Design car side impact using machine learning

Mohammad AlShabi; Khaled Obaideen; Ali Bou Nassif; Maamar Bettayeb

doi:10.1117/12.2664467

14 June 2023 Design car side impact using machine learning

Mohammad AlShabi, Khaled Obaideen, Ali Bou Nassif, Maamar Bettayeb

Proceedings Volume 12549, Unmanned Systems Technology XXV; 125490G (2023) https://doi.org/10.1117/12.2664467
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

In this paper, the design of vehicle door weight is minimized using a newly developed machine learning algorithm that is referred to as Grey Wolf optimizer (GWO). GWO is a metaheuristic technique that show good and robust performance in solving optimization applications. It is a nature-inspired algorithm that is based on the hunting grey wolf while hunting and catching the prey. The algorithm is known to have simple, yet efficient, structure. On the other hand, the design of the car’s door during an impact is known to be a multi-objective optimization problem that is based the European Enhanced Vehicle-Safety Committee. The algorithm needs to minimize the door weight will be satisfying several constrains. The design depends on 11 parameters including the B-pillar inner, B-pillar reinforcement, floor side inner, cross members, door beam, door beltline reinforcement, roof rail, materials of B-pillar inner floor side inner barrier height and hitting position. Monte Carlo simulation is used to test the method and its robustness and stability.

Conference Presentation

Citation Download Citation

Mohammad AlShabi, Khaled Obaideen, Ali Bou Nassif, and Maamar Bettayeb "Design car side impact using machine learning", Proc. SPIE 12549, Unmanned Systems Technology XXV, 125490G (14 June 2023); https://doi.org/10.1117/12.2664467

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available