Multistage Mass Optimization of a Quadcopter Frame
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Table 2 Design variables
Parameter
Lower bound
Upper bound
Frame height (mm)
45
55
Curvature (mm)
80
150
Shell thickness (mm)
5
8
Optimization method used for this simulation is an adaptive multi-objective
method which is a variant of the popular Non-dominated Sorted Genetic Algorithm
(NSGA). From the results, a set of three combinations is suggested by the optimization tool that is the best. Since the priority is to identify the sample that yields the
least mass, the sample in Table 3 is chosen. The model generated from the selected
combination is as shown in Fig. 4.
The optimized model is validated using finite element analysis with the same
loading and boundary conditions. From the results, it is observed that the maximum
equivalent stress is 0.81 MPa and the maximum deformation is 0.055 mm. Though
the stress and deformations are within the limits, the mass of the model seems to be
high and there is scope for further optimization. Hence, the model is considered for
topology optimization to reduce its mass.
Table 3 Optimum input parameter combination
Frame height (mm)
Curvature (mm)
Shell thickness (mm)
50
140
5
Fig. 4 Design optimized model