354
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Numerical investigation on automotive bumper structure improvements for pedestrian protection

, ORCID Icon, ORCID Icon &
Pages 635-653 | Received 23 Nov 2016, Accepted 23 Jan 2017, Published online: 17 Feb 2017
 

ABSTRACT

Vehicle bumper design remains a key automotive engineering design challenge for ensuring pedestrian safety in car accidents. In this study, a three-dimensional finite-element lower legform is simulated and validated using static and dynamic tests according to three main criteria, namely, the upper tibia acceleration, knee shearing displacement and bending angle. Important design parameters such as material, thickness and location of different parts of the front vehicle structure were studied. The lower legform and dynamic impactor were simulated in LS-DYNA according to European commission (EC) regulation No 631/2009. Then, the legform and a Class-B car front bumper were used in collision tests at three different distances from the bumper centre point. Finally, the design was optimised in order to meet all requirements of the EC regulation related to vehicle pedestrian collision tests, and an improved bumper model which guarantees complete pedestrian protection is presented and discussed along with guidelines which can have significant applications in the design of pedestrian-friendly bumper structure components.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 433.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.