Measurements optimize battery run time
To characterize your device, you can capture long-term battery current drain data at high sample rates and over a wide dynamic range. A detailed characterization and analysis of your device's battery-current-drain profiles lets you make informed tradeoffs for optimizing run time. You can take a number of approaches measure power consumption.
You can measure current consumption with an oscilloscope and current probes. Oscilloscopes provide high-speed waveform digitization, but their limited dynamic range, 8-bit resolution, and relatively high noise floor add uncertainty to your measurements.
Another option uses a high-sampling-speed, high-resolution, data-acquisition system and a precision current shunt. The better resolution of a data-acquisition system (typically 12 bits or 16 bits) provides better accuracy and wider dynamic measurement range compared to a current probe and oscilloscope. You must, though, keep maximum tolerable current shunt peak voltage drop small so that it does not unduly affect the mobile device. Keeping the shunt voltage drop sufficiently small limits the measurement's dynamic range and low-signal-level accuracy
DC sources that incorporate a high-speed digitizers wide-dynamic-range also let you accurately characterize a mobile device's current drain. This method eliminates the voltage drop issues associated with using external shunt resistors.
Figure 1. A wireless device's current draw pulses during transmit operations, with small pulsed current during receive time.
While mobile phones and many other mobile devices have high-power active modes (which need to be optimized for battery run time), they often spend the majority of their time in standby or another similar type of power-savings mode. Other wireless devices, like sensors, may have only power-savings operating modes. Although the power consumption may seem negligible, because the devices spend long periods in these modes, they can consume a major portion, or even all, of the battery's capacity. Evaluating these power-savings operating modes is a top priority for optimizing battery run time. The nature of current drain, spanning several decades of amplitude, during power-savings operation makes them challenging to measure.
Wireless devices spend most of their time in a low-power sleep state. Periodically, the device wakes up and briefly enters a higher-power active state, often to transmit to and maintain contact with a base station. The resulting current drain is pulsed and has the following characteristics:
- Long period of typically tenths to tens of seconds (even minutes or greater for wireless sensors, depending on their function),
- Extremely low duty cycle of tenths of a percent to a few percent, and
- Extremely high crest factor on the order of a few hundred or higher.
Figure 2. Wireless temperature transmitter's current drain measurements show the difference between sleep current and transmit current.
- Period of 4 s (5 divisions at 0.8 s/div),
- Duty cycle of 0.17%, and
- Approximately 21.8 mA peak and 53.7 µA average currents, for a crest factor of 400.
The wireless temperature transmitter is an example of a very low power device. While these characteristics are quite substantial, they are even far more dramatic for cellular-based devices, certain medical devices, and other battery powered devices drawing peaks of hundreds of milliamps to amps, but having sleep currents of 10's to 100's of microamps.
Optimizing battery run time calls for much more than simply validating the run time. You need to test and characterize your device, its sub circuits, and its battery, both independently and in combination as a system. Capturing and analyzing detailed long-term battery current drain profiles provides deeper insights on the inner workings of the device for optimizing battery run time. The current draw of a wireless devices had a wide dynamic range between power-saving and operating modes. Thus, making the current measurements is particularly challenging.
a BSEE from Villanova University and MSEE from New Jersey Institute
of Technology. Ed joined Agilent Technologies (at that time, Hewlett
Packard) in 1979 and worked as an R&D engineer, manufacturing
engineer, and marketing engineer in many various roles and presently
as an applications engineer in marketing.E-Mail