To conform the design requirements of automotive ignition coils,a multi-input multi-output(MIMO) model is proposed to estimate the technological parameters,such as coils windings,wire diameters and iron core lengths.For small sample size properties,support vector regression (SVR) is utilized to establish the model of ignition coils,and it is verified to be more effective than artificial neural networks (ANN) in this paper.The experimental data are obtained from the typical samples of ignition coils which are specially manufactured and measured.Appropriate SVR parameters and kernel functions are determined to improve the accuracy of the model by experiments.Furthermore,an improved decomposing training algorithm is designed to increase the automation degree of sample choosing and global accuracy of the model.Simulation results verify the rationality and accuracy of the model,which shows that the proposed model can provide guidance for the design of ignition coils,and analyze the relationship between technological parameter with spark time,spark current and ignition energy.
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