Boost Device Runtime With Battery Drain Analysis
Key takeaways:
- Mobile and Internet of Things (IoT) devices work in several modes, and each mode has drastically different current drain characteristics.
- There are source measure units specially designed for battery drain analysis.
- Instruments in this space must be capable of measuring current changes from a few nanoamperes to hundreds of milliamperes within a few microseconds.
In the discussion forum of a major smartphone manufacturer, one of the longest threads, spanning dozens of pages, is full of disappointed customers complaining about high battery drain in their latest models. Such problems may discourage customers from buying their products.
Engineers can avoid such reputational damage by using the sophisticated instruments available for accurate battery drain analysis. In this article, find out how battery drain analysis is done and what instruments are used.
What is battery drain analysis?
Battery drain analysis is the systematic measurement and characterization of battery consumption by IoT devices, consumer devices like phones and wearables, medical devices like pacemakers and hearing aids, and large equipment like electric vehicles.
Its goals are to:
- measure battery consumption in different modes like active, sleep, or battery-saver
- analyze battery usage by various subsystems of devices, like the central processing unit (CPU) cores, Bluetooth, Wi-Fi, baseband, and so on
- study the consequences of external and internal events, such as calls or radio transmissions, on battery usage
- identify the components and circuits with high power consumption
- assess how environmental factors like temperature and humidity affect battery levels
- evaluate the impact of software components on battery performance, especially in mobile devices
- extend battery life by optimizing power usage
How does the operating mode of a device affect its power consumption?
Fig 1. Current drain in different modes
To optimize battery usage, IoT and consumer devices operate in multiple modes and switch between them.
In their active modes, the devices perform their main functions, like interacting with users, measuring something, or processing some data. Some operations like radio transmissions or data processing can result in pulses of high current drain of the order of several hundred milliamperes (mA) or even low amperes (A).
In standby and idle modes, most of the device subsystems go into idle states with reduced power usage. For example, in these low-power modes, phones may enable notifications and run just one or two CPU cores actively while all the rest are throttled down or even sleeping.
In sleep modes, only essential functions run while all subsystems are at their lowest power usage levels. Current draws go as low as a few microamperes (μA) or even nanoampere (nA) ranges.
What are the key factors that contribute to battery drain in devices?
In mobile devices as well as IoT devices, functions that contribute to battery drain include:
- Cellular transmissions: In 4G/5G/6G device radios, the transmission power, number of subcarrier resource blocks, paging wake-ups, and connected-mode discontinuous reception (DRX) settings lead to large current drains. Multiple-input multiple-output (MIMO) capabilities of 4G/5G/6G also draw high currents.
- Satellite transmissions: Satellite navigation radios in IoT and mobile devices can drain a lot of battery charge, especially when the line-of-sight is obscured.
- Software and firmware: Background tasks, wireless communications, and processing algorithms of device software and firmware have a major influence on the current drain.
- Displays: In mobile devices, displays, touch screens, and user interactions are major sources of phone battery drain.
- Environmental factors: Internal and ambient temperatures can lead to increased battery drain.
Additionally, battery drain may be the outcome of suboptimal decisions in the engineering or test process.
Why is battery drain analysis of electronic devices important?
For consumer devices like phones and wearables, battery drain analysis helps with:
- Customer satisfaction: Most users nowadays expect their mobile devices to run for at least 24 hours, if not more, on a single charge. Devices with long runtimes have inherent market advantages over power-hungry ones.
- Real-world simulation: Battery drain analysis enables device manufacturers to understand and predict battery discharge behavior while simulating real-world scenarios using instruments like the E36731A emulator. They can study battery drain under varying signal conditions, usage patterns, and application loads, to accurately predict the battery life under typical end-user conditions.
- Identify inefficiencies: Using battery optimization systems like the X8712A and its event-based battery drain analysis, engineers can identify exactly which subsystems, subcircuits, and components are draining power during research and development as well as quality assurance stages.
- Safety improvement: When lithium-polymer and lithium-ion batteries are overloaded or overheated, they can sometimes turn incendiary, putting lives and property at risk. Battery drain analysis helps discover potential overloading early on.
- Compliance with industry standards: Battery drain analysis is an essential step in compliance with industry standards like the Institute of Electrical and Electronics Engineers (IEEE) 1725standard and 1625 standard for rechargeable batteries as well as the CTIA'sbattery life certification.
For IoT in industrial or consumer applications, battery drain analysis is essential for:
- Reliability in mission-critical applications: In health care and industrial monitoring, IoT devices provide critical data and functionality. Battery failures can lead to operational disruptions, data loss, or even the endangerment of lives. Battery drain analysis ensures that they work reliably over months or even years.
- Reducing maintenance costs: Many industrial IoT devices are installed in remotelocations where regularly sending maintenance crews can be expensive. Long battery life is essential for reducing operational expenses.
What instruments and software are used for battery drain analysis?
In this section, let's understand the test instruments and software typically used for battery drain analysis.
Two-quadrant source measure units (SMUs)
Fig 2. N6781A SMU
The N6781A (with output power up to 20 watts) and the N6785A (with output power up to 80 watts) are sourcemeasure units that are specially designed for battery drain analysis. “Two-quadrant” means they can source and sink power. Their capabilities include:
- Seamless measurement ranging: As devices switch from sleep to active modes, current drains can go from a few nA to hundreds of mA or even a few A, a breathtaking increase of eight to nine orders of magnitude. Incredibly, these two SMUs can precisely measure the current across that entire span by automatically, instantaneously, and seamlessly shifting to the best range without glitches or disruptions. This allows engineers to visualize the complete waveform from nA to A in a single plot.
- Built-in high-speed digitizers: These SMUs can measure and log voltage, current, and power at high sampling rates of about five microseconds, which is critical to accurately capture fast-changing current levels.
- Ammeter mode: In this mode, the SMUs can connect a battery to the device under test (DUT) and simultaneously log the current drain profile and the battery voltage values with no shunt burden voltage.
These SMUs are modules that are added to power analyzers to capture battery current drain waveforms. Two such power analyzers, one of them a benchtop instrument and the other a system for automated testing, are explained next.
Benchtop power analyzer
Fig 3. N6705C power analyzer
The N6705C is a benchtop poweranalyzer to accurately measure the current draw of the DUT and display its waveform. To simulate various real-world device states, the SMUs are programmed to turn on or off power to different device subsystems and subcircuits.
Power system for automated test equipment
Fig 4. N6700 system power supply
The N6700 series instruments are modular system power supplies for automated test equipment used in high-volume production testing. The battery drain SMU modules can plug into these power supplies and enable them to accurately measure battery drain.
Battery emulator power supply
Fig 5. E36731A battery emulator and profiler DC power supply
An alternative to the above power supplies and specialized SMUs is a battery emulator power supply like the E36731A. It's a two-quadrant device just like the SMUs and is specialized for profiling and emulating battery behavior.
First, it creates battery models by profiling real batteries. Then, those models are used to emulate the same behaviors while simultaneously measuring the current draw and other parameters when connected to a DUT.
Compared to the SMUs, these devices can supply more power, but their measurement resolution and accuracy are lower. Use the SMUs for devices that run on very low currents and require high-precision measurements. Use something like the E36731A for devices that operate at higher currents and have less need of precision.
Battery drain analysis software
Fig 6. PathWave BenchVue advanced battery test and emulation software
Capable software is essential because battery drain is a complex phenomenon that requires sophisticated data analysis to draw reliable conclusions and correctly predict real-world outcomes.
Software like the PathWave BenchVue AdvancedBattery Test and Emulation and the Advanced Power Control and Analysis connect to the power analyzer and system power supplies to provide battery drain analysis features like:
- short-term waveform capture
- data logger for long-term waveform capture
- Complementary Cumulative Distribution Function (CCDF) for statistical analyses of power consumption
Integrated solutions for battery drain analysis
Fig 7. X8712A battery life optimization solution
The X8712A IoTbattery lifeoptimization solution bundles the above instruments and software into a proven and calibrated ready-to-use solution for battery drain analysis.
In the next section, we'll understand how these instruments and software are actually used.
How is battery drain measured and analyzed?
Fig 8. A typical test setup for battery drain analysis of wireless communications
The essential idea is to make the power supply (one of N6705C+SMU, N6700+SMU, or E36731A) emulate a real battery with the help of a battery model while it simultaneously measures the current draw as the DUT is put through its paces with various modes, functions, or onboard software.
Fig 9. Battery drain analysis steps
Let's see how the instruments and software introduced above are used for battery drain analysis:
- Connect the DUT to the power supply: The DUT is connected to the power supply, which is configured to measure current in zero-burden ammeter mode to ensure that the voltage drop across the measurement setup does not affect the battery voltage at the DUT.
- Configure the test parameters: Using the PathWave BenchVue software, configure the desired test parameters like the measurement range and integration period for measured current values.
- Run the test: The test is initiated from the BenchVue software. The software instructs the SMU to emulate a certain battery model's power supply and discharge characteristics. It then accurately measures the current draw by the DUT over the specified test duration.
- Analyze the battery drain data: As the battery drain data is recorded for offline analysis, the software also provides real-time visualization of the current waveform.
Frequently asked questions on battery drain analysis
Below are answers to some common questions engineers have on battery drain analysis.
What are the challenges of battery drain analysis for devices with intermittent or bursty power consumption?
The rapid switching from sleep mode to screen-on mode is an example of bursty power consumption. The current drain can shoot up from nA to hundreds of mA or low A, which is an extremely wide span to seamlessly measure.
The N6781A and N6785A SMUs can span this wide dynamic range with their seamless measurement ranging features.
How can battery drain analysis help identify and mitigate power-hungry components or software functions in a device?
Using event-based power measurements and current measurements at the subsystem or subcircuit levels, it’s possible to accurately identify inefficient components and software functions.
Also, the ability to perform long-term data logging for days or weeks gives insights into how intermittent or continuous use of certain device functions impacts overall battery life. By monitoring the device over extended periods, developers can identify software functions or hardware components that trigger significant power consumption.
Rely on Keysight instruments for accurate battery drain analysis
In this article, we reviewed how battery drain analysis is done and what instruments are used.
Keysight's high-precision instruments equipped with innovations like seamless measurement ranging and sophisticated battery analysis software allow unmatched accuracy in battery drain analysis.
Contact us for expert advice on the testing instruments and software that will help you optimize batteries for your mobile, IoT, medical, or wearable devices.