IoT Battery Life Estimator

Estimate IoT device lifetime from duty cycle, power states, battery derating, and self-discharge.

animation
energy
power
battery
duty-cycle
hardware
intermediate
A learner-ready battery life animation with scenario presets, duty-cycle waveform, drain curve, formula trace, battery derating, and technical accuracy notes.
Animation Intermediate with ramp Duty cycle Battery estimate

IoT Battery Life Estimator

Change the duty cycle and battery assumptions, then watch how a tiny sleep current or a short radio burst can decide whether a device lasts days, months, or years.

4.8 yr Estimated lifetime
44.8 uA Average current including self-discharge
0.022% Awake duty cycle
134 uWh Energy per wake cycle

1. Pick a device

Start with a realistic radio pattern, then compare it with other presets.

2. Watch the cycle

The waveform shows sensor, processing, transmit, and sleep states in one period.

3. Check the budget

Average current is compared with the current budget needed for the target life.

4. Read the limits

Battery capacity, temperature, peak current, and retries are assumptions, not guarantees.

1

Power states

Measure current and duration for sensor, CPU, radio, and sleep.

2

Wake cycle

Add state charge across one interval: mA multiplied by time.

3

Average current

Spread the cycle charge over the full period, including sleep.

4

Battery model

Apply usable capacity, temperature derating, efficiency, and self-discharge.

5

Target check

Compare estimated average current with the budget for the desired life.

6

Reality check

Review radio retries, cutoff voltage, temperature, aging, and peak load limits.

Animated duty-cycle and drain model

A LoRaWAN meter sleeps most of the time, so sleep current and radio burst length dominate the lifetime.

Duty-cycle current waveform Current waveform across one wake interval showing sensor, processing, transmit, and sleep states. LoRaWAN meter One wake interval, compressed so short active states remain visible current one interval Dominant drain sleep Budget status on track budget 45 uA Battery drain over time Battery remaining percentage over time with ideal drain and drain including self-discharge. Battery remaining Capacity derating and self-discharge are included in the estimate. empty
sensor processing transmit sleep ideal drain

Design diagnosis

The design is close to the target. Compare the dominant state and current budget before choosing a battery.

Target fit

On track

Estimated life meets the selected target.

Dominant load

Sleep

Sleep current uses the most charge per day.

Current budget

45 uA

Average current is below the target budget.

Model risk

Moderate

Capacity derating and self-discharge are included, but field retries still matter.

charge_per_state = current_mA x duration_ms / 3,600,000
Quick Reference

Formula State charge

mAh = current_mA x duration_ms / 3,600,000. Add all states in a wake cycle.

Formula Average current

Average mA = cycle_charge_mAh x 3,600,000 / cycle_period_ms.

Formula Battery life

Life hours = usable_capacity_mAh / total_average_current_mA.

Duty Awake percentage

Duty cycle = awake_time / interval. Low duty cycle does not help if sleep current is too high.

Budget Target current

For a fixed target life, the device must stay below a current budget after derating and self-discharge.

Reality Bench first

Measure sleep current and radio bursts with an instrument that can capture both uA sleep and mA peaks.

Battery And Radio Assumptions

Coin cell Pulse limits

Coin cells can have high internal resistance. A nominal mAh rating may not support repeated high radio peaks without voltage sag.

AA lithium Long field life

Lithium primary cells often suit long-life sensor nodes, but capacity still depends on load, cutoff voltage, and temperature.

Li-ion Rechargeable packs

Li-ion packs can supply higher peaks, but self-discharge, protection circuits, and charger leakage can shorten standby life.

LPWAN Short bursts

LoRaWAN and similar radios can last years when messages are infrequent and retransmissions are rare.

Cellular Attach cost

NB-IoT and LTE-M can spend significant energy during attach, coverage search, and poor-signal retries.

Wi-Fi High current

Wi-Fi often needs a larger battery or longer interval because association and transmit current are comparatively high.

Technical Accuracy Notes

Capacity is not fixed

Battery capacity changes with discharge rate, temperature, age, chemistry, and cutoff voltage. Treat catalogue mAh as a starting point.

Average current hides peaks

Averages estimate lifetime, but hardware must still tolerate peak current and voltage droop during radio transmission.

Self-discharge is a current

The model converts self-discharge into an equivalent mA term, so it becomes important for multi-year targets.

Regulator efficiency matters

Boost and buck regulators draw quiescent current and lose energy. Efficiency is approximate unless measured at the actual load profile.

Retries can dominate

Poor signal, acknowledgements, and network joins can multiply radio time. Use a stress case when sizing a battery.

Validate with logging

Use a power profiler or shunt measurement over several complete cycles before promising field lifetime.

Practice 1

Increase sleep current until a five-year LoRaWAN target fails. Notice how small uA changes matter.

Practice 2

Switch to Wi-Fi and lengthen the wake interval. Decide whether interval changes alone are enough.

Practice 3

Apply a cold temperature factor and lower usable capacity. Compare the field result with the nominal result.