ,  Xuechao Wang ,  Rongxue Kang ,  Zhiwei Zhao

IPC: F17C13/02 ,  G01M3/32 ,  G06V10/82

CPC classification number: F17C13/025 ,  G01M3/3272 ,  G06V10/82 ,  F17C2260/038

Abstract: The present disclosure provides a method and system for diagnosing a leakage in a hydrogen system for a vehicle, an electronic device, and a storage medium. The method includes: obtaining data of a hydrogen cylinder gas pressure of a fuel cell vehicle; separately performing Gramian angular field transformation and Markov transition field transformation on the pressure data, to obtain static and dynamic feature information; performing, by a static feature LeNet neural network, recognition based on the static feature information, to obtain a probability output of the static feature LeNet neural network; performing, by a dynamic feature LeNet neural network, recognition based on the dynamic feature information, to obtain a probability output of the dynamic feature LeNet neural network; and performing fusion through a Dempster-Shafer (D-S) evidence theory based on the probability output of the static and dynamic feature LeNet neural network, to obtain an excellent hydrogen leakage diagnosis result.

公开(公告)号：US11897344B2

公开(公告)日：2024-02-13

申请号：US18212143

申请日：2023-06-20

Applicant: BEIJING INSTITUTE OF TECHNOLOGY

Inventor： Jianwei Li ,  Zhonghao Tian ,  Xinming Wan ,  Hongwen He ,  Fengchun Sun ,  Wenjun Guo ,  Zhanxin Mao

IPC: F02C9/46 ,  B60L3/04

CPC classification number: B60L3/04

Abstract: The present disclosure relates to a risk early warning method and system for hydrogen leakage, and relates to the field of hydrogen leakage. The method includes: obtaining ventilation information of a hydrogen-related area; carrying out grid division on a pipeline system of the hydrogen-related area to obtain a gridded pipeline system; determining a risk coefficient corresponding to each grid of the gridded pipeline system according to leakage sources of the pipeline system; determining a high-risk region by means of a jet cone model according to the risk coefficients; determining a medium-risk region, a low-risk region and a safe region according to the risk coefficients and the ventilation information; and carrying out risk early warning according to the high-risk region, the medium-risk region, the low-risk region and the safe region.