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Shifting from analog to digital control

An AC/DC power supply with input power greater than 75 W requires power factor correction (PFC) to:

• Take the universal AC input (90 V to 264 V) and rectify that input to a DC voltage.
• Maintain the output voltage at a constant level (usually 400 V) with a voltage control loop.
• Force the input current to follow the input voltage such that the electronics load appears to be a pure resistor with a current control loop.

Designing an analog-controlled PFC is relatively easy because the voltage and current control loops are already built into the controller, making it almost plug-and-play. The power-supply industry is currently transitioning from analog control to digital control, especially in high-performance power-supply design. In fact, nearly all newly designed power supplies in data centers use digital control.

Compared to analog control, digital-controlled PFC provides lower total harmonic distortion (THD), a better power factor, and higher efficiency, along with integrated housekeeping functions.

Switching from analog control to digital control is not easy; however, you will face new challenges where continuous signals are represented in a discrete format. And unlike an analog controller, the MCU used in digital control is essentially a “blank” chip; you must write firmware to implement the control algorithms.

Writing the correct firmware can be a headache for someone who has never done this before. To help you learn digital control, in this article series, I’ll provide a step-by-step guide on how to design a digital-controlled PFC, using totem-pole bridgeless PFC as a design example to illustrate the advantages of digital control.

A digital-controlled PFC system 

Among all PFC topologies, totem-pole bridgeless PFC provides the best efficiency. Figure 1 shows a typical totem-pole bridgeless PFC structure.

Figure 1 Totem-pole bridgeless PFC where Q1 and Q2 are high-frequency switches and will work as either a PFC boost switch or synchronous switch based on the VAC polarity. Source: Texas Instruments

Q1 and Q2 are high-frequency switches. Based on VAC polarity, Q1 and Q2 work as a PFC boost switch or synchronous switch, alternatively.

At a positive AC cycle (where the AC line is higher than neutral), Q2 is the boost switch, while Q1 works as a synchronous switch. The pulse-width modulation (PWM) signal for Q1 and Q2 are complementary: Q2 is controlled by D (the duty cycle from the control loop), while Q1 is controlled by 1-D. Q4 remains on and Q3 remains off for the whole positive AC half cycle.

At a negative AC cycle (where the AC neutral is higher than line), the functionality of Q1 and Q2 swaps: Q1 becomes the boost switch, while Q2 works as a synchronous switch. The PWM signal for Q1 and Q2 are still complementary, but D now controls Q1 and 1-D controls Q2. Q3 remains on and Q4 remains off for the whole negative AC half cycle.

Figure 2 shows a typical digital-controlled PFC system block diagram with three major function blocks:

• An ADC to sense the VAC voltage, VOUT voltage, and inductor current for conversion into digital signals.
• A firmware-based average current-mode controller.
• A digital PWM generator.

Figure 2 Block diagram of a typical digital-controlled PFC system with three major function blocks. Source: Texas Instruments

I’ll introduce these function blocks one by one.

The ADC

An ADC is the fundamental element for an MCU; it senses an analog input signal and converts it to a digital signal. For a 12-bit ADC with a 3.3-V reference, Equation 1 expresses the ADC result for a given input signal Vin as:

Conversely, based on a given ADC conversion result, Equation 2 expresses the corresponding analog input signal as:

To obtain an accurate measurement, the ADC sampling rate must follow the Nyquist theorem, which states that a continuous analog signal can be perfectly reconstructed from its samples if the signal is sampled at a rate greater than twice its highest frequency component.

This minimum sampling rate, known as the Nyquist rate, prevents aliasing, a phenomenon where higher frequencies appear as lower frequencies after sampling, thus losing information about the original signal. For this reason, the ADC sampling rate is set at a much higher rate (tens of kilohertz) than the AC frequency (50 or 60 Hz).

Input AC voltage sensing

The AC input is high voltage; it cannot connect to the ADC pin directly. You must use a voltage divider, as shown in Figure 3, to reduce the AC input magnitude.

Figure 3 Input voltage sensing that allows you to connect the high AC input voltage to the ADC pin. Source: Texas Instruments

The input signal to the ADC pin should be within the measurement range of the ADC (0 V to 3.3 V). But to obtain a better signal-to-noise ratio, the input signal should be as big as possible. Hence, the voltage divider for VAC should follow Equation 3:

where VAC_MAX is the peak value of the maximum VAC voltage that you want to measure.

Adding a small capacitor (C) with low equivalent series resistance (ESR) in the voltage divider can remove any potential high-frequency noise; however, you should place C as close as possible to the ADC pin.

Two ADCs measure the AC line and neutral voltages; subtracting the two readings using firmware will obtain the VAC signal.

Output voltage sensing

Similarly, resistor dividers will attenuate the output voltage, as shown in Figure 4, then connect to an ADC pin. Again, adding C with low ESR in the voltage divider removes any potential high-frequency noise, with C placed as close as possible to the ADC pin.

Figure 4 Resistor divider for output voltage sensing, where C removes any potential high-frequency noise. Source: Texas Instruments

To fully harness the ADC measurement range, the voltage divider for VOUT should follow Equation 4:

where VOUT_OVP is the output overvoltage protection threshold.

AC current sensing

In a totem-pole bridgeless PFC, the inductor current is bidirectional, requiring a bidirectional current sensor such as a Hall-effect sensor. With a Hall-effect sensor, if the sensed current is a sine wave, then the output of the Hall-effect sensor is a sine wave with a DC offset, as shown in Figure 5.

Figure 5 The bidirectional hall-effect current sensor output is a sine wave with a DC offset when the input is a sine wave. Source: Texas Instruments

The Hall-effect sensor you use may have an output range that is less than what the ADC can measure. Scaling the Hall-effect sensor output to match the ADC measurement range using the circuit shown in Figure 6 will fully harness the ADC measurement range.

Figure 6 Hall-effect sensor output amplifier used to scale the Hall-effect sensor output to match the ADC measurement range. Source: Texas Instruments

Equation 5 expresses the amplification of the Hall-effect sensor output:

Firmware-based average current-mode controller

As I mentioned earlier, because the digital controller MCU is a blank chip, you must write firmware to mimic the PFC control algorithm used in the analog controller. This includes voltage loop implementation, current reference generation, current loop implementation, and system protection. I’ll go over these implementations in Part 2 of this article series.

Digital compensator

In Figure 7, GV and GI are compensators for the voltage loop and current loop. One difference between analog control and digital control is that in analog control, the compensator is usually implemented through an operational amplifier, whereas digital control uses a firmware-based proportional-integral-derivative (PID) compensator.

For PFC, its small-signal model is a first-order system; therefore, a proportional-integral (PI) compensator is enough to obtain good bandwidth and phase margin. Figure 7 shows a typical digital PI controller structure.

Figure 7 A digital PI compensator where r(k) is the reference, y(k) is the feedback signal, and Kp and Ki are gains for the proportional and integral, respectively. Source: Texas Instruments

In Figure 7, r(k) is the reference, y(k) is the feedback signal, and Kp and Ki are gains for the proportional and integral, respectively. The compensator output, u(k), clamps to a specific range. The compensator also contains an anti-windup reset logic that allows the integral path to recover from saturation.

Figure 8 shows a C code implementation example for this digital PI compensator.

Figure 8 C code example for a digital PI compensator. Source: Texas Instruments

For other digital compensators such as PID, nonlinear PID, and first-, second-, and third-order compensators, see reference [1].

S/Z domain conversion

If you have an analog compensator that works well, and you want to use the same compensator in digital-controlled PFC, you can convert it through S/Z domain conversion. Assume that you have a type II compensator, as shown in Equation 6:

Replace s with bilinear transformation (Equation 7):

where Ts is the ADC sampling period.

Then H(s) is converted to H(z), as shown in Equation 8:

Rewrite Equation 8 as Equation 9:

To implement Equation 9 in a digital controller, store two previous control output variables: un-1, un-2, and two previous error histories: en-1, en-2. Then use current error en and Equation 9 to calculate the current control output, un.

Digital PWM generation

A digital controller generates a PWM signal much like an analog controller, with the exception that a clock counter generates the RAMP signal; therefore, the PWM signal has limited resolution. The RAMP counter is configurable as up count, down count, or up-down count.

Figure 9 shows the generated RAMP waveforms corresponding to training-edge modulation, rising-edge modulation, and triangular modulation.

Figure 9 Generated RAMP waveforms corresponding to training-edge modulation, rising-edge modulation, and triangular modulation. Source: Texas Instruments

Programming the PERIOD resistor of the PWM generator will determine the switching frequency. For up-count and down-count mode, Equation 10 calculates the PERIOD register value as:

where fclk is the counter clock frequency and fsw is the desired switching frequency.

For the up-down count mode, Equation 11 calculates the PERIOD register value as:

Figure 10 shows an example of using training-edge modulation to generate two complementary PWM waveforms for totem-pole bridgeless PFC.

Figure 10 Using training-edge modulation to generate two complementary PWM waveforms for totem-pole bridgeless PFC. Source: Texas Instruments

Equation 12 shows that the COMP equals the current loop GI output multiplied by the switching period:

The higher the COMP value, the bigger the D.

To prevent short through between the top switch and the bottom switch, adding a delay on the rising edge of PWMA and the rising edge of PWMB inserts dead time between PWMA and PWMB. This delay is programmable, which means that it’s possible to dynamically adjust the dead time to optimize performance.

Blocks in digital-controlled PFC

Now that you have learned about the blocks used in digital-controlled PFC, it’s time to close the control loop. In the next installment, I’ll discuss how to write firmware to implement an average current-mode controller.

Bosheng Sun is a system engineer and Senior Member Technical Staff at Texas Instruments, focused on developing digitally controlled high-performance AC/DC solutions for server and industry applications. Bosheng received a Master of Science degree from Cleveland State University, Ohio, USA, in 2003 and a Bachelor of Science degree from Tsinghua University in Beijing in 1995, both in electrical engineering. He has published over 30 papers and holds six U.S. patents.

Reference

1. “C2000 Digital Control Library User’s Guide.” TI literature No. SPRUID3, January 2017.

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• Power Tips #116: How to reduce THD of a PFC

The post How to design a digital-controlled PFC, Part 1 appeared first on EDN.

At the SEMICON Europa 2025 event in Munich, Germany (18–21 November), micro/nanotechnology R&D center CEA-Leti of Grenoble, France has launched a three-year, multi-lateral program on micro-LED technology for ultra-fast data transfer, with a particular focus on accelerating artificial intelligence (AI) growth. The lab- to-fab initiative draws on the institute’s expertise in micro-LED process technology. Beginning in January, it aims to engage manufacturers of micro-LEDs, optical fibers, photodiodes and interconnects, as well as chipmakers, system integrators, and hyperscalers...

Sweden-based AlixLabs AB (which was spun off from Lund University in 2019) has closed a €15m (~SEK165m) Series A funding round led by long-term investors Navigare Ventures, Industrifonden, and FORWARD.one, and joined by Sweden-based STOAF as well as Global Brain (an independent Japanese venture capital firm that manages strategic funds and invests in semiconductor startups), further strengthening AlixLabs’ international reach and industry partnerships...

Intelligent power and sensing technology firm onsemi of Scottsdale, AZ, USA says that its board of directors has authorized a new share repurchase program of up to $6bn over the next three years, launching on 1 January 2026 after the previous $3bn authorization expires on 31 December. Under the prior authorization, onsemi has repurchased $2.1bn of its common stock over the last three years, in particular spending about 100% of the company’s free cash flow in 2025 for share repurchase...

Mojo Vision Inc of Cupertino, CA, USA — which is developing and commercializing micro-LED display technology for consumer, enterprise and government applications — has appointed Dr Anthony Yu to its advisory board. The firm is applying its micro-LED technology to the development of high-speed optical interconnects for AI infrastructure. The addition of Yu to the board brings decades of silicon photonics leadership experience to support the firm’s product strategy and go-to-market execution...

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It may seem at times that there is a divide between the optical/photonic domain and the RF one, with the terahertz zone between them as a demarcation. If you need to make a transition between the photonic and RF words, you use electrooptical devices such as LEDs and photodetectors of various types. Now, all or most optical systems are being used to perform functions in the optical band where electric comments can’t fulfill the needs, even pushing electronic approaches out of the picture.

In recent years, this divide has also been bridged by newer, advanced technologies such as integrated photonics where optical functions such as lasers, waveguides, tunable elements, filters, and splitters are fabricated on an optically friendly substrate such as lithium niobate (LiNbO3). There are even on-chip integrated transceivers and interconnects such as the ones being developed by Ayar Labs. The capabilities of some of these single- or stacked-chip electro-optical devices are very impressive.

However, there is another way in which electronics and optics are working together with a synergistic outcome. The optical frequency comb (OFC), also called optical comb, was originally developed about 25 years ago—for which John Hall and Theodor Hänsch received the 2005 Nobel Prize in Physics—to count the cycles from optical atomic clocks and for precision laser-based spectroscopy.

It has since found many other uses, of course, as it offers outstanding phase stability at optical frequencies for tuning or as a local oscillator (LO). Some of the diverse applications include X-ray and attosecond pulse generation, trace gas sensing in the oil and gas industry, tests of fundamental physics with atomic clocks, long-range optical links, calibration of atomic spectrographs, precision time/frequency transfer over fiber and through free space, and precision ranging.

Use of optical components is not limited to the optical-only domain. In the last few years, researchers have devised ways to use the incredible precision of the OFC to generate highly stable RF carriers in the 10-GHz range. Phase jitter in the optical signal is actually reduced as part of the down-conversion process, so the RF local oscillator has better performance than its source comb.

This is not an intuitive down-conversion scheme (Figure 1).

Figure 1 Two semiconductor lasers are injection-locked to chip-based spiral resonators. The optical modes of the spiral resonators are aligned, using temperature control, to the modes of the high-finesse Fabry-Perot (F-P) cavity for Pound–Drever–Hall (PDH) locking (a). A microcomb is generated in a coupled dual-ring resonator and is heterodyned with the two stabilized lasers. The beat notes are mixed to produce an intermediate frequency, fIF, which is phase-locked by feedback to the current supply of the microcomb seed laser (b). A modified uni-traveling carrier (MUTC) photodetector chip is used to convert the microcomb’s optical output to a 20-GHz microwave signal; a MUTC photodetector has response to hundreds of GHz (c). Source: Nature

But this simplified schematic diagram does not reveal the true complexity and sophistication of the approach, which is illustrated in Figure 2.

Figure 2 Two distributed-feedback (DFB) lasers at 1557.3 and 562.5 nm are self-injection-locked (SIL) to Si3N4 spiral resonators, amplified and locked to the same miniature F-P cavity. A 6-nm broad-frequency comb with an approximately 20 GHz repetition rate is generated in a coupled-ring resonator. The microcomb is seeded by an integrated DFB laser, which is self-injection-locked to the coupled-ring microresonator. The frequency comb passes through a notch filter to suppress the central line and is then amplified to 60 mW total optical power. The frequency comb is split to beat with each of the PDH-locked SIL continuous wave references. Two beat notes are amplified, filtered and then mixed to produce fIF, which is phase-locked to a reference frequency. The feedback for microcomb stabilization is provided to the current supply of the microcomb seed laser. Lastly, part of the generated microcomb is detected in an MUTC detector to extract the low-noise 20-GHz RF signal. Source: Nature

At present, this is not implemented as a single-chip device or even as a system with just a few discrete optical components; many of the needed precision functions are only available on individual substrates. A complete high-performance system takes a rack-sized chassis fitting in a single-height bay.

However, there has been significant progress on putting multiple functional locks into single-chip substrate, so it wouldn’t be surprising to see a monolithic (or nearly so) device within a decade or perhaps just a few years.

What sort of performance can such a system deliver? There are lots of numbers and perspectives to consider, and testing these systems—at these levels of performance—to assess their capabilities is as much of a challenge as fabricating them. It’s the metrology dilemma: how do you test a precision device? And how do you validate the testing arrangement itself?

One test result indicates that for a 10-GHz carrier, the phase noise is −102 dBc/Hz at 100 Hz offset and decreases to −141 dBc/Hz at 10 kHz offset. Another characterization compares this performance to that of other available techniques (Figure 3).

Figure 3 The platforms are all scaled to 10-GHz carrier and categorized based on the integration capability of the microcomb generator and the reference laser source, excluding the interconnecting optical/electrical parts. Filled (blank) squares are based on the optical frequency division (OFD) standalone microcomb approach: 22-GHz silica microcomb (i); 5-GHz Si3N4 microcomb (ii); 10.8-GHz Si3N4 microcomb (iii) ; 22-GHz microcomb (iv); MgF2 microcomb (v); 100-GHz Si3N4 microcomb (vi); 22-GHz fiber-stabilized SiO2 microcomb (vii); MgF2 microcomb (viii); 14-GHz MgF2 microcomb pumped by an ultrastable laser (ix); and 14-GHz microcomb-based transfer oscillator (x). Source: Nature

There are many good online resources available that explain in detail the use of optical combs for RF-carrier generation. Among these are “Photonic chip-based low-noise microwave oscillator” (Nature); “Compact and ultrastable photonic microwave oscillator” (Optics Letters via ResearchGate); and “Photonic Microwave Sources Divide Noise and Shift Paradigms” (Photonics Spectra).

In some ways, it seems there’s a “frenemy” relationship between today’s advanced photonics and the conventional world of RF-based signal processing. But as has usually been the case, the best technology will win out, and it will borrow from and collaborate with others. Photonics and electronics each have their unique attributes and bring something to the party, while their integrated pairing will undoubtedly enable functions we can’t fully envision—at least not yet.

Bill Schweber is a degreed senior EE who has written three textbooks, hundreds of technical articles, opinion columns, and product features. Prior to becoming an author and editor, he spent his entire hands-on career on the analog side by working on power supplies, sensors, signal conditioning, and wired and wireless communication links. His work experience includes many years at Analog Devices in applications and marketing.

Related Content

• Is Optical Computing in Our Future?
• Use optical fiber as an isolated current sensor?
• Analog Optical Fiber Forges RF-Link Alternative
• Silicon yields phased-arrays for optics, not just RF
• Attosecond laser pulses drive petahertz optical transistor switching

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STMicroelectronics raises the performance bar for embedded edge AI and industrial applications with the new STM32V8 high-performance microcontrollers (MCUs) for demanding industrial applications such as factory automation, motor control, and robotics. It is the first MCU built on ST’s 18-nm silicon-on-insulator (FD-SOI) process technology with embedded phase-change memory (PCM).

The STM32V8’s phase-change non-volatile memory (PCM) claims the smallest cell size on the market, enabling 4 MB of embedded non-volatile memory (NVM).

(Source: STMicroelectronics)

In addition, the STM32V8 is ST’s fastest STM32 MCU to date, designed for high reliability and harsh environments in embedded and edge AI applications, and can handle complex applications and maintain high energy efficiency. The STM32V8 achieves clock speeds of up to 800 MHz, thanks to the Arm Cortex-M85 core and the 18-nm FD-SOI process with embedded PCM. The FD-SOI technology delivers high energy efficiency and supports a maximum junction temperature of up to 140°C.

The MCU integrates special accelerators, including graphic, crypto/hash, and comes with a large selection of IP, including 1-Gb Ethernet, digital interfaces (FD-CAN, octo/hexa xSPI, I2C, UART/USART, and USB), analog peripherals, and timers. It also features state-of-the-art security with the STM32 Trust framework and the latest cryptographic algorithms and lifecycle management standards. It targets PSA Certified Level 3 and SESIP certification to meet compliance with the upcoming Cyber-Resilience Act (CRA). 

The STM32V8 has been selected for the SpaceX Starlink constellation, using it in a mini laser system that connects the satellites traveling at extremely high speeds in low Earth orbit (LEO), ST said. This is thanks in part to the 18-nm FD-SOI technology that provides a higher level of reliability and robustness.

The STM32V8 supports bare-metal or RTOS-based development. It is supported by ST’s development resources, including STM32Cube software development and turnkey hardware including Discovery kits and Nucleo evaluation boards.

The STM32V8 is in early-stage access for selected customers. Key OEM availability will start in the first quarter of 2026, followed by broader availability.

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Melexis claims the first automotive-grade surface-mount (SMD) far-infrared (FIR) temperature sensor designed for temperature monitoring of critical components in electric vehicle (EV) powertrain applications. These include inverters, motors, and heating, ventilation, and air conditioning (HVAC) systems.

(Source: Melexis)

The MLX90637 offers several advantages over negative temperature coefficient (NTC) thermistors that have traditionally been used in these systems, where speed and accuracy are critical, Melexis said.

These advantages include eliminating the need for manual labor associated with NTC solutions thanks to the SMD packaging, which supports automated PCB assembly and delivers cost savings. In addition, the FIR temperature sensor with non-contact measurement ensures intrinsic galvanic isolation that helps to enhance EV safety by separating high- and low-voltage circuits, while the inherent electromagnetic compatibility (EMC) eliminates typical noise challenges associated with NTC wires, the company said.

Key features include a 50° field of view, 0.02°C resolution, and fast response time, which are suited for applications such as inverter busbar monitoring where temperature must be carefully managed. Sleep current is less than 2.5 μA. and the ambient operating temperature range is -40°C to 125°C.

The MLX90637 also simplifies system integration with a 3.3-V supply, factory calibration (including post calibration), and an I2C interface for communication with a host microcontroller, including a software-definable I2C address via an external pin. The AEC-Q100-qualified sensor is housed in a 3 × 3-mm package.

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GlobalFoundries of Malta, NY (GF, the only US-based pure-play foundry with a global manufacturing footprint, including facilities in the USA, Europe and Singapore) has announced the acquisition of commercial pure-play specialty silicon photonics foundry Advanced Micro Foundry Pte Ltd (AMF) – a spin-off of the Institute of Microelectronics (IME), a research institute of Singapore’s Agency for Science, Technology and Research (A*STAR) – marking what is described as a pivotal step in GF’s strategy to advance innovation in silicon photonics. The acquisition will expand GF’s silicon photonics technology portfolio, production capacity and R&D in Singapore, complementing its existing technology capabilities in the USA and unlocking new market opportunities with a broader set of data-center and communication technologies...

Filtronic plc of Sedgefield and Leeds, UK — which designs and manufactures RF and millimeter-wave (mmWave) transmit & receive components and subsystems — has completed a multi-year project to develop novel plastic QFN packaging for gallium nitride (GaN) devices, marking what is described as a significant milestone for UK sovereign capability in advanced semiconductor technology...

I’ve recently published Design Ideas (DIs) showing circuits for linear PWM programming of standard bucking-type regulators in applications requiring an output span that can swing below the regulator’s sense voltage (Vsense or Vs). For example: “Simple PWM interface can program regulators for Vout < Vsense.”

Wow the engineering world with your unique design: Design Ideas Submission Guide

Objections have been raised, however, that such circuits entail a significant loss of programming analog accuracy because they rely on adding a voltage term typically derived from an available voltage (e.g., logic rail) source. Therefore, they should be avoided.

The argument relies on the fact that such sources generally have accuracy and stability that are significantly worse (e.g., ±5%) than those of regulator internal references (e.g., ±1%).

But is this objection actually true, and if so, how serious is the problem? How much of an accuracy penalty is actually incurred? This DI addresses these questions. 

Figure 1 shows a basic topology for sub-Vs regulator programming with current expressions as follows:

A = DpwmVs/R1
B = (1 – Dpwm)(Vl – Vs)/(R1 + R4)

Where A is the primary programming current and B is the sub-Vs programming current giving an output voltage:

Vout = R2(A + B) + Vs

Figure 1 Basic PWM regulator programming topology.

Inspection of the A and B current expressions shows that when the PWM duty factor (Dpwm) is set to full-scale 100% (Dpwm = 1), then B = 0. This is due to the (1 – Dpwm) term.

Therefore, there can be no error contribution from the logic rail Vl at full-scale.

At other Dpwm values, however, this happy circumstance no longer applies, and B becomes nonzero. Thus, Vl tolerance and noise degrade accuracy, at least to some extent. But, by how much?

The simplest way to address this crucial question is to evaluate it as a plausible example of Figure 1’s general topology. Figure 2 provides some concrete groundwork for that by adding some example values.

Figure 2 Putting some meat on Figure 1’s bare bones, adding example values to work with.

Assuming perfect resistors, nominal R1 currents are then:

A = Dpwm Vs/3300
B = (1 – Dpwm)(Vl – Vs)/123300
Vout = R2(A + B) + Vs = 75000(A + B) + 1.25

Then, making the (highly pessimistic) assumption that reference errors stack up as the sum of absolute values:

 Aerr = Dpwm 1%Vs/3300 = Dpwm 3.8µA
Berr = (1 – Dpwm) (5% 3.3v + 1% 1.25v)/123300 = (1 – Dpwm) 1.44µA
Vout total error = 75000(Dpwm 3.8µA + (1 – Dpwm)1.44µA)) + 1% Vs

The resulting Vout error plots are shown in Figure 3.

Figure 3 Vout error plots where the x-axis is Dpwm and y-axis is Vout error. Black line is Vout = Vs at Dpwm = 0 and red line is Vout = 0 at Dpwm = 0.

Conclusion: Error does increase in the lower range of Vout when the Vout < Vsense feature is incorporated, but any difference completely disappears at the top end. So, the choice turns on the utility of Vout < Vsense.

Stephen Woodward’s relationship with EDN’s DI column goes back quite a long way. Over 100 submissions have been accepted since his first contribution back in 1974.

Related Content

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• Revisited: Three discretes suffice to interface PWM to switching regulators
• PWM nonlinearity that software can’t fix
• Another PWM controls a switching voltage regulator

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Wolfspeed Inc of Durham, NC, USA — which makes silicon carbide (SiC) materials and power semiconductor devices — has launched 1200V SiC six-pack power modules for high-power inverters. By combining its latest Gen 4 SiC MOSFET technology and innovative packaging, the modules are claimed to deliver three times more power cycling capability at operating temperature than competing solutions, and 15% higher inverter current capability in an industry-standard footprint...

The University of Arkansas has opened its Multi-User Silicon Carbide Facility (MUSiC), which is claimed to the only open-access fabrication facility of its kind in the USA...