Integration of Frequency Response Measurement Capabilities in Digital Controllers for DC–DC Converters

Abstract

Recent work has shown the feasibility of integrating nonparametric frequency-domain system identification functionality into digital controllers for switched-mode pulse-width modulated (PWM) dc-dc power converters. The resulting discrete-time frequency response can be used for design, diagnostic, or self-tuning purposes. The success of these applications depends on the fidelity of the identified frequency responses and the degree to which the process is automated, as well as the costs, in terms of gate count, time duration of identification, and effect on output voltage, incurred to obtain these benefits. This paper demonstrates the feasibility of incorporating fully automated frequency response measurement capabilities in digital PWM controllers at relatively low additional cost. In particular, it is shown that relatively accurate and smooth frequency response data can be obtained using a Verilog-coded implementation with low tens of thousands of logic gates and about 10 kB of memory. The identification process can be accomplished in several hundred milliseconds and the output voltage can be kept within specified bounds during the entire process. Experimental results are provided for four different PWM dc-dc converters, including a synchronous buck with two different filter capacitors, a boost operating in continuous conduction mode (CCM), and a boost operating in discontinuous conduction mode (DCM).

Real-Time Parameter Estimation of DC–DC Converters Using a Self-Tuned Kalman Filter

“…As depicted in Fig. 2, both estimation algorithms rapidly identify the transfer function coefficient with fina estimation values very close to the average model in (11). However, the KF estimation convergence to steady state is less than 0.5 ms, while the ERLS estimator takes around 1.5 ms to converge to the fina values.…”

“…14(a). As stated in (11), each element in the matrix Q is tuned accordingly to the contribution of the related parameter vector component in the estimator output (ϕ kθk ). Therefore, the assigned Kalman gain elements for K 1 for a 1 , and K 2 for a 2 , vary with different rates in the correction step.…”

“…In nonparametric identificatio methods, the system frequency response is determined directly, with no prior knowledge of the system model [5], [6]. The proposed strategies include correlation analysis [7], [8], transient response analysis [9], [10], Fourier, and spectral analysis [11], [12]. Typically, nonparametric system identificatio approaches assume steady-state operation and the system identificatio process is carried out, while the control loop is open to inject the excitation signal.…”

Computationally Efficient Self-Tuning Controller for DC–DC Switch Mode Power Converters Based on Partial Update Kalman Filter

“…However, due to the high computational complexity of many existing adaptive algorithms, this kind of control scheme is often not fully implemented in real-time for low-cost low-power SMPCs. Instead, the identification step is demonstrated offline using real-time data, and then the results obtained are used in the digital control design for the SMPC [4,5].…”

“…There are many self-tuning control techniques based on system identification of SMPC have been presented in the literature [4,5,7]. Both parametric and non-parametric identification methods have been utilised in this scheme to show the feasibility of integrating system identification in digital control design.…”