Optimizing the performance of the zero-burden battery run-down test setup

Two years ago I added a post here to “Watt’s Up?” titled:  “Zero-burden ammeter improves battery run-down and charge management testing of battery-powered devices” (click here to review). In this post I talk about how our N6781A 20V, 3A 20W SMU (and now our N6785A 20V, 8A, 80W as well) can be used in a zero-burden ammeter mode to provide accurate current measurement without introducing any voltage drop. Together with the independent DVM voltage measurement input they can be used to simultaneously log the voltage and current when performing a battery run-down test on a battery powered device. This is a very useful test to perform for gaining valuable insights on evaluating and optimizing battery life. This can also be used to evaluate the charging process as well, when using rechargeable batteries. The key thing is zero-burden current measurement is critical for obtaining accurate results as impedance and corresponding voltage drop when using a current shunt influences test results. For reference the N678xA SMUs are used in either the N6705B DC Power Analyzer mainframe or N6700 series Modular Power System mainframe.

There are a few considerations for getting optimum performance when using the N678xA SMU’s in zero-burden current measurement mode. The primary one is the way the wiring is set up between the DUT, its battery, and the N678xA SMU. In Figure 1 below I rearranged the diagram depicting the setup in my original blog posting to better illustrate the actual physical setup for optimum performance.

Figure 1: Battery run-down setup for optimum performance

Note that this makes things practical from the perspective that the DUT and its battery do not have to be located right at the N678xA SMU.  However it is important that the DUT and battery need to be kept close together in order to minimize wiring length and associated impedance between them. Not only does the wiring contribute resistance, but its inductance can prevent operating the N678xA at a higher bandwidth setting for improved transient voltage response. The reason for this is illustrated in Figure 2.

Figure 2: Load impedance seen across N678xA SMU output for battery run-down setup

The load impedance the N678xA SMU sees across its output is the summation of the series connection of the DUT’s battery input port (primarily capacitive), the battery (series resistance and capacitance), and the jumper wire between the DUT and battery (inductive). The N678xA SMUs have multiple bandwidth compensation modes. They can be operated in their default low bandwidth mode, which provides stable operation for most any load impedance condition. However to get the most optimum voltage transient response it is better to operate N678xA SMUs in one of its higher bandwidth settings. In order to operate in one of the higher bandwidth settings, the N678xA SMUs need to see primarily capacitive loading across its remote sense point for fast and stable operation. This means the jumper wire between the DUT and battery must be kept short to minimize its inductance. Often this is all that is needed. If this is not enough then adding a small capacitor of around 10 microfarads, across the remote sense point, will provide sufficient capacitive loading for fast and stable operation. Additional things that should be done include:

• Place remote sense connections as close to the DUT and battery as practical
• Use twisted pair wiring; one pair for the force leads and a second pair for the remote sense leads, for the connections from the N678xA SMU to the DUT and its battery

By following these best practices you will get the optimum performance from your battery run-down test setup!

When is it best to use a battery or a power supply for testing my battery powered device?

As I do quite a bit of work with mobile battery powered devices I regularly post articles here on our “Watt’s Up?” blog about aspects on testing and optimizing battery life for these devices. As a matter of fact my posting from two weeks ago is about the webcast I will be doing this Thursday, June 18^th: “Optimizing Battery Run and Charge Times of Today’s Mobile Wireless Devices”. That’s just two days away now!

With battery powered devices there are times it makes sense to use the device’s actual battery when performing testing and evaluation work to validate and gain insights on optimizing performance. In particular you will use the battery when performing a battery run-down test, to validate run-time. Providing you have a suitable test setup you can learn quite a few useful things beyond run-time that will give insights on how to better optimize your device’s performance and run-time. I go into a number of details about this in a previous posting of mine: “Zero-burden ammeter improves battery run-down and charge management testing of battery-powered devices”. If you are performing this kind of work you should find this posting useful.

However, there are other times when it makes sense to use a power supply in place of the device’s battery, to power up the device for the purpose of performing additional types of testing and evaluation work for optimizing the device’s performance. One major factor for this is the power supply can be directly set to specific levels which remain fixed for the desired duration. It eliminates the variability and difficulties of trying to do likewise with a battery, if at all possible. In most all instances it is important that the power supply provides the correct characteristics to properly emulate the battery. This includes:

• Full two-quadrant operation for sourcing and sinking current and power
• Programmable series resistance to simulate the battery’s ESR

These characteristics are depicted in the V-I graph in figure 1.

Figure 1: Battery emulator power supply output characteristics

Note that quadrant 1 operation is emulating when the battery is providing power to the device while quadrant 2 is emulating when the battery is being charge by the device.

A colleague here very recently had an article published that goes into a number of excellent reasons why and when it is advantageous to use a power supply in place of trying to use the actual battery, “Simulating a Battery with a Power Supply Reaps Benefits”. I believe you will find this to also be a useful reference.

Webcast this June 18th: Optimizing Battery Run and Charge Times of Today’s Mobile Wireless Devices

One thing for certain: Technological progress does not stand still for a moment and there is no place where this is any truer than for mobile wireless devices! Smart phones, tablets, and phablets have all but totally replaced yesterday’s mobile phones and other personal portable devices. They provide virtually unlimited information, connectivity, assistance, and all kinds of other capabilities anywhere and at any time.

However, as a consequence of all these greater capabilities and time spent being actively used is battery run time limitations. Battery run time is one of top dissatifiers of mobile device users. To help offset this manufacturers are incorporating considerably larger capacity batteries to get users through their day. I touched upon this several weeks ago with my earlier posting “Two New Keysight Source Measure Units (SMUs) for Battery Powered Device and Functional Test”. We developed higher power versions of our N678xA series SMUs in support of testing and development of these higher power mobile devices.

Ironically, a consequence of higher capacity batteries leads to worsening of another top user dissatifier, and that is battery charging time. Again, technological progress does not stand still! New specifications define higher power delivery over USB, which can be used to charge these mobile devices in less time. I also touched upon this just a few weeks ago with my posting “Updates to USB provide higher power and faster charging”. The power available over USB will no longer be the limiting factor on how long it takes to recharge a mobile device.

I have been doing a good amount of investigative work on these fronts which has lead me to put together a webcast “Optimizing Battery Run and Charge Times of Today’s Mobile Wireless Devices”. Here I will go into details about operation of these mobile devices during use and charging, and subsequent testing to validate and optimize their performance.  If you do development work on mobile devices, or even have a high level of curiosity, you may want to attend my webinar on June 18. Additional details about the webcast and registration are available at: “Click here for accessing webcast registration”. I hope you can make it!

Two New Keysight Source Measure Units (SMUs) for Battery Powered Device and Functional Test

Over the past few years here on “Watt’s Up?” I have posted several articles and application pieces on performing battery drain analysis for optimizing run time on mobile wireless devices. The key product we provide for this application space is the N6781A 20V, +/-3A, 20W source measure module for battery drain analysis. A second related product we offer is the N6782A 20V, +/-3A, 20W source measure module for functional test. The N6782A has a few less key features used for battery drain analysis but is otherwise the same as the N6781A. As a result the N6782A is preferred product for testing many of the components used in mobile devices, where the extra battery drain analysis features are not needed. These products are pictured in Figure 1. While at first glance they may appear the same, one thing to note is the N6781A has an extra connector which is independent voltmeter input. This is used for performing a battery run-down test, one of a number of aspects of performing battery drain analysis. Details on these two SMUs can be found on by clicking on: N6781A product page.  N6782A product page,

Figure 1: Keysight N6781A SMU for battery drain analysis and N6782A for functional test

These products have greatly helped customers through their combination of very high performance specialized sourcing and measurement capabilities tailored for addressing the unique test challenges posed by mobile wireless devices and their components. However, things have continued to evolve (don’t they always!). Today’s mobile devices, like smart phones, tablets and phablets, have an amazing amount of capabilities to address all kinds of applications. However, their power consumption has grown considerably as a result. They are now utilizing much larger batteries to support this greater power consumption in order to maintain reasonably acceptable battery run-time. Optimizing battery life continues to be a critical need when developing these products. With their higher power however, there is in turn a greater need for higher power SMUs to power them during test and development. In response we have just added two new higher power SMUs to this family; the N6785A 20V, +/-8A, 80W source measure module for battery drain analysis and the N6785A 20V, +/-8A, 80W source measure module for functional test. These products are pictured in Figure 2. Details on these two new higher power SMUs can be found on by clicking on: N6785A product page.  N6786A product page.

Figure 2: Keysight N6785A SMU for battery drain analysis and N6786A for functional test

A press release went out about these two new SMUs yesterday; Click here to view. With their greater current and power capability, customers developing and producing these advanced mobile wireless devices and their components now have a way to test them to their fullest, not being encumbered by power limitations of lower power SMUs.

This is exciting to me having been working within the industry for quite some time now, helping customers increase battery life by improving how their devices make more efficient use of the battery’s energy. A key part of this has been by using our existing solutions for battery drain analysis to provide critical insights on how their devices are making use of the battery’s energy.  There is a lot of innovation in the industry to make mobile wireless devices operate with even greater efficiency at these higher power and current levels. There is no other choice if they are going to be successful. Likewise, it is great to see continuing to play a key role in this trend in making it a success!

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Techniques for using the Agilent N6781A and N6782A and their seamless measurement ranging when currents exceed 3 amps

In an earlier posting “Zero-burden ammeter improves battery run-down and charge management testing of battery-powered devices” (click here to access) I had talked about how the Agilent N6781A 2-quadrant SMU can alternately be used as a zero-burden ammeter. When placed in the current path as a zero-burden ammeter, due to its extended seamless measurement ranging, it can measure currents from nanoamps, up to +/-3 amps, which is the maximum limit of the N6781A. The N6782A 2-quadrant SMU can also be used as a zero burden ammeter. It is basically the same as the N6781A but with a few less features.

One customer liked everything about the N6782A’s capabilities, but he had a battery-powered device that drew well over 3 amps when it was active. When in standby operation its current drain ranged back and forth between just microamps of sleep current to 6 or greater amps of current during periodic wake ups. The N6782A’s +/- 3 amps of current was not sufficient to meet their needs.

An alternate approach was taken that worked out well for this customer, which was made possible only because of the N6782A’s zero-burden ammeter capability. The set up is shown in Figure 1.

Figure 1: Setup for measuring micro-amps in combination with large active-state currents

The N6752A 50V, 10A, 100W autoranging DC power module provides all the power. The N6782A is set up as a zero-burden ammeter and is connected in series with the N6752A’s output. When current ranges from microamps up to +/- 3 amps the N6782A maintains its zero-burden ammeter operation, holding its output voltage at zero. Once +/- 3 amps is exceeded, the N6782A goes into current limit and the voltage increases across its output, at which point one of the back-to-back clamp diodes turns on, conducting current in excess of 3 amps through it. This all can be observed in the screen image of the 14585A software in Figure 2. The blue trace is the N752A’s output current. The middle yellow trace is the N6781A’s current and the top yellow trace is the N6781A’s voltage.

Figure 2: Current and voltage signals for Figure 1 setup captured with 14585A software

In Figure 2 measurement markers have been placed across a portion of the sleep current and we find from the N6782A’s measurement readback it is just 1.458 microamps average. The reason why this works is because of zero burden operation. Because the N6782A is maintaining zero volts across its output, there is no current flowing through either diode. If this same thing was attempted using a conventional ammeter or current shunt, the voltage would increase and current would flow through a diode, corrupting the measurement.

Now the customer was able to get the microamp sleep current readings from the N6782A and at the same time get the high level wake up current readings from the N6752A!

In a similar fashion another customer wanted to perform battery run down testing. Everything was excellent about using the N6781A in its zero-burden ammeter mode, along with using its independent DVM input for simultaneously logging the battery’s run down voltage in conjunction with the current. The only problem was they wanted to test a higher power device. At device turn-on, it would draw in excess of 3 amps, which is the current limit of the N6781A. Current limit would cause the N6781A to drop out of its zero-burden ammeter operation and in turn the device would shut back down due to low voltage. The solution was simple; add the back-to-back diodes across the N6781A acting as a zero-burden ammeter, as shown in Figure 3.  Any currents in excess of 3 amps would then pass through a diode. Schottky diodes were used so the device would momentarily see just a few tenths of a volt drop in the battery voltage, during the short peak current in excess of 3 amps. Now the customer was able to perform battery run-down testing using the N6781A along with the 14585A software to log all the results!

Figure 3: Agilent N6781A battery run-down test set up, with diode clamps for peak currents above 3A

Zero-burden ammeter improves battery run-down and charge management testing of battery-powered devices

One way of assessing run-time of battery-powered devices is to power them up with a regulated DC source, place the device into its appropriate operating modes, and get the corresponding current drawn by the device for each of the various operating modes. Estimations of battery run-time can then be made for different user types, based on the percentage of time spent in each of these operating modes, and the capacity of the battery in mA-hours. The DC source must be able to maintain a stable, transient free voltage at the DUT. A lot of general purpose power supplies have difficulty with mobile wireless devices that draw fast rising, high peak currents. Providing the regulated DC source meets maintains a stable voltage, it offers some advantages, including:

• Maintains a fixed voltage level over time, removing variability due to changing voltage.
• Using built-in current read-back eliminates voltage drop issues encountered with using a resistive shunt. This is problematic with mobile wireless devices that draw high peak, but low average current.

An alternative to using a regulated DC source to power the battery powered device is instead use the actual battery. Just like with using a DC source, one can make representative current drain measurements over shorter periods for all the various operating modes and then make predictions on run-time. Alternately one can also perform actual battery run-down tests which, when performed correctly, yields quite a few more insights beyond representative current drain measurements, such as:

• Low battery discharge termination details.
• Battery capacity and energy actually delivered.
• Actual run time achieved.
• How well the battery and device work together as a system

An actual battery-run down test is an indispensable part of validation as a final proof of performance.

Just as with evaluating battery run-down, it is also just as important to evaluate battery charging and management. Again, a lot of testing can be done on a device independent of its battery, but there is also a lot of additional value in validating a device’s charge management performance with its actual battery.

When validating a device’s discharging and charging performance with an actual battery, the first test challenge is the current drawn from or sourced to the battery needs to be accurately measured and logged over time, together with the battery’s voltage, for making good capacity and energy measurements. The second test challenge here is you cannot afford to introduce any significant drop in voltage between the device and its battery, as this alters charging and discharging performance of the battery powered device. This can be a real problem when trying to use shunt resistors.

An alternative is to use a zero-burden ammeter. You may ask how an ammeter can be zero-burden. It has to have some resistance in order to produce a measurable value, right? Well, not always. Agilent provides an innovative alternative use of the N6781A 2-quadrant source measure module that enables it to operate as a zero-burden ammeter (in addition to being a DC source). Using the N6781A as a zero-burden ammeter to evaluate battery run-down and battery charging of a battery-powered device is depicted in Figure 1.

Figure 1: N6781A zero-burden ammeter / wattmeter operation

The N6781A is able to operate as a zero-burden ammeter because it is able to actively regulate its output at zero volts independent of the current flowing through it. Because its output is zero volts, when placed in series between the device and its battery, there is no voltage drop. At the same time its precision current measurement system is able to now measure the discharge or charge currents. In addition a separate voltage measurement port allows it to measure the battery voltage, so now you are able to capture the battery’s discharge or charge voltage profile, as well as determine charge in amp-hours and energy in watt-hours, as shown in Figure 2.

Figure 2: Capturing, displaying, and evaluating battery run-down results with 14585A software

A useful reference providing further details on evaluating a device’s battery run-down and charging, and how to configure and use the N6781A as a zero-burden ammeter are available in our application note; “Evaluating Battery Run-Down with the N6781A 2-Quadrant Source Measure Unit and the 14585A Control and Analysis Software” (click here to access).

Power analysis of automobile self-charging emergency tool

I was recently given a “Swiss+Tech BodyGard Survivor 8-in-1 Automobile Self-Charging Emergency Tool”. How’s that for a compact name? This device does have many features, so I imagine the company had some difficulty devising a name for it. It is meant to be carried in your car and kept close enough to the driver to be used in an emergency. It contains a glass breaker, a seatbelt cutter, a flashlight, an emergency flasher and siren, an AM/FM radio, and rechargeable NiCad batteries that charge by using the self-charging hand crank. See Figure 1.

Since this device contains rechargeable batteries and Agilent makes instrumentation that can do battery drain analysis, I figured I would test the device using our equipment. I used an Agilent N6705B DC Power Analyzer loaded with an N6781A 2-Quadrant Source/Measure Unit (SMU) for Battery Drain Analysis. See Figure 2.

The product’s instruction sheet includes information about the batteries (700 mAH) and the expected battery run time when using the various features. With fully charged batteries, the expected battery run time for each of the features listed below is:

• Flashlight: 12 to 16 hours
• Flasher: 10 to 12 hours
• Radio (low volume): 35 to 40 hours
• Flasher/siren: 6 to 9 hours

Given the battery amp-hour rating (700 mAH) and the expected run time in hours, we can calculate the approximate expected average current draw for each of the various features:

• Flashlight: 700 mAH / 14 hours = 50 mA
• Flasher: 700 mAH / 11 hours = 63.6 mA
• Radio: 700 mAH / 37.5 hours = 18.7 mA
• Flasher/siren: 700 mAH / 7.5 hours = 93 mA

Using the N6781A SMU and the built-in front panel features of the N6705B DC Power Analyzer, I was able to analyzer the current drawn from the batteries when using each of the features. Each feature was used by itself with the other features turned off.

The flashlight draws a steady-state current that I read right from the front panel meter as shown in Figure 3: 50 mA. This agrees perfectly with the expected current draw I calculated. For this measurement and all subsequent current measurements, I connected the N6781A in series with the batteries and set it to Current Measure mode where it acts likes a zero-burden shunt. The measured current is negative in my setup because positive current is current flowing into the battery and with the flashlight on, current is flowing out of the battery.

For the flasher, since the current is not constant, I used the N6705B/N6781A built-in data logger feature and captured 30 seconds of data while the device was flashing. I then used the markers to measure the average current. Since the flasher flashes for a very short period of time (low duty cycle), I expected the average current to be low. When using the flasher, the expected battery run time seemed unusually short to me. At 10 to 12 hours, it is shorter than the flashlight or radio run time, which seems odd. In reality, as shown in Figure 4, the flasher drew very little current (5.6 mA), so it appears that the instruction sheet run time for the flasher is too low. With the device flashing, the battery will last much longer than indicated. In fact, the expected battery run time, when flashing, is about 700 mAH / 5.6 mA = 125 hours, 10 times longer than the time shown on the instruction sheet!

With the radio on, tuned to a station, and set to a low but audible volume, I once again used the data logger to capture the current. The markers show an average current of about 10 mA, which is less than the calculated value of 18.7 mA, but within reason. See Figure 5.

Using the flasher and siren, the data logger shows a current draw of 93 mA, in exact agreement with the expected current draw calculated from the numbers on the instruction sheet. See Figure 6.

The last current analysis I did was to capture 30 seconds of data logging when turning the self-charging crank to recharge the batteries. I purposely varied my cranking rate to see what would happen. Figure 7 shows an average of about 350 mA when turning the crank at what I considered to be a typical rate (highest average numbers on the captured data log). To fully charge 700 mAH batteries, it would take about 2 hours at that rate, which is in agreement with the instruction sheet (it says 2 to 3 hours). I don’t know about you, but I don’t want to turn that crank for 2 hours straight! Let’s hope I never have to use the tool for real, but I’m glad I have it just in case!

Validating battery capacity under end-use conditions for battery powered mobile devices

One aspect (of many) I have talked about for optimizing battery life for battery powered mobile devices is assessing the battery’s actual capacity. Not only do you need to assess its capacity under conditions as stated by the manufacturer but also under conditions reflecting actual end use.

Validating the battery under a manufacturer’s stated conditions establish a starting point of what you might be achievable in how much capacity you can obtain from the battery and if it is in line with what the manufacturer states. Sometime it can be less for a variety of reasons. Even subtle differences in stated conditions can lead to fairly substantial differences in capacity. The stated conditions usually provide a “best case” achievable value for capacity. Do not be surprised if your results for the battery’s capacity fall a little short of the best case value provided by the manufacturer. With a little work you may be able to determine what subtle difference caused it, or simply, the best case value given is a bit optimistic.

Validating the battery under end-use conditions helps establish the difference you can expect between the battery’s capacity for rather ideal stated conditions against end-use conditions. Battery powered mobile devices draw current in a pulsed fashion, with high peaks in relation to the overall average current drain. An example of this kind of dynamic current drain is shown in Figure 1. In this case it is the active mode current drain of a GPRS smart mobile phone.

Figure 1: GPRS smart mobile phone dynamic current drain waveform

This usually significantly degrades the battery’s delivered capacity in comparison to the manufacturer’s stated conditions, which are based on a constant DC current discharge. If you do not take the impact of end-use loading conditions on the battery’s capacity into account there is a good chance the mobile device’s run-time will fall quite a bit short of expectations.

The usual way to validate a battery’s capacity under end-use conditions is to actually hook the battery together with its device, connect up logging instrumentation for recording the battery run down voltage and current over time, and then placing the device in a desired operating mode and let it run until the battery is run down. While a battery run-down test like this is useful to do it has a couple of issues when trying to focus explicitly on just the battery:

• It is a test of the combination of the battery together with its host device. The host device also has influence on the test’s outcome and must be taken into account in assessing just the battery under end-use.
• It can often be complex and difficult to set up the device in its desired operating condition, requiring a substantial amount of supporting equipment to recreate its environment for providing a realistic operating condition.
• It can sometimes be difficult to get consistently repeatable results with the actual device.

An alternative to repeatedly using the actual device is to use an electronic load that can draw a dynamic current representative of the actual device the electronic load is being used in place of. In some cases a simple low duty cycle, high crest factor pulsed current waveform can be directly programmed into the electronic load. In cases where the host device’s current drain waveform is a bit more complex it may be useful to have an electronic load that is able to “play back” a digitized waveform file that is a representative portion of the device’s actual current drain, on an ongoing basis to run down the battery. As one example we put features into our 14585A software to simplify this record and playback approach using our N6781A 2-quadrant DC source measure module. This set up is depicted in Figure 2.

Figure 2: Current drain record and playback set up using the 14585 and N6781A

In the first half of this process the N6781A serves as a voltage source to power up the device while digitizing its dynamic current drain waveform. In the second half of this process the captured current drain waveform is inverted and then played back by the N6781A now instead operating as a constant current load connected to a battery to discharge it. A colleague in our office recently completed a video of how to do this record and playback process using a digital camera as an example, capturing the current drain waveform of the process of taking a picture. This could be played back repeatedly to determine how many pictures could be taken with a set of batteries, for example. I know with my digital camera I need to take a spare set of batteries with me as it uses up batteries quite quickly! The video is available to be viewed at the following link:“record and playback video”

Battery-killing cell phone apps? – Part 2

Back on May 25, 2012, I posted about mobile device users avoiding security apps because they think the apps run down their batteries too quickly (read that post here). I also mentioned that a member of the Anti-Malware Testing Standards Organization (AMTSO) is using Agilent’s N6705B DC Power Analyzer to evaluate just how much the security apps affect battery run time and that the results would not be available for a few months. Well, the results are in and guess what? Which security app you choose does not make much difference in your battery run time.

On average, they reported that the effect of using a security app on reducing battery run time is only about 2% which translates into less than 30 minutes of lost battery life per day. And the study went on to explain that the differences in performance of one mobile security product to another were small (they tested 13 products each from a different vendor). I was amused by the author’s comment that they were “not providing a ranking” because it “could get misused by marketing departments”. Indeed!

Here is a link to the report:
http://www.av-comparatives.org/images/docs/avc_mob_201209_en.pdf

The report shows a picture of Agilent’s N6705B DC Power Analyzer as the measuring device. They used this product because “This high-precision instrument can measure battery drain exactly”. A screen shot of Agilent’s 14585A Control and Analysis Software for the DC Power Analyzer was also shown in the report. The software allowed them to evaluate power consumption while performing various mobile phone tasks, such as making phone calls, viewing pictures, browsing websites, watching YouTube (I wonder if they watched any of the DC Power Analyzer videos we have posted!), watching locally stored videos, receiving and sending mails, and opening documents.

If the N6705B DC Power Analyzer and 14585A Control and Analysis Software can evaluate power consumption for all of those things, just think of what it could do for you! Check out Ed’s post from earlier this week for some of those things: http://powersupplyblog.tm.agilent.com/2012/09/optimizing-mobile-device-battery-run.html

Optimizing Mobile Device Battery Run-time Seminars

On many occasions in the past here both I, and my colleague, Gary, have written about measuring, evaluating, and optimizing battery life of mobile wireless battery powered devices. There is no question that, as all kinds of new and innovative capabilities and devices are introduced; battery life continues to become an even greater challenge.

I recently gave a two-part webcast entitled “Optimize Wireless Device Battery Run-time”. In the first part “Innovative Measurements for Greater Insights” a variety of measurement techniques are employed on a number of different wireless devices to illustrate the nature of how these devices operate and draw power from their batteries over time, and in turn how to go about making and analyzing the measurements to improve the device’s battery run-time. Some key points brought out in this first part include:

• Mobile devices operate in short bursts of activities to conserve power. The resulting current drain is pulsed, spanning a wide dynamic range. This can be challenging for a lot of traditional equipment to accurately measure.
• Not only is a high level of dynamic range of measurement needed for amplitude, but it is also needed on the time axis as well, for gaining deeper insights on optimizing a device’s battery run-time.
• Over long periods of time a wireless device’s activity tends to be random in nature. Displaying and analyzing long term current drain in distribution plots can quickly and concisely display and quantify currents relating to specific activities and sub-circuits that would otherwise be difficult to directly observe in a data log.
• The battery’s characteristics influence the current and power drawn by the device. When powering the device by other than its battery, it can be a significant source of error in testing if it does not provide results like that of when using the battery.

Going beyond evaluating and optimizing the way the device makes efficient use of its battery power, the second part, “The Battery, its End Use, and Its Management” brings out the importance of, and how to go about making certain you are getting the most of the limited amount of battery power you have available to you. Some key points for this second part include:

• Validating the battery’s stated capacity is a crucial first step both for being certain you are getting what is expected from the battery and serve as a starting reference point that you can correlate back to the manufacturer’s data.
• Evaluating the battery under actual end-use conditions is important as the dynamic loading a wireless device places on the battery often adversely affects the capacity obtained from the battery.
• Charging, for rechargeable batteries, must be carefully performed under stated conditions in order to be certain of in turn getting the correct amount of capacity back out of the battery. Even very small differences in charging conditions can lead to significant differences in charge delivered during the discharge of the battery.
• The wireless device’s battery management system (or BMS) needs to be validated for proper charging of the battery as well as suitability for addressing the particular performance needs of the device.

In Figure 1 the actual charging regiment was captured on a mobile phone battery being charged by its BMS. There turned out to be a number of notable differences in comparison to when the battery was charged using a standard charging regiment.

Figure 1: Validating BMS charge regiment on a GSM/GPRS mobile phone

If you are interested in learning more about optimizing wireless device battery run-time this two part seminar is now available on-demand at:

Optimize Wireless Device Battery Run-time: Two Part Webcast Series

I think you will enjoy them!

Validating Battery Capacity for End-use Conditions

In my previous posting “Some Basics on Battery Ratings and Their Validation” I discussed the importance of making certain you are getting the most out of your battery as a key task for optimizing the battery run-time of a mobile battery powered device. You do not want to just rely on what is specified for the battery but you really need to validate it. Indeed, when I did, I found a battery’s capacity to be 12% lower than its rated value. That is a lot of unexpected loss of run-time to try to make up for! On further testing and investigation I indeed confirmed it was the battery and not something I did with inadequate charging or discharging.

Once you get a handle on the battery’s stated ratings, based on recommended charging and discharging conditions, you should then validate the capacity you are able to get under the loading conditions your device subjects the battery to. Most modern mobile battery powered devices draw high peak pulsed, low average current from the battery. Batteries subject to pulsed loading deliver less capacity in comparison to being subjected to the comparable loading that is only DC.  The amount of impact depends on the battery’s design and its ability to handle high peak pulsed loading. Furthermore two different batteries with the same ratings can deliver substantially different results in the end-use application. The bottom line is you need to validate the battery under end-use conditions to assess how much impact it has on the battery’s performance.

Creating end-use operating conditions for devices of course depends on the type of device. In some cases it may be fairly simple but in many cases it can be rather complex. A smart mobile phone, for example, requires a set up that can emulate the wireless network it normally operates in and then place it in a representative active operating state under which to run down the battery. The battery’s run down voltage and current in turn needs to be logged until the battery reaches its proper discharge termination point, in order to assess the amount of capacity it delivers under end-use conditions. An example of such a set up is shown in Figure 1.

Figure 1: End-use battery run down test set up for a mobile phone

As you are trying to assess battery capacity under end-use conditions you will likely want to run trials several times and for different batteries, you will want to control conditions as closely as possible so that you can confidently compare results knowing they were done under comparable test conditions. You also need to be careful about (not) relying on the mobile device’s internal battery management system for end-of-life discharge termination as it is a possible source of error. A technique I resorted to was to record a representative portion of the end-use pulsed current drain drawn by the mobile phone which I then “played back” continuously through our N6781A SMU, acting as an electronic load, to discharge the battery. The N6781A had the required fidelity, accuracy, and “playback” hooks to faithfully reproduce loading of the actual device.  Further details on this record and playback approach are documented in a technical overview “Simplify Validating a Battery’s Capacity and Energy for End-Use Loading Conditions”. The results of my validating the battery’s capacity under end-use conditions are shown in Figure 2.

Figure 2: End-use battery capacity validation results

In this case the battery delivered 3% less capacity under end-use pulsed loading in comparison to the results when validated using comparable DC-only loading. Here the battery appears well suited for its end-use application. Many times however, the impact can be much greater. As always, make certain to take appropriate safety precautions when working with batteries and cells.

Some Basics on Battery Ratings and Their Validation

A key aspect of optimizing battery run-time on battery powered mobile devices is measuring and analyzing their current drain to gain greater insight on how the device is making use of its battery power and then how to make better use of it. I went into a bit of detail on this in a previous posting, “Using Current Drain Measurements to Optimize Battery Run-time of Mobile Devices”.

A second aspect of optimizing battery run-time is making certain you are making optimum use of the battery powering the device. This starts with understanding and validating the battery’s stated capacity and energy ratings. Simply assuming the battery meets or exceeds its stated ratings without validating them is bound to leave you coming up shorter than expected on run-time.  It is critical that you validate them per the manufacturer’s recommended conditions. This serves as a starting point of finding out what you can ultimately expect from the battery you intend to use in your device. More than likely constraints imposed by the nature of your device and its operating conditions and requirements will further reduce the amount of capacity you can expect from the battery in actual use.

A battery’s capacity rating is the total amount of charge the battery can deliver. It is product of the current it can deliver over time, stated as ampere-hours (Ah) or miiliampere-hours (mAh). Alternately the charge rating is also stated as coulombs (C), where:

·         1 coulomb (C)= 1 ampere-sec

·         1 ampere-hour (Ah)= 3,600 coulombs

A battery’s energy rating is the total amount of energy the battery can deliver. It is the product of the power it can deliver over time, stated as watt-hours (Wh) or milliwatt-hours (mWh). It is also the product of the battery’s capacity (Ah) and voltage (V). Alternately the energy rating is also stated as joules (J) where:

·         1 joule (J)= 1 watt-second

·         1 watt-hour (Wh) = 3,600 joules

One more fundamental parameter relating to a battery’s capacity and energy ratings is the C rate or charge (or discharge) rate. This is the ratio of the level of current being furnished (or drawn from, when discharging) the battery, to the battery’s capacity, where:

·         C rate (C) = current (A) / (capacity (Ah)

·         C rate (C) = 1 / charge or discharge time

It is interesting to note while “C” is used to designate units of C rate, the units are actually 1/h or h^-1. The type of battery and its design has a large impact on the battery’s C rate. Batteries for power tools have a high C rate capability of 10C or greater, for example, as they need to deliver high levels of power over short periods of time. More often however is that many batteries used in portable wireless mobile devices need to run for considerably longer and they utilize batteries having relatively low C rates. A battery’s capacity is validated with a C rate considerably lower than it is capable of as when the C rate is increased the capacity drops due to losses within the battery itself.

Validating a battery’s capacity and energy ratings requires logging the battery’s voltage and current over an extended period of time, most often with a regulated constant current load. An example of this for a lithium ion cell is shown in Figure 1 below. Capacity was found to be 12% lower than its rating.

Figure 1: Measuring a battery’s capacity and energy

Additional details on this can be found in a technical overview I wrote, titled “Simply Validating a Battery’s Capacity and Energy Ratings”. As always, proper safety precautions always be observed when working with batteries and cells. Validating the battery’s stated capacity and energy ratings is the first step. As the battery is impacted by the device it is powering, it must then be validated under its end-use conditions as well. Stay tuned!

Battery drain analysis of handheld HP 973A multimeter

I have owned a Hewlett-Packard 973A multimeter for longer than I can remember. What has always amazed me about this meter is that I have never had to change the batteries in it! It runs off of 2 AA batteries (in series, of course), and earlier this week, I had to open it up to change a blown fuse for the mA/uA current measurement input (that’s what I get for lending the meter to someone).

While I had it open, I took a look at the AA batteries and was surprised to see a date code of 04-99. That means these batteries have been powering this multimeter for at least 13 years! I admit that I don’t use the meter very frequently, but I am still impressed with how long these batteries lasted. The series combination measured about 2.6 V – still plenty of charge left to power the multimeter (2 new batteries in series measure about 3.2 V).

Since we make power supplies that can perform battery drain analysis, I decided to take a quick look at the current drawn by the multimeter from these batteries. I used an Agilent N6705B mainframe with an N6781A Source/Measure Unit (SMU) installed. This SMU has many features that make it easy to analyze current drain. For example, I set the SMU for Current Measure mode which means it acts like a zero-burden ammeter (an ammeter with no voltage drop across the inputs). I found that the multimeter (set to measure DC V) draws about 3.5 mA from the 2.6 V series combination of AA batteries. I used both the Meter View feature of the SMU and the Data Logger to verify the current. The Data Logger shows the dynamic current being drawn from the batteries and I measured the average current between the markers.

Typical AA batteries are rated for about 2500 mA-hours, so with a 3.5 mA load, they will last more than 700 hours. It is no wonder that the batteries lasted a long time; I use this meter only a few hours per month, so assuming 3 hours per month, the batteries would last about 20 years!

While I had the back cover off, I removed the batteries and powered the multimeter directly from the N6781A SMU. I could then slowly lower the voltage and find when the low battery indicator came on. This happened at about 2.3 V. Continuing to lower the voltage, the LCD display continued to work down to almost 1.0 V. I also noticed that the current drawn by the multimeter increased as the voltage decreased – the multimeter was drawing a nearly constant amount of power from the source – roughly 9 to 10 mW.

I figured while I had the multimeter open, I might as well install new batteries. I doubt I will write another post the next time these batteries need to be replaced in 20 to 30 years, but keep checking here.… you never know!

Battery-killing cell phone apps?

Two days ago, I came across an article entitled “Do Android Security Apps Kill Your Batteries?” The article talks about mobile device users avoiding security apps because they think the apps run down their batteries too quickly. A member of the Anti-Malware Testing Standards Organization (AMTSO) is using Agilent’s N6705B DC Power Analyzer to evaluate just how much the security apps affect battery run time. While the results are not yet complete, the researchers are planning to measure power usage with no security app running, with the app running in the background, and with the app actively working. Their full report is due out by the end of July. Here is a link to the article, written by Neil Rubenking in his SecurityWatch blog for PC Magazine Digital Edition:

http://securitywatch.pcmag.com/mobile-security/298170-do-android-security-apps-kill-your-batteries

I was pleased to see the N6705B DC Power Analyzer used in this way – this product has power modules and software that are specifically designed to do exactly this type of evaluation!

If you have to evaluate a mobile device’s battery run time for any reason, here is a link to “10 Tips to Optimize a Mobile Device’s Battery Life” written by our own Ed Brorein (contributor extraordinaire to this blog):

http://cp.literature.agilent.com/litweb/pdf/5991-0160EN.pdf

And here is a link to Ed’s post from a few months ago on “Using Current Drain Measurements to Optimize Battery Run-time of Mobile Devices”:

http://powersupplyblog.tm.agilent.com/2012/03/using-current-drain-measurements-to.html

When the researchers complete and publish their evaluation on how security apps affect your cell phone battery run time, we’ll be sure to follow-up with another post! In the mean time, protect your phone in whatever way you like, and keep charging ahead by charging your batteries!

Pay Attention to the Impact of the Bypass Capacitor on Leakage Current Value and Test Time

It is no secret there is big demand for all kinds of wireless battery powered devices and, likewise, the components that go into these devices. These devices and their components need to be very efficient in order to get the most operating and standby time out of the limited amount of power they have available from the battery. Off-mode and leakage currents of these devices and components need to be kept to a minimum as an important part of maximizing battery run and standby time. Levels are typically in the range of tens of microamps for devices and just a microamp or less for a component. Off-mode and leakage currents are routinely tested in production to assure they meet specified requirements. The markets for wireless battery powered devices and their components are intensely competitive. Test times need to be kept to a minimum, especially for the components. It turns out the choice of the input power bypass capacitor being used, either within the DUT on the DUT’s test fixture, can have a large impact on the leakage current value and especially the test time for making an accurate leakage current measurement.

Good things come in small packages?
A lot has been done to provide greater capacitance in smaller packages for ceramic and electrolytic capacitors, for use in bypass applications. It is worth noting that electrolytic and ceramic capacitors exhibit appreciable dielectric absorption, or DA. This is a non-linear behavior causing the capacitor to have a large time-dependent charge or discharge factor, when a voltage or short is applied. It is usually modeled as a number of different value series R-C pairs connected in parallel with the main capacitor. This causes the capacitor to take considerable time to reach its final steady state near-zero current when a voltage is applied or changed. When trying to test the true leakage current on a DUT it may be necessary to wait until the current on any bypass capacitors has reached steady state before a current measurement is taken. Depending on the test time and capacitor being used this could result in an unacceptably long wait time.

So how do they compare?
In Figure 1 I captured the time-dependent current response waveform for a 5.1 megohm resistor, a 5.1 megohm resistor in parallel with 100 microfarad electrolytic capacitor, and finally a 5.1 megohm resistor in parallel with 100 microfarad film capacitor, when a 5 volt step stimulus was applied.

Figure 1: Current response of different R-C loads to 5 volt step

The 5.1 megohm resistor (i.e. “no capacitor”) serves as a base line to compare the affect the two different bypass capacitors have on leakage current measurement. The film capacitor has relatively ideal electrical characteristics in comparison to an equivalent electrolytic or ceramic capacitor. It settles down to near steady state conditions within 0.5 to 1 second. At 3 to 3.5 seconds out (marker placement in Figure 1) the film capacitor is contributing a fairly negligible 42 nanoamps of additional leakage. In comparison the electrolytic capacitor current is still four times as great as the resistor current and nowhere near being settled out. If you ever wondered why audio equipment producers insist on high performance film capacitors in critical applications, DA is one of those reasons!

So how long did it take for the electrolytic capacitor to reach steady state? I set up a longer term capture in Figure 2 for the electrolytic capacitor. After about a whopping 40 seconds later it seemed to be fully settled out, but still contributing a substantial 893 nanoamps of additional steady state leakage current.

Figure 2: 100 microfarad electrolytic capacitor settling time

Where do I go from here?
So what should one do when needing to test leakage current? When testing a wireless device be aware of what kind and value of bypass capacitor has been incorporated into it. Most likely it is a ceramic capacitor nowadays. Film capacitors are too large and cost prohibitive here. Find out how long it takes to settle to its steady state value. Also, off-state current measurements are generally left until the end of the testing to not waste time waiting for the capacitor to reach steady state. If testing a component, if a bypass capacitor is being used on the test fixture, consider using a film capacitor. With test times of just seconds and microamp level leakage currents the wrong bypass capacitor can be a huge problem!

Using Current Drain Measurements to Optimize Battery Run-time of Mobile Devices

One power-related application area I do a great deal of work on is current drain measurements and analysis for optimizing the battery run-time of mobile devices. In the past the most of the focus has been primarily mobile phones. Currently 3G, 4G and many other wireless technologies like ZigBee continue to make major inroads, spurring a plethora of new smart phones, wireless appliances, and all kinds of ubiquitous wireless sensors and devices. Regardless of whether the device is overly power-hungry due to running data-intensive applications or power-constrained due to its ubiquitous nature, there is a need to optimize its thirst for power in order to get the most run-time from its battery. The right kind of measurements and analysis on the device’s current drain can yield a lot of insight on the device’s operation and efficiency of its activities that are useful for the designer in optimizing its battery run-time. I recently completed an article that appeared in Test & Measurement World, on-line back in November and then in print in their Dec 2011- Jan 2012 issue. Here is a link to the article:
http://www.tmworld.com/article/520045-Measurements_optimize_battery_run_time.php

A key factor in getting current drain measurements to yield the deeper insights that really help optimize battery run-time is the dynamic range of measurement, both in amplitude and in time, and then having the ability to analyze the details of these measurements. The need for a great dynamic range of measurement stems from the power-savings nature of today’s wireless battery powered devices. For power-savings it is much more efficient for the device to operate in short bursts of activities, getting as much done as possible in the shortest period of time, and then go into a low power idle or sleep state for an extended period of time between these bursts of activities. Of course the challenge for the designer to get his device to quickly wake up, stabilize, do its thing, and then just as quickly go back to sleep again is no small feat! As one example the current drain of a wireless temperature transmitter for its power-savings type of operation is shown in Figure 1.


Figure 1: Wireless temperature transmitter power-savings current drain

The resulting current drain is pulsed. The amplitude scale has been increased to 20 µA/div to show details of the signal’s base. This particular device’s current drain has the following characteristics:
• Period of ~4 seconds
• Duty cycle of 0.17%
• Currents of 21.8 mA peak and 53.7 µA average for a crest factor of ~400
• Sleep current of 7 µA
This extremely wide dynamic range of amplitude is challenging to measure as it spans about 3 ½ decades. Both DC offset error and noise floors of the measurement equipment must be extremely low as to not limit needed accuracy and obscure details.

Likewise being able to examine details of the current drain during the bursts of activities provides insights about the duration and current drain level of specific operations within the burst. From this you can make determinations about efficiencies of the operations and if there is opportunity to further optimize them. As an example, in standby operation a mobile phone receives in short bursts about every 0.25 to 1 seconds to check for incoming pages and drops back into a sleep state in between the receive (RX) bursts. An expanded view of one of the RX current drain bursts is shown in figure 2.


Figure 2: GPRS mobile phone RX burst details

There are a number of activities taking place during the RX burst. Having sufficient measurement bandwidth and sampling time resolution down to 10’s of µsec provides the deeper insight needed for optimizing these activities. The basic time period for the mobile phone standby operation is on the order of a second but it is usually important to look at the current drain signal over an extended period of time due to variance of activities that can occur during each of the RX bursts. Having either a very deep memory, or even better, high speed data logging, provides the dynamic range in time to get 10’s of µsec of resolution over an extended period of time, so that you can determine overall average current drain while also being able to “count the coulombs” it takes for individual, minute operations, and optimize their efficiencies.

Anticipate seeing more here in future posts about mobile wireless battery-powered devices, as it relates to the “DC” end of the spectrum. In the meantime, while you are using your smart phone or tablet and battery life isn’t quite meeting your expectation (or maybe it is!), you should also marvel at how capable and compact your device is and how far it has come along in contrast to what was the state-of-the-art 5 and 10 years ago!