A novel nonparametric system identification (SI) algorithm is described, focusing on PID-based control loops for buck converters with effective series resistance (ESR) in the output filter. Dithering amplification effects on the control path are exploited during the steady-state converter operation. The noise injected is used to stimulate the loop reaction and to identify the output filter configuration. Oversampling-dithering features of third-order δ σ modulators are used to increase the DPWM resolution during the converter nominal operation and, moreover, as the core key to compute the SI algorithm. A modified structure of a noise shaper is used to handle the resolution of the SI algorithm over a range of the desired frequencies during the nonparametric identification. The SI algorithm comprises two steps: The first processing step extracts the resonant frequency, and the second extracts the ESR zero from the power spectrum density computation of the control feedback error. The SI method has been validated with different buck converter configurations, and has successfully been integrated and measured into a digitally controlled buck converters prototype for automotive safety application.

A δ∑ Dithering-Amplification-Based Identification Technique for Online SMPS

CONGIU, ANDREA;BARBARO, MASSIMO
2016

Abstract

A novel nonparametric system identification (SI) algorithm is described, focusing on PID-based control loops for buck converters with effective series resistance (ESR) in the output filter. Dithering amplification effects on the control path are exploited during the steady-state converter operation. The noise injected is used to stimulate the loop reaction and to identify the output filter configuration. Oversampling-dithering features of third-order δ σ modulators are used to increase the DPWM resolution during the converter nominal operation and, moreover, as the core key to compute the SI algorithm. A modified structure of a noise shaper is used to handle the resolution of the SI algorithm over a range of the desired frequencies during the nonparametric identification. The SI algorithm comprises two steps: The first processing step extracts the resonant frequency, and the second extracts the ESR zero from the power spectrum density computation of the control feedback error. The SI method has been validated with different buck converter configurations, and has successfully been integrated and measured into a digitally controlled buck converters prototype for automotive safety application.
autoregulation; DC-DC; Digital control; nonparametric; online regulator; self-Tuning; SMPS; system identification; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/169047
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