The passive devices in state-of-the-art miniaturized switched-mode DC-DC converters are generally integrated by means of on-chip and in-package methods. Nevertheless, the quality is poor-to-moderate, thereby compromising the power-efficiency. In this paper, we propose the miniaturization of the DC-DC converter by means of realizing its passive devices as embedded devices that are printed within a high-density 3D inkjet printed-circuit-board (PCB). We propose a fourth-order stacked LC filter embodying passive components with small values-effectively at no additional cost because they are embedded through 3D-printing. For the inductor and capacitor, we propose to adopt a high-$Q$solenoidal structure and the metal-insulator-metal planar structure, respectively. The proposed filter is printed within the 3D-PCB with a compact 124 mm3volume due to the stacked arrangement. The measured AC attenuation is 21.2 dB at 200 MHz. The filter is further verified by means of computer simulations of a DC-DC buck converter. Simulation results of the converter employing the filter show a low output voltage ripple at 146 mV and a high peak power-efficiency of ~78% at 200 MHz switching frequency with 150 mA load current.

This paper presents a digital current sensor for digitally-controlled current-ripple-based DC-DC buck converters to estimate the instantaneous inductor-current ripple accurately in both the Discontinuous (DCM) and Continuous (CCM) Current Modes. The current sensor employs a proposed dual-mode input multiplexing technique to select an appropriate representation of the pertinent voltage of the switching node$(\boldsymbol{V}_{\boldsymbol{x}})$in any mode, thereby allowing the current to be estimated more accurately compared to that of the prior-art design. The accurate inductor-current ripple information enables the controller to yield output-voltage transient response with small overshoot or undershoot (OS/US) and fast settling time. Benchmarking results using a digitally-controlled current-ripple constant on-time DC-DC buck converter show that the converter employing the proposed sensor achieves$\geq \mathbf{49}{\%}$smaller OS/US and$\geq \mathbf{45}{\%}$faster settling time at the output voltage in both the DCM and the CCM collectively compared with that of the same converter but with the prior-art sensor.

The average power-efficiency of integrated DC- DC converters for Internet-of-Things is generally compromised over a wide load current range. This is because their efficiency is typically severely compromised at light load currents. We present a novel asymmetrical segmented power-stage configuration to improve the average power-efficiency of integrated converters. We achieve this by configuring different power-stage segments with different sizes of power transistors and their inductors, and a circuit to enable the corresponding segment for high power-efficiencies at different load conditions. Specifically, the circuit enables the segment with small-sized power transistors and a large inductor for light-load operations, and conversely, it enables the segment with large-sized power transistors and a small inductor for heavy-load operations. The integrated converter employing our proposed configuration is designed using a CMOS 180 nm process for 2. 5-3.3V input, 1.2 V output, and 50 MHz switching frequency. Simulation results show the proposed converter achieves a high average power-efficiency at ~73% over a wide load current range of 5-200mA. When benchmarked against the competing contemporary designs, the proposed converter features 5-30% higher average power-efficiency over the wide load current range, and >34% higher power-efficiency at 20 mA light load.

Planar air-core inductors come in a variety of geometrical shapes, including in the form of the conventional spiral geometry and novel complex geometries. In the design phase of a system, the inductance of the employed inductor would need to be ascertained. This is usually ascertained by tedious mathematical derivations on a segment-by-segment (inductor) basis or time-consuming computer modeling, and the complexity can become intractable for complex geometries. In this paper, we propose a versatile, yet accurate, vector-based method to ascertain the inductance of planar air-core inductors with virtually any geometry, including novel complex geometry inductors—rather easily. Our proposed method decomposes the inductor segments into vectors, and thereafter utilizes geometric models to compute the inductance in a systematic fashion. We benchmark our proposed method against the conventional electromagnetic field solver simulations to estimate the inductances of six planar inductors ranging from a conventional spiral air-core inductor to that embodying different and complex geometries. On the basis of these six inductor examples, we show that our method is highly accurate with a worst-case error of $\sim 5$% compared to that obtained using conventional electromagnetic field solver. Of particular interest, our modeling for novel complex geometry planar inductors is relatively simple.