公开(公告)号：US12070994B2

公开(公告)日：2024-08-27

申请号：US17560278

申请日：2021-12-23

Applicant: TSINGHUA UNIVERSITY

Inventor： Qing Zhou ,  Po-Wen Chen ,  Yong Xia

IPC: B60K1/04 ,  B60L50/60 ,  B60L50/64 ,  H01M50/209 ,  H01M50/242

CPC classification number: B60K1/04 ,  B60L50/64 ,  B60L50/66 ,  H01M50/209 ,  H01M50/242 ,  B60K2001/0438

Abstract: A battery pack is provided, including at least one layer of battery cells in a height direction thereof. Each layer of battery cells includes either or both of a plurality of rows and a plurality of columns of battery cells. The battery cells in each row are arranged end-to-end in a length direction of the battery pack. The rows are arranged in a width direction of the battery pack. At least a part of the battery cells in each row are staggered with corresponding battery cells in an immediately adjacent row of battery cells. The battery cells in each column are arranged end-to-end in the width direction of the battery pack. The columns are arranged in the length direction of the battery pack. At least a part of the battery cells in each column are staggered with corresponding battery cells in an immediately adjacent column of battery cells.

公开(公告)号：US12194936B2

公开(公告)日：2025-01-14

申请号：US17705355

申请日：2022-03-27

Applicant: TSINGHUA UNIVERSITY

Inventor： Bing-Bing Nie ,  Wen-Tao Chen ,  Qing-Fan Wang ,  Jiajie Shen ,  Quan Li ,  Shengbo Li ,  Qing Zhou

IPC: B60N2/02 ,  B60N2/01 ,  B60R16/023 ,  B60R16/037 ,  B60R21/0132 ,  B60R21/015 ,  B60R21/16 ,  B60R22/48 ,  B60W30/085 ,  B60W30/095 ,  G06N20/00 ,  B60R21/013

Abstract: Disclosed is a method for predicting collision severity, including: establishing a first learning model, and inputting vehicle data and collision accident scene feature data into the first learning model; obtaining a predicted collision acceleration curve outputted by the first learning model, the predicted collision acceleration curve being established based on a plane rectangular coordinate system; establishing a second learning model, and inputting the predicted collision acceleration curve, the occupant feature data and the restraint system feature data into the second learning model; obtaining a plurality of predicted collision kinematics and dynamics curves of human body parts outputted by the second learning model; generating a collision severity parameter according to the plurality of predicted collision kinematics and dynamics curves of the human body parts, the collision severity parameter being configured to evaluate the collision severity.

公开(公告)号：US11751785B2

公开(公告)日：2023-09-12

申请号：US17006419

申请日：2020-08-28

Applicant: Tsinghua University

Inventor： Bingbing Nie ,  Quan Li ,  Qing Zhou

IPC: G08B23/00 ,  A61B5/18 ,  A61B5/103 ,  A61B5/16 ,  G02B27/01 ,  G06F3/01 ,  G06F3/16 ,  G09B9/05 ,  G09B9/052

CPC classification number: A61B5/18 ,  A61B5/1038 ,  A61B5/165 ,  G02B27/0172 ,  G06F3/015 ,  G06F3/167 ,  G09B9/05 ,  G09B9/052 ,  A61B2503/22

Abstract: The present disclosure relates to a testing method and a testing system for a human stress reaction, and a computer-readable storage medium. The testing method for the human stress reaction includes acquiring position information and visual field information of a testee in a virtual road traffic scene after the virtual road traffic scene is established; guiding the testee into a test zone when the testee is within a test-waiting zone and when a visual field direction of the testee faces the test zone, and simultaneously, starting acquiring stress reaction data of the testee; controlling a virtual reality environment module to create a virtual stress event in the test zone after it is determined that the testee is within the test zone, and applying a stimulation to the testee, such that the testee make a stress reaction.