Estimate predictive-maintenance sensor battery life from active time, sleep load, battery energy, and usable-capacity derating. The model builds a daily energy budget from active and sleep states, then reports runtime in days and years plus average power. It is useful for comparing sampling and radio-duty-cycle assumptions, while temperature, pulse current, self-discharge, and battery aging still need separate validation.
The runtime is a steady-duty-cycle estimate. Shortening active time can materially extend life because active power is often far greater than sleep power.
Add self-discharge, temperature effects, transmission retries, and end-of-life voltage constraints through a conservative usable-capacity input or a more detailed engineering model.
A 19 Wh battery at 80% usable capacity, with 0.6 W active power for 12 minutes daily and 0.08 mW sleep power, uses about 0.1219 Wh per day. Estimated runtime is 124.69 days, or 0.34 years.
Active minutes are divided by 60 to obtain hours, then multiplied by active power in watts.
Yes. Sleep power is applied to the remaining hours of each day.
The calculator can estimate sleep-only runtime, but at least one power state must consume energy.
Not explicitly. Reflect it through usable-capacity derating or use a detailed battery model.
Temperature, retries, aging, leakage, pulse-current limits, and changing duty cycles can reduce actual life.
| State | Energy calculation |
|---|---|
| Active | Active power × active hours |
| Sleep | Sleep power in watts × remaining hours |
| Daily total | Active energy + sleep energy |
| Runtime | Usable battery energy ÷ daily total |