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Abstract

In this paper, the changes of safety belt anchorage, H point, and H point-anchorage angle (α1 and α2) with seat back angle and seat pan angle of the high-angle seat are studied. Firstly, the structure of the high-angle seat was analyzed. The research range of the seat back angle and seat pan angle was determined by the three-dimensional H-point test device. Then, Latin hypercube sampling and back propagation neural networks were combined to study the changing trend of α1 and α2. Finally, the genetic algorithm and back propagation neural network were combined to build a model to identify the minimum H point-anchorage angle. The results show that the α1 and α2 tend to increase with the increase of seat pan angle. The proposed model has a recognition error of 4.3% and can identify the minimum H point-anchorage angle seat position.

Details

1009240
Title
Research on the H point-anchorage angle of high-angle seat based on BPNN-GA
Author
Bi, Tengfei 1 ; Sun, Jiawei 2 ; Sun, Hongjie 2 ; Ma, Qiang 2 

 Tianjin University , Tianjin 300072, China; CATARC Automotive Test Center (Tianjin) Co., Ltd. , Tianjin 300300, China 
 CATARC Automotive Test Center (Tianjin) Co., Ltd. , Tianjin 300300, China 
Publication title
Volume
3043
Issue
1
First page
012105
Publication year
2025
Publication date
Jun 2025
Publisher
IOP Publishing
Place of publication
Bristol
Country of publication
United Kingdom
Publication subject
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
ProQuest document ID
3227051243
Document URL
https://www.proquest.com/scholarly-journals/research-on-h-point-anchorage-angle-high-seat/docview/3227051243/se-2?accountid=208611
Copyright
Published under licence by IOP Publishing Ltd. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-07-04
Database
ProQuest One Academic