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CR2032 Coin Cell battery life estimation with NRF52 as beacon

Hello,

This in reference to Case ID: 121570. 

We are developing a wearable device with NRF52 as a Beacon with CR2032 coin cell battery from Panasonic. We have calculated the theoretical CR2032's battery life using the formula mentioned in the Case mentioned above. Is there any way to cross check it practically by some experiment as we need to assure our customers about minimum life of the product?

Any help would be highly appreciable!

Thank You,

Madhav

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  • Hi Madhav,

    You can refer to the Measuring current chapter in the nRF52 DK documentation for details about how to measure current consumption. You need to measure the current consumption during development as well, to verify that the current consumption is as expected. We often see customer projects with too high current consumption, typically caused by how the nRF is used (such as not disabling peripherals that are not needed, keeping HFCLK running etc.) or other components on their custom PCB drawing a lot of current.

    I recommend you also use the nRF52 Online Power Profiler to find the power consumption of the nRF52 beacon. This is uses a model that is based on extensive testing and measurements, and results are typically within 5%. Then you compare that with the data you have from your battery to find the expected battery life of your device.

     

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  • Hi Madhav,

    You can refer to the Measuring current chapter in the nRF52 DK documentation for details about how to measure current consumption. You need to measure the current consumption during development as well, to verify that the current consumption is as expected. We often see customer projects with too high current consumption, typically caused by how the nRF is used (such as not disabling peripherals that are not needed, keeping HFCLK running etc.) or other components on their custom PCB drawing a lot of current.

    I recommend you also use the nRF52 Online Power Profiler to find the power consumption of the nRF52 beacon. This is uses a model that is based on extensive testing and measurements, and results are typically within 5%. Then you compare that with the data you have from your battery to find the expected battery life of your device.

     

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