Multi-objective optimisation of vehicle bodies made of FRP sandwich structures

Abstract

An optimisation methodology is developed and applied on a FRP sandwich body of an electric vehicle -ZBee, where single-objective and multi-objective optimisation studies are performed stepwise using a commercially available software package. The single-objective optimisation allows the identification of the load paths within the composite body, according to the loading conditions previously defined. Within the multi-objective optimisation, the optimum thickness and distribution for each of the layers that form the composite body are searched within the design space so as to obtain the best performance with respect to weight, material cost, global and local stiffness. Strength requirements are also considered as constraints within the optimisation. A conflict situation appears when several objectives are considered within the optimisation, meaning that an increased performance in one objective may often lead to a decreased performance for the others. Therefore, a trade-off between objectives is needed. The interpretation of results is partially made by using trade-off plots, the so-called Pareto frontiers. A method for the overall selection of the most beneficial solutions is proposed and applied in order to choose between the best obtained solutions according to the importance of the objectives.

Multiobjective design of viscoelastic laminated composite sandwich panels

“…If the value is between 1 and 2, the material is aluminium and this interval is discretized in 33 equal subintervals, from which we chose the corresponding aluminium thickness from Table 1. The same is applicable for the intervals [2,3] (GFRP) and [3,4] (CFRP). In this last case, the number of subintervals is 5 and the thickness of the ply is obtained by multiplying the subinterval number by 0.12 mm for GFRP and 0.17 mm for CFRP.…”

“…Multiobjective optimization of structural sandwich panels has also been conducted recently by Velea et al [3], where a multiobjective optimization genetic algorithm is used to improve the performance of an electric vehicle made of sandwich materials. The objective functions are mass, material cost, torsion and bending stiffnesses, displacements and Tsai-Hill failure index, while the design variables are the thickness of the composite material layers of the sandwich.…”

Design Optimization Approach of a Large-Scale Moving Framework for a Large 5-Axis Machining Center

“…In general, conflict occurs when several objectives are considered within the optimization, meaning that an increased performance in one objective may lead to decreased performance in others [30]. Therefore, there is a trade-off between objectives.…”

“…The design variables were n, t s and c. Table 3 lists the above materials' properties used within the optimization studies. Note: Data were taken from the literature [30,31], and costs were converted from SEK to USD.…”

A multi-scale approach for the optimum design of sandwich plates with honeycomb core. Part II: the optimisation strategy

“…Therefore, engineers always use some simplifying assumptions or rules to obtain, in an easier and faster way, a solution. For example, in [3,10,30] the optimal design of a sandwich plate is addressed determining exclusively the optimum thickness of both the core and the skins, keeping constant the rest of geometric and material parameters of the system.…”