Using power analysis to optimize battery life in IoT devices

The Internet of Things (IoT) continues its rapid growth, but in the rush to capitalize on great business opportunities, many companies miss key technical opportunities to gain market share and lock in a large, highly satisfied installed base. Application areas including smart cities, smart agriculture, smart energy, smart environment, smart homes, connected cars, smart buildings, and wireless medical devices are driving forecasts of tens or hundreds of billions of devices over the next few years. Companies that make the right decisions for device operation at end of battery life can delight customers and gain a competitive advantage.

Battery life is key

Many IoT applications rely on small, non-rechargeable batteries, so optimizing battery life is important for several reasons. The most obvious reason is that customers prefer long operating life; device vendors who demonstrate superiority in this area will have a key competitive advantage that drives market share growth.  In some cases, a long battery life may be essential to a project’s economic viability, and early failures of sensors and actuators may lead to unacceptably high replacement costs.  If these costs are covered under warranty, the financial risk to the manufacturer may be extremely high.

There are also environmental issues associated with batteries, and proper disposal costs both time and money. Furthermore, some devices are installed in locations that are difficult to access, so the labor costs of battery replacement are considerable.  If the battery is in an implanted medical device, the cost and risk go up exponentially, to say nothing of the legal and human costs associated with failed medical devices.

To understand how products consume battery power, manufacturers use various tools to perform battery drain analysis (BDA).  For simple devices that consume power at a steady rate, a digital multimeter (DMM) may suffice.  For complex devices, such as cell phones and IoT devices, the current waveforms are highly variable, with fast switching between operational modes in the tens or hundreds of milliamps and sleep modes measured in micro- or nano-amps.  To meet this challenge, modern BDA instruments must have good measurement bandwidth and seamless ranging to avoid losing data during measurement range changes.

Beyond battery drain analysis to event-based power analysis

To make the appropriate design enhancements, design engineers also must know what is causing the charge consumption.  This is particularly important for IoT device designers, because the IoT evolves quickly and product development cycles are very tight.  Design and validation engineers must get quick insights into how and why their devices consume power, so correlating charge consumption with RF and sub-circuit events is key.  Many engineers find that event-based power analysis quickly reveals what events they need to focus on to improve their device’s charge consumption behavior.  For example, event-based power analysis software can automatically analyze a waveform to produce fast, graphical insights, as shown below in figure 1.


Figure 1:  Event-based power analysis on Keysight X8712A IoT device battery life optimization solution

In this case, the user can quickly see that the events labeled MCU and DUT Tx are consuming more than 80% of the device’s power (bar chart), and that most of the charge is consumed at rates between 5 and 10 mA (CCDF chart, bottom).  Such insights allow the design engineer to make intelligent architectural, hardware configuration, and firmware programming choices. The engineer can also quickly re-test the device to see the effects of the changes.

Eventually, of course, the device’s battery will near the end of its charge, and what was once a steady 3.3-V battery (for example) will deliver only 3.2 V, then 3.1 V, and so on until it fails completely, often in a mode that turns out to be surprising.  Instead of simply letting the device operate normally until the battery fails, you can give your product a competitive edge by carefully answering the following questions:

  • How does the device behave as voltage drops?

  • How does this affect charge consumption?

  • Where is the critical point?

  • What would customers want you do about it?

1 thought on “Using power analysis to optimize battery life in IoT devices

  1. “The battery life of IOT devices can be extended by a large factor is proper design techniques are implemented. These include, limiting the peak current drawn from the battery, avoiding intermitent wake-ups etc. To ensure this can be done, measuring the cu

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