Low power high accuracy fuel gauging
tailored for embedded IoT
Estimating state-of-charge
in lithium batteries is crucial for optimizing performance and ensuring safe operation. There are several methods used to estimate the state-of-charge of single-cell lithium batteries.
All methods have their benefits and drawbacks, but some benefits are more desired and some drawbacks are less severe than others. For the nPM1300, we decided that algorithm based fuel gauging was the way to go.
To take advantage of the fuel gauging capabilities of the nPM1300, you can read the application note explaining how to create a virtual model of your battery for use with the fuel gauge sample in the nRF Connect SDK.
For selected lithium ion polymer batteries from Renata, Nordic is also providing turnkey battery models ready to use. Scroll down to se the list of supported batteries.
Learn how
Guide to profile your batteries with nPM FG
Low power high accuracy fuel gauging tailored for embedded IoT
To accurately estimate the battery state-of-charge in percent, from 0 to 100 %, the nPM1300's fuel gauge functionality uses a virtual model of your battery along with the battery's temperature, voltage and the current measured by the PMIC. The estimation algorithm can then be run on any Arm Cortex M4 or M33, like those found in the nRF52, nRF53 and nRF91 Series and does not require additional hardware beyond this.
The battery model is created by doing an analysis of your specific battery, in your own lab, with the help of the nPM1300 Evaluation Kit along with a dedicated nPM Fuel Gauge board.
Learn how to profile batteries from the comfort of your own lab:
Fuel Gauging Webinar
nPM PowerUP walktrough Webinar