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Design and Voltage Supply of High-Speed Induction - Aaltodoc

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110<br />

<strong>of</strong> this is the use <strong>of</strong> linear <strong>and</strong> cubic spline functions as a replacement for a FEM model as<br />

illustrated in Bianchi <strong>and</strong> Bolognani (1999). One potential use for the solution data would be the<br />

teaching <strong>of</strong> a neural network system.<br />

This combined use <strong>of</strong> discretization <strong>and</strong> solution history is applicable to any algorithm but it is most<br />

efficient when used with stochastic optimization algorithms like GA, fuzzy logic (Bianchi <strong>and</strong><br />

Bolognani, 1996) or simulated annealing. There, the reduction <strong>of</strong> calculation time is likely to be<br />

most significant. The use <strong>of</strong> solution history in surface fitting is also utilized best with stochastic<br />

algorithms, since the fitting requires large amounts <strong>of</strong> data in order to give a good estimation <strong>of</strong> the<br />

real behavior <strong>of</strong> the objective function.<br />

9.2 Optimization <strong>of</strong> a squirrel cage rotor <strong>of</strong> the 60 kW 60000 1 /min motor<br />

A numerical optimization <strong>of</strong> the rotor design was performed for a squirrel cage solid steel rotor. The<br />

16 bar <strong>and</strong> the 26 bar rotors compared in Chapter 5 were already designed <strong>and</strong> manufactured but the<br />

existence <strong>of</strong> better designs was checked. For the squirrel cage rotors seen in Fig. 9.3, the main<br />

variables are the number <strong>of</strong> cage bars <strong>and</strong> the width <strong>and</strong> height <strong>of</strong> a bar. The air gap was also taken<br />

as a free variable. The dimensions <strong>of</strong> stator <strong>and</strong> stator winding were kept constant. The objective<br />

was to minimize the temperature rise in the stator winding as this was considered the limiting factor<br />

for the utilization <strong>of</strong> the motor. The objective function for the temperature rise ∆T was <strong>of</strong> the<br />

following form:<br />

( w p + w p + w p − ) S<br />

∆ T = a<br />

1 + , (9.1)<br />

s<br />

cus<br />

cus<br />

fes<br />

fes<br />

rot<br />

rot<br />

where as is a scaling factor <strong>and</strong> pcus, pfes <strong>and</strong> prot are the normalized power loss for the stator<br />

winding, stator iron <strong>and</strong> rotor, respectively. wcus, wfes <strong>and</strong> wrot are the corresponding weights. The<br />

normalization is done so that the losses <strong>of</strong> the initial 16 bar design yield zero as a value for the<br />

function. S is the penalty function term. The scaling factor <strong>and</strong> weights for the loss components<br />

were derived from the results <strong>of</strong> a sensitivity analysis for a thermal network model made by Saari<br />

(1995). The power loss components were calculated with the finite element model discussed in<br />

Chapter 7.<br />

The rotor design was optimized <strong>and</strong> the comparison was made at the nominal power <strong>of</strong> 60 kW at the<br />

rated speed <strong>of</strong> 60000 1 /min although speeds only up to 50000 1 /min could be tested, as discussed in<br />

Chapter 5. <strong>Design</strong>s were supplied with PAM. The model for the motor included stator end windings<br />

<strong>and</strong> rotor end rings.

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