Abstract
Tight assembly of stator windings with no insulation paper damage is a manufacturing challenge. We evaluate different sets of parts according to the following parameters: magnet wire thickness, stator slot smoothness, length of the straight magnet wire after the slot end, and type and amount of insulation cap at the end of the slot. These parameters have discrete values with small differences between them. The damage criterion is the decrease of the insulation paper breakdown voltage after assembly/disassembly of parts, assembled in a small set of designed experiments. Parameter values, i.e., levels at individual experiments are set by an orthogonal experiment matrix. Repetition of each experiment provides statistical significance. Data analysis shows that the additive model alone is not sufficient due to the high correlation of the parameters’ influences. We extend the model to include interparameter influences, which we model by adding a virtual parameter. The extended additive model generates parameter values that do not degrade the insulation paper breakdown voltage within the manufacturing process. These values are verified by repetitions of the control experiment.
Highlights
The influence of tight assembly parameters on preservation of the insulation paper breakdown voltage is found and their selection for stator manufacturing of an in-wheel electric motor is reached via designed experiments, modeling, simulation, the development of an extended additive model, and experimental verification.The promises and challenges facing in-wheel motors are addressed in [1], [2]
Total sum of squares, which is the sum of squares over all experiments Sum of squares for the parameter P over all levels Sum of squares of the error Insulation paper breakdown voltage
Each of the 16 experiments made by the orthogonal experiment matrix (OEM) in Table 2 results in its own insulation paper breakdown voltage VBi which is equal to our definition of result quality ηi
Summary
Result quality Result quality η of the i-th experiment Result quality η of the experiment with parameter P at level L Result quality η of the experiment with parameter A at level I, B at level J, at level K, and D at level M Additive model error Fisher factor for the parameter P Mean of the result qualities ηi Mean of the result qualities ηPL Parameter contribution to result quality η Probability density function. Total sum of squares, which is the sum of squares over all experiments Sum of squares for the parameter P over all levels Sum of squares of the error Insulation paper breakdown voltage
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