4 Ways to Enhance IoT Battery Performance Using Emulation Software
White Papers

4 Ways to Enhance IoT Battery Performance Using Emulation Software

Show Description

Battery profiling and emulation software is a solution engineers can use to accurately predict battery life. In addition, engineers can use insight into the battery behavior provided by software to change device designs resulting in longer battery run time. This white paper discusses how you can use emulation software to achieve these objectives and includes the following topics:

  1. Profiling batteries through charging / discharging to create unique battery models.
  2. Emulating charge states to reduce test time, improve safety, and gain insight to extend battery life.
  3. Visually tracking the charging and discharging of batteries to determine capacity.
  4. Cycling batteries to determine loss of capacity and reduction of battery life.

Battery life can contribute significantly to the cost and reliability of Internet of Things (IoT) infrastructure. While for consumer electronic devices, battery life is often a critical purchase consideration. Therefore, the fact that the calculated battery life of IoT devices is often inaccurate is a significant issue for manufacturers.

One method to measure battery life is to divide the battery capacity in amp-hours by the average current drain in amps which gives you a time in hours. However, in the real world, this calculation is overly simplistic.

This formula can generate inaccurate results because devices use different power modes, including active, sleep, and hibernate. Additionally, operating modes such as constant power and constant resistance will draw current from the battery differently and change the battery lifetime. It is essential to fully understand how a battery responds to these different scenarios and the typical usage patterns of the device to predict battery life accurately.

In addition to varying current drain, battery capacity is variable, depending on the average discharge current and usage patterns. Furthermore, temperature can affect battery life; so it is critical to consider this.

The following are additional factors that can lead to a longer computed battery runtime as compared to real-world usage:

  • Battery model / profile is not available to the engineer.
  • Battery profiles are not generated with accurate device operating conditions.
  • Current consumption measurements are not accurate.
  • Voltage drops such as a device shutting down when the voltage reaches a cutoff range are not considered.

Battery profiling and emulation software can enable you to accurately predict battery life and not allow these factors to impact your estimates.