Fast space vector modulation based on a neurocomputing digital signal processor

This paper presents a novel approach to the implementation of the space vector modulation (SVM). The proposed technique takes advantage of a modified Kohonen's competitive layer to calculate the on duration of the adjacent switching state vectors. By using this technique: (a) the hardware and software complexity of the system is reduced; (b) the maximum attainable switching frequency and thus the bandwidth of the control system is increased; and (c) the waveform degradation and parasitic harmonics resulting from inaccurate calculations are avoided. The proposed method is compared to the conventional implementations of SVM techniques in terms of hardware/software requirements, switching frequency, computation time, and harmonic spectra. The method is applied to a DSP controlled 3 kVA unit (voltage source inverter) and experimental results verify the validity of theoretical and simulation results.