How to deal with short battery life in wireless sensors
Keywords:IoT sensor battery life battery drain analysis
When we add this current drain to the 599nA sleep current, it moves to 730nA, 22 per cent higher current than we expected. This type of surprise can be one of the reasons for underestimating energy requirements and delivering a shorter battery life than anticipated.
In wireless sensor power optimisation, engineers get great value by understanding the details. Knowing how much energy it takes to send out a single packet of information is very important when balancing user experience against battery drain and answering questions such as "should I send information once every second, every 5 seconds or every 10 seconds?" Engineers can accurately estimate the battery drain impact of any firmware change and validate it in a reasonable time with real measurements.
Joule measurements made easy
Joules are useful in battery life estimation, as every activity has a defined amount of energy. We can also compare device performance using Joules/transmitted bits. But engineers rarely use Joules because they need to be calculated from voltage, current and time.

Figure 5: Using Keysight 14585A software, you can measure energy directly in Joules.
With the Keysight 14585A control and analysis software, energy in Joules can be measured directly. For example, you might measure the energy consumed by transmitting a packet (see Fig.5) captured with a triggered measurement.
This is one benefit of having two digitisers for voltage and current with simultaneous sampling that enable point-by-point power measurements. Joules can be easily read out as a value between the markers, and designers can go a step further by defining Joules/transmitted bit.
Summary
Engineers who design IoT battery-powered devices use advanced power management techniques to conserve battery life. Traditional measurement techniques are complex, time consuming and don't deliver the measurement accuracy required to optimise and validate battery drain, and often this causes engineers to underestimate the power required to operate the device.
The Keysight SMUs for battery drain analysis enable accurate current drain analysis with one picture that provides a complete and detailed current and energy drain analysis. Post-analysis software simplifies the engineer's job by offering visibility into details never seen before.
With Keysight's latest introduction of the N6785A SMUs for battery drain, these capabilities are now available up to 80W and from nA to 8A. The new SMUs are used in multiple applications from smartphone and tablet testing to automotive ECU and IoT wireless sensors and chipsets.
- Carlo Canziani
EE Times Europe/business development manager
Keysight Technologies
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