This article discusses how to accurately predict battery life and manage + monitor battery level of devices in the field.
Click to jump to:
- TABLE OF CONTENTS
- The Battery Meter - Coulomb Counter
- Other Devices (without the Battery Meter)
- Battery Good Flag and Alerts for Low Battery
- How do I monitor and alert on battery level in Telematics Guru and 3rd Party Platforms?
- Predicting Battery Life
- Indicative Battery Lifetimes
- Trip Tracking Battery Life
Predicting the battery life of Lithium batteries is quite difficult due to their chemistry. The batteries will output a constant voltage until nearly the end of their life, and suddenly this drops off. Meaning early warning, and accurate gauging of battery life is quite difficult based on voltage alone.
Below is the discharge profile of Energizer Ultimate Lithium L92 (AA) batteries.
Due to this flat profile, it is hard to say that a certain voltage means a certain percentage of battery remaining. Each percentage range is fairly broad. However we have developed a variety of methods to aid in achieving the best possible battery capacity estimates. Device firmwares handle most of this automatically in the background.
The Battery Meter - Coulomb Counter
The Remora2, Falcon, Eagle and Oyster2 are fitted with a battery meter (coulomb counter) that tracks energy (mAh) used by the battery.
A coulomb counter is a device which measures the total amount of charge flowing out of the battery. This can be used to estimate the battery percentage, and remaining battery life.
This is superior to voltage alone. Considering the discharge profile graph above, for the first 600mAh per cell of capacity used, the voltage changes minimally. So we can't make accurate capacity estimates when we only have voltage to go off. However the battery meter would be able to detect this and therefore tell what percentage has been utilised - i.e. 600mAh/1200mAh = 50%.
Despite the excellent battery capacity estimates the battery meter provides, these estimates still rely on an assumption of the total capacity of the batteries. This can vary per battery type, and even on a single type quite significantly due to temperature variations. So the estimates aren't infallible.
How the battery meter generates the capacity estimates is detailed below.
Oyster2 and Falcon
The device 'guesses' as to whether the installed batteries are Lithium Iron Disulphide (LiFeS2), or Lithium Thionyl Chloride (LTC) based upon the battery voltage reading. LiFeS2 are 1.5V nominal per cell compared to LTC 3.7V
i.e. 3 x 1.5 LiFeS2 batteries will result in around 5.2V total supply voltage when fresh. The LTCs will read around 12V.
Once this is determined the following assumptions are made:
- LTC - capacity of 1650mAh
- LiFES2 - capacity of 3100mAh (Energizer Ultimate Lithiums are assumed)
So how do we know the percentage?
If the coulomb counter measures 1650mAh has been used, and the battery voltage is low enough to suggest LiFeS2 batteries, then we can say there is 1650mAh remaining, i.e. - (3100-1650)/3100 * 100% = 50%
14Ah capacity of the 2 x D Cell LTC batteries is assumed.
Eagle 4G 4x C Cells default mAh are:
- Alkaline Cells - 7000mAh
- LTC Cells - 6000mAh
Other battery types and adjusting the capacity assumptions
The assumptions for battery mAh and capacity can be changed under this parameter tab in System Parameters if required.
In general, these should remain unchanged (do not touch these parameters unless you know what you are doing). However if you are finding you are regularly getting greater/less capacity from your batteries, or you are using a different type of batteries with a different total capacity - they can be adjusted.
Other Devices (without the Battery Meter)
Since other battery powered devices in our range do not have a battery meter, the battery estimate must be made on voltage alone. We recommend Energizer Ultimate Lithium for the following devices:
- Yabby GPS + Yabby Wi-Fi
- Oyster v1
- Oyster Sigfox
- Oyster LoRaWAN
- Yabby LoRaWAN
- SensorNode BLE
- SensorNode LoRaWAN
The above all use 3 x AA 1.5V Lithium Batteries. The Oyster Sigfox can however be used with Alkaline batteries if needed - percentage -> voltage ranges for these batteries can be found here: Oyster Sigfox Battery Curves.
The nature of the Lithium AAA batteries (LiFeS2) recommended requires a capacity estimate to be made based on sampling the battery voltage after at least 3 hours at a low current. The devices attempt to sample the battery voltage at a low current, and the highest recent sample is stored in Analogue 1. This can be used to make some rough estimations of the remaining capacity. Given all devices make use of 3 x 1.5V Lithium cells - and this is the voltage that is being measured, the ranges below is the same across all devices which use 3 x cells (AA or AAA is the same).
The below voltage ranges therefore apply to all the above devices.
'Battery Good' Status Flag
|4.85 – 5.30 V||50% + remaining||Set (1)|
|4.20 – 4.85 V||0 – 50% remaining||Clear (0)|
The Guppy BLE and Guppy LoRaWAN only use 2 x 1.5V Lithium Cells, so the total voltage is always 2/3 that of the other devices. So the capacity for these devices becomes:
|3.25 - 3.5V||50% + remaining|
|2.8 - 3.25V||0 - 50% remaining|
- This will be less accurate if the device does not regularly sleep for 3 hours. For example, hourly heartbeats may not allow the battery voltage to recover completely, leading to a lower estimate.
- Further to the previous point, the voltage will not recover completely if the device is usually colder than 5 degrees C. The low temperature stops the battery voltage from recovering completely, providing a lower capacity estimate.
- Analogue 5 (Loaded Voltage) is an instantaneous sample of the battery voltage, and varies considerably with device activity. This is not useful for battery capacity estimates.
Battery Good Flag and Alerts for Low Battery
The 'Battery Good' Flag is bit 1 of the digital status flags (Field ID 2) - or Digital input 25 in Telematics Guru.
The Remaining Battery Percentage is reported in Analogue 6 in the device data and in Telematics Guru.
Cellular devices devices use a 'Battery Good' Flag. It is set '1' when the battery is 'good', and cleared '0' when the battery is not good (see table above) This applies to all cellular devices - both battery powered devices, and the internal back up battery of powered devices. The device firmware selects an appropriate voltage level to 'unset' the Battery Good Flag. This means integrators can simply set up a low battery alert to fire when this flag is unset - and it will operate consistently across all DM devices.
This is how the Telematics Guru 'Low Battery' alert works.
For the devices with the battery meter (Oyster2, Remora2, Falcon), the low battery flag is unset when the remaining battery percentage drops below 20%. For the Eagle this occurs at 15%.
How do I monitor and alert on battery level in Telematics Guru and 3rd Party Platforms?
3rd Party Platforms
For devices with a battery meter - the remaining battery % is in Analogue 6. A low battery alert can be set at any level, or use the low battery flag - which fires at 20% remaining.
For other devices, use the 'battery good' flag from the status flags in Field 2. This flag uses the voltage ranges in the table above. Alert when this bit is '0'.
Predicting Battery Life
Devices with the Battery Meter provide an excellent way to estimate how long batteries will last in a given application.
We can simply run the device in the intended application, with the desired settings, and take note of the remaining battery percentage over time.
So for example, if we run an Oyster2 in the intended application for 4 weeks, and 4% of the battery is used in this time, therefore we know that the usage rate is 1% per week, and we will get 100 weeks of life.
Telematics Guru's Battery Management page handles this all for us, and displays the estimated run time for all devices in a grid. Battery life is impacted by a wide variety of factors and the actual usage as measured by the Battery Meter is the true real-world usage which has all these factors accounted for.
To get a rough estimate of battery life when assessing the suitability of a device for an application, the calculators at the bottom of the article can be referenced.
Indicative Battery Lifetimes
Please be aware that these are estimations, and can be influenced heavily by factors such as:
- Application and configuration
- The battery life is dependant on the update rate and other settings
- GPS reception
- If GPS reception is poor, the device has to work harder, and keep its GPS module on for longer in order to get a fix - or it may time out and fail to get a fix, draining additional battery.
- GSM Reception
- As for the GPS, the same applies for the cellular modem attempting to connect to the network
- Mounting position
- This will impact GPS and GSM reception
- Battery type and chemistry
- Different batteries are of different quality and capacity
- Extreme temperatures reduce the lifetime of most battery types.
The below table shows the battery life estimations from Lithium or LTC batteries (where applicable) across the battery powered range - when they are configured for Periodic Tracking
Battery Life - Periodic Updates
|Avg. GPS fix time||10s||15s||30s||45s||60s||60s|
|Oyster2 4G||1 year||1.8 years||2.8 years||4.5 years||6 years||7 years|
|Remora2 4G||5 years||8.5 years||10 years||10 years||10 years||10 years|
|Yabby GPS 4G||17 weeks||30 weeks||45 weeks||1.3 years||1.7 years||3 years|
|Yabby Wifi 4G||20 weeks||40 weeks||1.4 years||2.5 years||3.8 years||6.5 years|
|Oyster Sigfox||1.5 years||2 years||2.5 years||3.3 years||3.7 years||5.5 years|
Why does the average GPS fix time have an impact?
Our device make use of GPS aiding data. This is data which is downloaded by the device, giving positions of the satellites. If the aiding data is fresh, GPS fixes are acquired faster. This means the GPS does not need to be run as long, and so it uses less power. Aiding data goes 'stale' after about 4 hours. So for this reason, the relationship between update rate and battery life is not linear, as when fixes are being acquired more regularly, they are achieved faster thanks to the aiding data.
Additionally, failed GPS fixes have an impact, as if a device is undercover/indoors and cannot get a GPS fix, the GPS module will attempt to get a fix for the GPS Fix Timeout - which is typically 60 seconds by default. This will increase the battery consumption, and is why predicting battery life can be tricky, as we can't predict the impact of this ahead of time (luckily the Battery Meter can help!)
If a heartbeat period is set under 4 hours, then it is considered a 'warm' GPS fix (fresh aiding data) and will optimally take around 10-15seconds to get a valid fix. This increases up to 24 hour heartbeats which can take around 60-120 seconds, as they are not sped up by fresh aiding data.
Indicative GPS fix times (for use with the calculators):
|Logging Interval||<2 hours||4||8||12||24|
|Typical GPS Fix Time||10-15 sec||20 sec||30 sec||45-60 sec||60-120 sec|
What about the Eagle and Falcon?
These devices are much more complicated to predict as their behaviour isn't as well defined, particularly due to the effect of connecting up sensors that draw power. For information on these devices, see Eagle and Falcon - Estimating Battery Life
Periodic Battery life Calculator
The below calculator is where the table of lifetimes is calculated from. It can be used to estimate battery lifetime for other heartbeat intervals.
Trip Tracking Battery Life
Our battery powered devices by default are configured to increase their update rate while on the move. This means when a device is stationary, it simply heartbeats (as a check-in) periodically - typically every 12 or 24 hours. When movement occurs, more GPS fixes are recorded and these are uploaded in batches. This provides detail when it is needed while the device is on the move, and conserves battery life when it is sitting still. The device settings are highly configurable - and addtionally a key driver in the battery life in this scenario is obviously how much/how often the device is on the move (i.e. and updating more regularly). Identical settings and differing amounts of asset utilisation will result in wildly different battery life.
The below calculator can be used to estimate battery lifetimes with specific settings and amounts of daily movement. GPS fix times should be adjusted based on update interval as per the above