Title: Multi-objective optimisation of composite coil spring for vehicle suspensions

Authors: Xiaokai Chen; Chao Li

Addresses: School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China ' School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China

Abstract: This work presents a general form of spring stiffness and strength prediction model and an optimisation method for developing a suspension fibre-reinforced plastic (FRP) coil spring. The prediction model can deal with arbitrary layer sequences instead of the widely used ±45° laminates. Considering the properties of the suspension coil spring, a laminate design was performed to obtain the optimal sequence of ply angles, thereby increasing the efficiency of optimisation process. After establishing a multi-objective optimisation problem to design a suspension composite spring, the Pareto front was obtained by using the genetic algorithm. Subsequently, the prediction model and optimisation results were verified by finite element analysis. The numerical results showed that the prediction model performed well, and the optimisation results showed that the optimisation method could capture an optimal design efficiently. Compared to the steel springs applied in the same suspension, the optimised composite spring could reduce weight by 38.8%.

Keywords: FRP; fibre-reinforced plastic; coil spring; stiffness prediction model; strength prediction model; optimisation design; CLT; classical lamination theory; laminate; multi-objective; finite element analysis.

DOI: 10.1504/IJVD.2023.135827

International Journal of Vehicle Design, 2023 Vol.93 No.4, pp.362 - 380

Accepted: 23 Apr 2022
Published online: 08 Jan 2024 *

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