Few factors may contribute to the stability of a linear voltage regulator (LVR). Among them is the value of the capacitor connected to the output terminal of the LVR, with the primary factor being the parasitic element of the capacitor, namely, equivalent series resistance. The LVR operation is based on the closed-loop system mechanism. LVR stability can be analyzed through two types of responses, namely, transient and frequency. This research focuses on the frequency response of the closed-loop system in terms of the phase margin at the unity gain frequency. Frequency response generates a more accurate outcome than transient response.The transient response can be acquired while the system is in the closed-loop condition, whereas frequency response can only be obtained in the open-loop condition. In this study, a noninvasive method is applied to obtain the LVR frequency response while the system is in the closed-loop condition. LTSpice software is utilized to simulate the LVR circuit. The simulation result is used as a reference for the actual hardware circuitry tests. The obtained outcome shows that the phase margin from the circuit simulation is similar to that of the hardware circuitry. Therefore, the noninvasive stability measurement method is valid for analyzing LVR stability by measuring the phase margin even in the closed-loop condition.

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Voltage regulator (VR) stability plays an essential role in ensuring maximum power delivery and long-lasting electronic lifespan. Capacitor with a specific equivalent series resistance (ESR) range is typically connected at the VR output terminal to compensate for instability of the VR due to sudden changes in load current. The stability of VR can be measured by analyzing output voltage during load transient tests. However, the optimum ESR range obtained from the ESR tunnel graph in its datasheet can only be characterized by testing a set of data points consisting of ESR and load currents. Characterization process is performed manually by changing the value of ESR and load current for each operating point. However, the inefficient process of estimating the critical value of ESR must be improved given that it requires a large amount of time and expertise.Furthermore, the stability analysis is currently conducted on the basis of the number of oscillation counts of VR output voltage signal. Therefore, a model-based virtual sensing approach that mainly focuses on black-box modeling through system identification method and training neural network on the basis of estimated transfer function coefficients is introduced in this study. The proposed approach is used to estimate the internal model of the VR and reduce the number of data points that need to be acquired. In addition, the VR stability is analyzed using noninvasive stability measurement method, which can measure phase margin from the frequency response of the VR circuit in closed-loop conditions. Results showed that the proposed method reduces the time it takes to produce an ESR tunnel graph by 84% with reasonable accuracy (MSE of 5×10 −6 , RMSE of 2.24×10 −3 , MAE of 1×10 −3 , and R 2 of 0.99). Therefore, efficiency and effectiveness of ESR characterization and stability analysis of the VR circuit is improved.

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