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IEEE 802.3bt PD Controller

Linear Technology Corp. recently introduced the LT4295IEEE 802.3bt powered device (PD) interface controller for applications that require up to 71 W. The next Power over Ethernet (PoE) standard—IEEE 802.3bt—enables manufacturers to go beyond the 25.5 W allocated by the 2009 IEEE 802.3at standard. The new standard—PoE++ or 4PPoE—increases the power budget to enable new applications and features, while supporting 10GBASE-T and maintaining backward compatibility with older IEEE equipment. The LT4295 is IEEE 802.3bt (Draft 2.0) compliant and supports newly introduced features, including all additional PD classes (5, 6, 7, and 8), additional PD types (Type 3 and Type 4), and five-event classification.Linear-LT4295

The LT4295 is a single-signature 802.3bt PD controller that integrates an isolated switching regulator controller. It is capable of synchronous operation in both high-efficiency forward and no-opto flyback topologies with auxiliary power support. This simplifies front end PD designs by reducing component count and board space, which means the LT4295 can deliver power to PD loads using just one IC. Unlike traditional PD controllers, the LT4295 controls an external MOSFET to reduce overall PD heat dissipation and maximize power efficiency. You can size the MOSFET to your application’s requirements. Standard LT4295-based implementations routinely select 30-mΩ RDS(ON) MOSFETs.

The LT4295’s features and specs:

  • IEEE 802.3af/at/bt (Draft 2.0) Powered Device (PD) with Forward/Flyback Controller
  • External hot swap N-channel MOSFET for lowest power dissipation and highest system efficiency
  • Supports up to 71-W PDs
  • Five-event classification sensing
  • Superior surge protection (100-V absolute maximum)
  • Wide junction temperature range (–40° to 125°C)
  • 94% End-to-end efficiency with LT4321 ideal bridge
  • No-opto flyback operation
  • Auxiliary power support as low as 9 V
  • Available in 28-lead 4 mm × 5 mm QFN package

Source: Linear Technology

Electrical Engineering Crossword (Issue 315)

315 crossword grid answerAcross

  1. SPECTROMETER—Device for measuring wavelengths
  2. KILLSWITCH—Big Red Switch [two words]
  3. RECURSION—When a routine calls itself
  4. BOOLEAN—Two values: true and false
  5. PASCAL—Pa
  6. TERA—1012
  7. FETCH—Load data before execution
  8. HECTO—102
  9. TRIODE—Amp device with three electrodes
  10. DUB—Copy


  1. CYBERNETIC—What’s cyber short for?
  2. VISHING—Phishing via phones
  3. MEMRISTOR—Memory resistor
  4. HANDSHAKE—Signal exchange of that starts or ends a function
  5. TRANSFORMER—Power brick
  6. BALUN—Transformer used to convert balanced/unbalanced signals
  7. EXBIBYTE—1,152,921,504,606,846,976 bytes
  8. QUBIT—Quantum bit
  9. GANGED—Coupled to work together (e.g., potentiometers)
  10. STEP—An increment

Tips for Predicting Product Reliability

British Prime Minister Benjamin Disraeli (1804–1881) once uttered: “There are lies, damned lies, and statistics.” I don’t say statistics lie, but not everything presented to us as a result of statistical analysis is necessarily true. Statistics are instrumental for investigation of many scientific and social subjects, but they’re just a tool. Incorrectly used, their results can be wittingly or unwittingly skewed and potentially used to prove or disprove just about anything.

One use of statistics in engineering is to predict product reliability, a topic I’ve addressed in several of my previous columns. In this article, I’ll investigate it further.


Predicted reliability is a probability of a product functioning without a failure for a given length of time. It is usually presented as a failure rate λ (Greek letter lambda) indicating the probable number of failures per million hours of operation. Its reciprocal Mean Time Between Failures (MTBF) or Mean Time to Failure (MTTF for irreparable products) is often preferred because it is easier to comprehend.

Having determined a product’s reliability, we can establish its criticality, the likely warranty and maintenance costs as well as to plan repair activities with spare parts quantities and their allocation. Figure 1 is the ubiquitous reliability bath tub curve. The subject of our discussion is the period called “Constant Failure Rate.”

Figure 1: Reliability bath tub curve.

Figure 1: Reliability bath tub curve.

Predicted reliability is not a precise number. It is a probability with less than 100% certainty that the product will work for the specified time. Unfortunately, many buyers, program managers, even design engineers do not recognize this and expect the predicted failure rate to be a certainty.

Most engineers aren’t expert statisticians, nor can every design organization afford such specialists on staff. Historical data to perform reliability prediction are rarely adequate in small companies. Luckily, the US military made the reliability prediction easy to calculate by following their Military Handbook: Reliability of Electronic Equipment (MIL-HDBK-217), now in version F (www.sre.org/pubs/Mil-Hdbk-217F.pdf), based on data collected over many years.

The general method for calculating failure rate during the development stages is by parts count which, once all design details are known, is refined by parts’ stress analysis.

With the parts count method, the predicted failure rate is:Novacek 314 EQ1

In this equation, λEQUIP is the total equipment failures per million hours. λg is the generic failure rate for ith generic part. πQ is the quality factor for ith generic part. Ni quantity of ith generic part. n is the number of different generic part categories in the equipment. Using a spreadsheet, for example, you follow the Military Handbook by calculating failure rates for individual components.

A typical component failure rate model is:Novacek 314 EQ2

In this equation, λp is the part’s failure rate. λb is the part’s base failure rate. p are factors modifying the base rate for stress, application, environment, and so on.

The Military Handbook provides tables with statistical data for components’ base failure rate and all the pertinent p factors. It is one of several methods for calculating predicted reliability. I was interested to see how some different statistical methods compare with each other. For my inquiry I selected an Arduino Uno, which many readers are familiar with (see Photo 1). Not having the Arduino’s design details, I estimated operating conditions. Because I used the same estimates for all the calculations, the relative comparison of the results is valid, while the absolute value may be somewhat off.

Photo 1: Arduino Uno

Photo 1: Arduino Uno

I have a number of Arduino boards, Duemilanove and Uno, which are quite similar, and through the years have collectively clocked over 600,000 hours of continuous operation without a single failure (including all their peripheral circuits which are not, however, included in my calculations). Several of my Arduinos have worked in the garage with the recorded ambient temperature ranging from –32°C (–25.6°F) to 39°C (102.2°F), which falls under the military category “ground fixed” (GF) environment. I used this for my calculations. While components’ failure rates generally increase exponentially with temperature, operation below about 50°C (122°F) does not significantly increase the stress over a room temperature, so there would not be a significant difference in failure rate between those Arduinos working in the garage and those inside the house.


I performed two manual calculations according to MIL-HDBK-217F and one per HDBK 217 Plus using Mathcad. The failure rate of Item 1 in Table 1 was calculated per MIL-HDBK-217F for commercial parts. The MIL handbook has been criticized for two shortcomings. First, for the unrealistic penalty on commercial parts by today’s quality standards as compared to the military-screened parts. This is understandable in view of the second shortcoming: that the handbook has not been updated since 1995. At that time, component manufacturers discontinued screening their parts for military compliance, but simultaneously and up to the present, have been improving quality of manufacturing processes, thus increasing components’ reliability. Based on experience, I modified the components’ quality factors and the result is shown by Item 2.

Table 1: Calculated reliability of Arduino Uno

Table 1: Calculated reliability of Arduino Uno

There are a number of commercially available programs to aid in reliability prediction calculations. You only need to input the bill of material (BOM) with the components’ operating specifics, such as the temperature, derating, and so forth. The programs have built-in databases and do the calculations for you. Those programs are powerful, and in addition to the predicted failure rate, they can generate analyses such as Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and others. Sadly, they are not inexpensive.

As there are different methodologies for calculating the predicted failure rate, these programs allow you to select which methodology you want to use. I performed 10 calculations for the same Arduino BOM and operating conditions by three computer programs per MIL-HDBK-217F, HDBK 217 Plus, Bellcore, Telcordia, Siemens, PRISM (which I believe is based on HDBK 217 Plus), and FIDES 2009 methodologies.

The results fall into two fairly consistent groups, roughly an order of magnitude (discounting Item 1) apart. Table 1 lists the calculated results and Figure 2 its graphic representation. Figure 2 displays the MTBF rather than the failure rate, which is easier to visualize.

Figure 2: Results tabulated in Table 1 shown graphically output.

Figure 2: Results tabulated in Table 1 shown graphically output.

As I already said, I discounted Item 1 which only demonstrates the MIL-HDBK-217F obsolete bias towards commercial parts. Items 3 and 4 show that the MIL-HDBK-217F implementation by commercial programs and my own adjustment, Item 2, are reasonably close. So are items 8, 10, and 13. These methodologies are geared towards tough military/aerospace applications and, therefore, I suspect, their statistical treatment is more conservative than that of Items 5, 6, 7, 11, and 12, which show the predicted MTBF up to more than a decade greater.

We should remind ourselves what those MTBF numbers mean. One hundred thousand hours MTBF represent 11.5 years of continuous operation! That’s a long time. It would be 23 years if operated only 12 hours daily. Many products become obsolete or fall apart before then. Consequently, I am rather skeptical about the predicted 578 years MTBF of Item #11.

Bellcore methodology was developed for telephone equipment, FIDES 2009 is the result of the efforts of the European aerospace manufacturers and the results are close to MIL-HDBK-217F. HDBK 217 Plus, Telcordia, Siemens and PRISM provided results by an order of magnitude greater.

It is important to strive for a realistic predicted failure rate because other analyses, not to mention design and manufacturing costs, warranty and spare parts allocation are affected by it. Later refinements of the calculated prediction by stress analyses, reliability testing and especially field experience should bring us close to the real value.


Which methodology should you use? My customers have always required MIL-HDBK-217, so I never had the headache of having to make and then justify my own choice. Despite its age, MIL-HDBK-217 continues to be alive and well to this day in the aerospace and military industries. In comparison with the results of Items 5, 6, 7, 9, 11, 12 MIL-HDBK-217 seems rather conservative, but when it comes to safety critical designs I much rather err on the safe side. My experience with the Arduinos doesn’t provide sufficient data to draw a general conclusion, although it appears to be better than the MIL-HDBK-217 predicts.

Ultimately, the field results will be the only thing that counts. All the calculations will be meaningless if the product’s reliability in field is not as required by the customer’s specification. Then you will be called upon to fix the design or the manufacturing process or both.

Reliability calculations differ from methodology to methodology, but if you are consistent using the same methodology, those numbers, coupled with experience, will enable you to judge what the field results will be. All my MTBF calculations met the specifications, but the field results have always exceeded those calculations. And that’s what really counts in the end.

George Novacek is a professional engineer with a degree in Cybernetics and Closed-Loop Control. Now retired, he was most recently president of a multinational manufacturer for embedded control systems for aerospace applications. George wrote 26 feature articles for Circuit Cellar between 1999 and 2004. Contact him at gnovacek@nexicom.net with “Circuit Cellar” in the subject line.

Scribbler 3 (S3) Hackable Robots

Parallax’s Scribbler 3 (S3) is a fully-assembled, preprogrammed, reprogrammable, and hackable robot that’s well suited for students and electronics enthusiasts. You can program the S3 in Parallax’s Graphical User Interface (GUI) software or its BlocklyProp tool. The visual programming support in Google’s Blockly makes learning to program easier than ever.

The S3’s improvements over its predecessor include:

  • Rechargeable lithium ion battery pack
  • Exposed Hacker Port with access to I/O and high-current power connections
  • XBee socket inside for RF networking and future wireless programming
  • Line sensor improvement: easy to follow lines of all types with Blockly
  • Up to 25% faster

The Scribbler 3 robot costs $179.

Source: Parallax

800-V CoolMOS P7 Series for Low-Power SMPS Applications

Infineon Technologies recently introduced its 800-V CoolMOS P7 series. Based on the superjunction technology, the product family is well suited for low-power SMPS applications, such a s LED lighting, audio, industrial, and auxiliary power.Infineon_CoolMOS

The 800 V CoolMOS P7’s offers up to 0.6% efficiency gain. In addition, an integrated Zener diode reduces ESD-related production yield losses. The easy to drive and design-in MOSFET features an industry leading V (GS)th of 3 V and the smallest V GS(th) variation of only ±0.5 V.

The 800-V CoolMOS P7 MOSFET family will be available in twelve R DS(on) classes and in six packages. You can order products with R DS(on) of 280 mΩ, 450, 1,400, and 4,500 mΩ.

Source: Infineon Technologies

10-Bit HDO9000 High Definition Oscilloscopes

Teledyne LeCroy recently launched the HDO9000, which uses HD1024 high-definition technology that automatically optimizes vertical resolution under each measurement condition to deliver 10 bits of vertical resolution. Featuring a bright 15.4” capacitive touch screen, the HDO9000 oscilloscopes offer 10-bit resolution, bandwidths of 1 to 4 GHz, and sample rates of 40 GS/s. The HDO9000 and MAUI with OneTouch enables you to perform all common operations with one touch of the display.Teledyne hdo9000

The HDO9000’s features, benefits, and specs:

  • HD1024 high-definition technology provides 10 bits of vertical resolution with 4-GHz bandwidth.
  • 15.4” high resolution capacitive touch screen
  • The mixed signal (-MS) models have 16 digital lines for trigger, decode, and measurements for analyzing timing irregularities or for general-purpose debugging.
  • Compatibility with the HDA125 High-speed Digital Analyzer, with 12.5 GS/s digital sampling rate on 18 input channels, and the revolutionary QuickLink probing solution
  • Several optional software packages are available to equip HDO9000 for all validation and debug requirements ranging from automated standards compliance packages to flexible debugging toolkits.
  • The HDO9000 is available in 1, 2, 3, or 4 GHz bandwidths

The HDO9000’s prices range from $21,250 to $37,400. -MS versions of each model are available with 16 digital channel sampling at 1.25 GS/s for an additional $3,000.

Source: Teledyne LeCroy teledynelecroy.com

Dialog Semiconductor Enters Gallium Nitride (GaN) Market

Dialog Semiconductor recently announced the upcoming availability of the DA8801, which is its first gallium nitride (GaN) power IC device, using Taiwan Semiconductor Manufacturing Corporation’s (TSMC) 650-V GaN-on-Silicon process technology. The DA8801 should initially find traction in the the fast-charging smartphone and computing adapter segment.

Along with Dialog’s digital Rapid Charge power conversion controllers, the DA8801 will enable more efficient, smaller, and higher power density adapters compared to FET-based options. The DA8801’s half-bridge integrates building blocks (e.g., gate drives and level shifting circuits) with 650-V power switches. Allows an up to 50% size reduction in power electronics

The DA8801 will be available in sample quantities in Q4 2016.

Source: Dialog Semiconductor

Electrical Engineering Crossword (Issue 314)

314 crosswordAcross

  1. CBAR—0.01 bar
  2. ATTO—0.000000000000000001
  3. KRYPTON—Atomic number 36; Kr
  4. ZENER—Solid-state diode for regulating power supply voltage
  5. TRIANGLE—Area = (b × h)/2
  6. DIRECT—Direct Unidirectional current
  7. TRAPEZOID—Area = (b1 + b2) × h/2
  8. COLUMN—Vertical array
  9. TERA—10 to the 12th
  10. KALMANFILTERING—Linear quadratic estimation [2 words]


  1. GAUSSIAN—Normal distribution
  2. POWER—A type of transformer that feeds a power supply by drawing energy from an AC line
  3. NIBBLE—4 bits
  4. TELECINE—Converts film images into video signals
  5. HERTZ—Current name for cycles per second (cps)
  6. PASCAL—What did Niklaus Wirth design?
  8. COULOMB—F = k[(q1 × q2)/r2]
  9. CANDELA—Luminous intensity
  10. RAIL—Portion of a power supply that has the highest voltage and/or current delivery capability.

Electrical Engineering Crossword (Issue 313)

313 crosswordAcross

  1. POPULATE—Install, place, solder
  2. WORM—Write once, read many
  3. NIBBLE—4 bits
  4. NORDSIECK—Differential analyzer, 1950
  5. POSITIVE—P-type
  6. SUBBASS—Below 60 Hz
  7. COSMICCUBE—Famous parallel computer developed at Caltech in 1981
  8. TRANSIENT—Brief current or voltage variation


  1. CHOKE—An inductor that bocks AC and passes DC
  2. ALNICO—Aluminum-nickel-cobalt compound
  3. FORCE—M × A
  4. BITERROR—Loss of a single bit [two words]
  5. SIEMENS—German inventor (1816-1892); telgraphy; conductance
  6. ADMITTANCE—The inverse of impedance; Y
  7. SHANNON—Information theory; “A Mathematical Theory of Communication”
  8. DIPOLE—Transmitting or receiving device with a bidriectional polar pattern
  9. YAGI—Directional antenna invented in 1926
  10. STABLE—Free from fluctuation or rapid change
  11. UNITY—Gain of 1
  12. PENN—ENIAC 1946

Electrical Engineering Crossword (Issue 312)

312 crosswordAcross

  1. RECTIFIER—Diode that converts AC to DC
  2. EXA—1000sup6
  3. BD—Baud
  4. PORT—Plug, socket
  5. EULER—Wrote Institutionum calculi integralis (circa 1770)
  6. PLESIOCHRONOUS—Close but not completely in sync
  7. PASCAL—Pa
  8. DIN—German Industrial Standards
  9. PHOTOEMISSION—The generation of electrons when lights hits a material


  1. VAPORWARE—Products advertised but unavailable
  2. CYLINDER—Its volume is pi × rsuper2 × h
  3. TRINOMIAL—A three-term polynomial
  4. TRANSISTOR—Shockley, Brattain, and Bardeen
  5. SCHEMATIC—Electronic wiring diagram, complete with component symbols and units
  6. ATTO—1000sup–6
  7. SILICON—Used in solid-state devices
  8. LADDER—Type of passive filter
  9. SINE—Trig function describing phases of rotation
  10. DRIVE—Linkage between a motor and its load
  11. ROM—Nonvolatile data that you can access but not erase

Issue 314: EQ Answers

Answer 1—Intersymbol interference is created by nonlinearities in the phase/frequency response of the RF channel. These irregularities are generally proportional to the carrier frequency — for example, if a channel centered at 1 MHz has a quality factor (Q) of 50, it will have a 3-dB bandwidth of 20 kHz. But a similar channel centered at 100 MHz will have a bandwidth of 2 MHz.

If you need a bandwidth of 20 kHz for your signal, the 100-MHz channel will have a flatter response over any 20 kHz segment than the 1-MHz channel, reducing the phase distortion.

This is just one way of thinking about it. In reality, there are many factors that affect the flatness of any given communication channel — and the analog circuitry used to interface to it. It’s just that in general, it’s easier to keep distortions of this type low if the bandwidth is a smaller fraction of the carrier frequency.

Answer 2—14.31818 MHz is exactly 4× the NTSC color-burst frequency. The value for the latter is 30 × 525 × 455 / 2 / 1.001 = 3.5795454… MHz. This crystal was used in computer display adapters that were used to produce signals that could be displayed on a standard NTSC color TV set.

11.0592 MHz is exactly 96× (i.e., 6 × 16) the standard UART baud rate of 115.2 kbps. It is also conveniently close to the maximum clock rate of many early Intel single-chip microcontrollers (12 MHz). This allowed systems based on them to communicate at standard baud rates without requiring a separate crystal.

6.176 MHz is exactly 4× the data rate of a digital telephony T1 subscriber line, which is 8000 × 193 = 1.544 MHz. This crystal frequency is often used in a VCXO (voltage-controlled crystal oscillator) within a PLL. This allows the terminal equipment to establish a local timebase that is synchronized to the network.

Answer 3—A solar panel has a characteristic curve that resembles that of a diode, except that in the presence of sunlight, the curve is shifted so that the panel can deliver energy to an external load.

Both of the proposed batteries will cause the panel to operate close to its maximum current, with the 1.5-V battery receiving slightly more current than the 9-V battery, and therefore greater charge (current × time).

However, the 9-V battery is getting 6× the voltage at a current that is much greater than 1/6 that of the 1.5-V battery, therefore it is receiving more power (current × voltage) and more energy (power × time).

Answer 4—An MPPT (maximum power point tracking) controller would deliver the full power of the solar panel to either battery, giving each one the same total energy. However, the 1.5-V battery would receive 6× the current and 6× the charge in the process.














Issue 312: EQ Answers

Question 1: What is the probably of a flip-flop with a uniformly-distributed asynchronous input going metastable?

Answer 1: The probably that a flip-flop with a uniformly-distributed asynchronous input will go metastable is a function of how wide its “window of opportunity” (the sum of the setup and hold times) is and the clock period. It is proportional to (and less than, because of manufacturer’s testing margins) the ratio of these two times.

Question 2: How long does it take for a flip-flop in a metastable state to resolve itself?

Answer 2: There is no definite time for a flip-flop to resolve a metastable state. All we can say is that there is some probability that it will remain metastable after a given amount of time has passed. This is usually a rapidly-decaying exponential funciton. The scale factor, or time constant associated with this function is determined by factors such as the internal gain of the flip-flop and the speed of the active devices used in its implementation.

Question 3: Why does putting multiple flip-flops in series reduce the probability of having a metastable output at the output?

Answer 3: When two flip-flops are placed in series, the probability of the second one going metastable is the product of two factors: the probabiliy of the first one going metastable in the first place, and the probability of that metastable state lasting exactly as long as the clock period. Both of these factors are much less than unity, so their product is even lower still.

A third flip-flop is sometimes used, which reduces the chances of metastability to infinitesimal levels.

Question 4: Under what conditions will a metastable condition propagate from one flip-flop to the next?

Answer 4: In order for the second flip-flop in a chain to go metastable, it’s input must be changing in the “window of opportunity” defined by its setup and hold times.

Note that if the first flip-flop has not yet resolved itself by the time the next clock edge comes along, the second one will not generally go metastable. This is because the circuitry of the flip-flop is always designed so that the input threshold voltage differs enough from the metastable output voltage by enough of a margin to guarantee that the second flip-flop will interpret it as a definite high or definite low.

Therefore, the only way that the second flip-flop can go metastable is if the first one’s metastable state had just started to resolve itself at the next clock edge, such that its output was passing through the second one’s input threshold at that moment.

Contributor: David Tweed

Issue 310: EQ Answers

Answer 1: UDP packets are subject to the following problems. Packets may be lost. Packets may experience variable delays. Packets may arrive in a different order from the order they were transmitted.

UDP gives the application the ability to detect and deal with these issues without experiencing the overhead and arbitrarily large delays associated with TCP.

Since UDP packets can get lost or arrive out of order, you include a sequence number in the packet so that the receiving side can detect either of these occurrances.

The packets also experience random delays over some range that is generally bounded. Therefore, you use a FIFO buffer (or “elastic store”) on the receive side to hide the packet arrival “jitter”. You try to keep the amount data in this buffer that corresponds to the average packet delay, plus a safety margin. If this FIFO ever “runs dry”, you might need to set the (re-)starting threshold to a higher value. Packets that arrive extremely late are treated the same as lost packets.

Answer 2: Any difference between the transmit and receive sample clocks means that the average amount of data in the receive-side FIFO will start to trend upward or downward over time. If the FIFO depth is increasing, it is necessary to increase the output audio sample rate slightly to match. Similarly, if it is decreasing, it is necessary to decrease the sample rate. These adjustments will cause the long-term average sample rate of the receiver to match that of the transmitter exactly.

Answer 3: You can effectively do both the multiplication and the division one addition and one subtraction at a time, by keeping track of the milliseconds right inside the ISR, rather than (or in addition to) simply counting the raw ticks:

/* microseconds can be a 16-bit integer */

microseconds += microsecondsPerTick;

while (microseconds >= 1000) {

microseconds -= 1000;


Answer 4: I2C clock “stretching” refers to the mechanism by which a slave device holds SCL low *after* the master has driven it low, in order to prevent it from going high again before the slave is ready to process the next data bit.

If the master is waiting for more data from, say, a host CPU, it simply won’t drive SCL low in the first place — it’ll simply leave SCL high until the next data transfer can start. There’s no reason for the master to hold SCL low for an extended period of time.

The one exception would be during the arbitration phase of a multi-master setup. In that case, some clock stretching will occur as a result of the various masters not being strictly in-phase as they start their transfers.


Build an Accurate Milliohm Meter

A milliohm meter is a handy benchtop tool for measuring small electrical resistance values. In this article, Mark Driedger details how to build a microcontroller-based milliohm meter that accurately measures DC resistance from 10 mΩ to 10 kΩ.

I built an Arduino-based milliohm meter that accurately measures DC resistance from 10 mΩ to 10 kΩ. I used careful design techniques to cancel many error sources rather than resort to costly components. The milliohm meter is useful for tasks such as measuring transformer and inductor winding resistance, ammeter current shunts, and resistance of PCB tracks.

The finished milliohm meter

The finished milliohm meter

Measurement Method

The milliohm meter calculates the value of the resistor under test (Rx) by measuring the voltage across it and the voltage across a series-connected, known reference resistor (Rr) when driven by a test current. The measured resistance is simply: Rx = Vx/Vr × Rr.

A technique called synchronous rectification (also known as a lock-in amplifier) is used to enhance accuracy. The direction of the test current is alternated and measurements of Vx and Vr are made synchronously with the change in direction of the test current. As we will see, this cancels a number of error sources and is easy to implement on the Arduino.

Synchronous rectification can be thought of as narrowband filter at the switching frequency, implemented using a mixer (multiplier) at the switching frequency followed by a low-pass filter at DC (averaging). Normally, the switching frequency would be high enough (say, 1 kHz) to allow AC-coupled, high-gain amplifiers to be used and to move the filter passband well away from induced 60-Hz AC line voltages. In this implementation, the relatively slow ADC conversion speed prevents us from using a high switching frequency. However, we retain many other benefits of synchronous rectification with regard to reducing measurement error and we gain accuracy improvement in other ways.


An Arduino is used to control the synchronous rectification, read voltages Vx and Vr, and then compute and display the test resistor value. The test current is derived by paralleling four I/O pins through current-limiting resistors for each of the source and sink legs.

sad dsg

The circuitry

This increases the test current to roughly 100 mA, which is still well within the 40 mA/pin and 200 mA/chip limits of the Arduino processor, and the 150 mA limit of the Pro Mini’s onboard voltage regulator. The source and sink legs are alternately driven high and low to produce the test current.

sdfg sdgf

A look inside the meter

Measurement of Vx and Vr is made with an Analog Devices ADS1115 ADC, which has two differential inputs, a programmable gain amplifier (PGA) with 16× maximum gain, and 16-bit accuracy in a very small 10 MSOP package. The device costs between $10 and $15 on a small PCB module. Series resistors and film capacitors on the analog inputs provide some overload protection and noise filtering. At the highest gain, the meter resolution is approximately 75 µΩ/bit. Each measurement consists of two cycles of synchronous rectification, with 100 samples per cycle for a total of 200 samples.

An OLED module with an I2C interface is used for the display, although other options can be substituted with corresponding code changes. The meter is powered by a 9-V battery. Battery voltage is read through one of the analog input ports. Measurements are initiated with the push of the test switch to maximize battery life and minimize self-heating errors in the reference resistor. Each measurement takes roughly 2 s. Purchased modules are used for the Arduino, ADS1115 ADC, and the 64 × 128 OLED display, making it very easy to build.


OLED for displaying data


The meter is built using purchased modules and a small piece of protoboard for the shield. The ADC and display modules are available from multiple sources, and you can use any Arduino module of your choosing. (The photos and layout are for the Pro Mini.) Keep the ADC analog input wiring short and away from the processor. Use a four-wire connection to the reference resistor. Solder the drive leads farthest from the body, and the sense leads closer. The display module is mounted on the reverse side of the protoboard. The SDA/SCL I2C connections are brought from the Arduino module to the protoboard with a short cable and connector since they are not on the regular 0.1” grid.

dsf dsf

Protoboard layout

The ADS1115 module includes the pull-ups that are needed on the I2C interface lines (SDA, SCL).  I used a six-pin GX-16-6 connector for the probes. The additional two pins were used to close the battery circuit on the ground side, turning the meter on and off when the probes are connected.

The complete article appears in Circuit Cellar 314 (September 2016).

Mark Driedger has been experimenting with tube audio and electronics for over 35 years. His earned a BSc and MSc in Electrical Engineering in his native Canada. Mark has worked in the telecom industry for the past 28 years in various technical, business, and executive roles. He is currently COO for Procera Networks and lives in Dallas, TX.

ZULU2 Radio Module

RF Solutions recently released its ZULU2 radio module range. Featuring a telemetry module, modem module, and a firmware-free module, the new range’s functionality is on par with its predecessor, with the advantage that no external components are required to provide a complete RF solution. RF Solutions ZULU2The new range includes:

  • ZULU2-M: A highly integrated RF modem and intelligent controller with a simple interface to the host controller. It handles all RF data communications automatically and without any requirement from the user.
  • ZULU2-T: Telemetry module providing a reliable transceiver based remote switch with up to 2km range. Each unit is supplied ready to operate, once paired with another, a remote control system is created.
  • ZULU2: A hardware platform module containing a SiLabs RF Transceiver and Processor allowing the user to programme the device to suit their own requirements. With no firmware supplied by RF Solutions, this would appeal to somebody with a confident programming ability.

The 25 mm × 11 mm smart modules can achieve a range of 2 km. License-free and operating on the 868- or 915-MHz frequency bands, the ZULU-2 range is available in surface-mount and dual-inline options, making it a good option for applications such as remote control, security, and data logging.

Source: RF Solutions