Low power design

Low power design

Battery life is an arithmetic problem: average current = (active current x active fraction) + (sleep current x sleep fraction), and the sleep term usually dominates. Design the duty cycle first, then make sleep genuinely cheap, then measure because estimates always lie.

Method

1. Build the power budget spreadsheet first. Battery capacity (derated for temperature and aging), target lifetime, and the resulting average-current ceiling; then allocate: sleep floor, per-wake cost (sensor read, radio transmission), wakes per hour. This arithmetic decides the architecture (see capacity-planning's spirit in microamps): a 5uA budget with a 20mA radio means the radio runs seconds per day, which shapes everything (see iot-messaging's batching).
2. Sleep as deep as state allows, wake on events. Map the MCU's sleep states (stop/standby with RAM retention tradeoffs: see embedded-memory-constraints' retention note) and choose per situation; wake sources are interrupts (RTC, GPIO edge, comparator), never polling loops; RTOS tickless idle so the scheduler itself stops the tick (see rtos-task-design's idle hooks). The design question per feature: "what is the cheapest state that can notice this event".
3. Kill the parasitic draws. Floating GPIOs (configure every pin), pull-ups fighting drivers, sensors and regulators left enabled, debug interfaces powered in the field, LEDs (a single LED can dwarf your MCU budget): power-gate peripheral rails where hardware allows. Most "impossible" sleep-current numbers are one forgotten peripheral; the hunt-order is a checklist, not intuition.
4. Make radio time the scarcest resource. Transmit costs orders of magnitude over compute: batch readings (see sensor-data-handling), compress/delta-encode, prefer connectionless or long-interval protocols suited to the link (see iot-messaging's QoS and keepalive costs), and back off reconnect attempts exponentially: a device that retries a dead network every second dies in days (see timeouts-and-retries, translated to milliamp-seconds).
5. Measure with real instruments across modes. A power profiler (Joulescope/PPK-class) or precision shunt across the actual operating modes: sleep floor, wake spike shape, radio bursts: not a multimeter average. Automate a power regression test (scripted device cycle on the profiler, CI or nightly): power regressions arrive silently with any firmware change (see performance-testing's gate ethic, in microamps).
6. Account for the analog realities. Brown-out behavior at battery end-of-life (clean shutdown, state saved: see firmware-ota-updates' power-loss machine), cold-temperature capacity collapse, self-discharge and quiescent regulator draw in the total, and duty-cycle jitter so synchronized fleets do not all wake together (see scheduled-jobs' jitter).

Boundaries

• Energy harvesting (solar, kinetic) changes the problem to power management (make progress when energy exists, checkpoint always); the measurement discipline transfers, the budget becomes stochastic.
• Wall-powered devices still care (thermals, efficiency standards) but the microamp obsession does not transfer; do not tax those designs with battery ceremony.
• Battery chemistry selection, fuel gauging, and charging are electrical engineering with safety implications; firmware consumes their outputs but the design belongs to hardware review.