Enter each operating mode with its current, duration and how often it happens. The calculator returns the average current, the runtime, and which mode is actually spending your battery — including self-discharge, which often exceeds the circuit itself.
| Mode | Current (mA) | Duration (ms) | Times per hour | Duty | Average (µA) | Share |
|---|
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Peak current sizes your decoupling and your regulator. It has almost nothing to do with runtime. What drains a cell is the average, and on a duty-cycled device that average is usually dominated by something with a duty cycle well under one percent.
Load the example and look at the share column. A radio transmitting 120 mA for 25 ms twelve times an hour has a duty cycle of one hundredth of a percent, and still contributes more than the microcontroller that is awake far longer. Meanwhile the 5 µA sleep current runs continuously and quietly matters more than either.
Iavg = Σ ( Imode × duration × rate ) per hour
·
runtime = usable mAh / (Iavg/η + Iself-discharge)That structure is why firmware optimisation so often disappoints. Halving the processing time of a mode contributing 8% of the drain buys 4%. Finding the mode at 60% is where the runtime is.
Every cell flattens itself. At 2% a month a 2000 mAh cell is losing about 55 µA continuously — more than many well-designed sleep modes draw. Once your circuit is quieter than the chemistry, further firmware work changes nothing at all, and the tool says so explicitly when that crossover happens.
This is the honest ceiling on multi-year battery products, and it is why chemistry selection is a design decision rather than a purchasing one. Lithium primary cells self-discharge at a fraction of a percent a year; some rechargeables lose several percent a month.
Each of these runs entirely in your browser. Nothing is uploaded, stored or sent anywhere, and none of them needs an email address.
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