Slime mould algorithm and kriging surrogate model-based approach for enhanced crashworthiness of electric vehicles


YILDIZ B. S.

INTERNATIONAL JOURNAL OF VEHICLE DESIGN, vol.83, no.1, pp.54-68, 2020 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 83 Issue: 1
  • Publication Date: 2020
  • Doi Number: 10.1504/ijvd.2020.114786
  • Title of Journal : INTERNATIONAL JOURNAL OF VEHICLE DESIGN
  • Page Numbers: pp.54-68
  • Keywords: SMA, slime mould algorithm, WCA, water cycle algorithm, SSA, salp swarm algorithm, electric vehicles, energy absorber, optimum design, Docol 1300, advanced high-strength steel, STRUCTURAL DESIGN, ENERGY-ABSORPTION, WATER CYCLE, OPTIMIZATION, ALUMINUM, TUBES, SIMULATION, SEARCH, SYSTEM

Abstract

Especially during the last decade, electric vehicles have been used frequently in most of the countries. With the establishment of charging station infrastructures, fossil fuel vehicles will inevitably be replaced by electric vehicles in the next ten years. For this reason, electric vehicle components need to be developed very quickly. This paper concentrates on designing a new thin-walled energy absorber to be used in designing of electric vehicles. The material of the thin-walled energy absorber developed in this paper is cold-rolled advanced high-strength steel, which is Docol 1300. This research presents the first application of the slime mould algorithm to the optimum design of automobile components in the literature. Function evaluations are carried out using finite element analysis and estimated by using the kriging surrogate model. The results show that both the SMA and Docol 1300 advanced high-strength material provide exceptional features for enhancing crashworthiness in electric vehicle design, simultaneously.