LoRa is chosen for range and efficiency, but many nodes still miss battery targets by a large margin. The reason is usually poor budgeting assumptions and missing field validation.
1. Build a current profile per operating mode
Measure current in each mode:
- deep sleep
- sensor warm-up
- sensor sampling
- radio transmit
- radio receive window
Do not rely only on datasheet typical values. Board-level leakage and regulator losses can dominate.
2. Duty-cycle aware energy model
Compute average current from real duty cycle:
- sample interval
- payload size
- spreading factor and airtime
- retransmission rate
Long airtime configurations can multiply energy usage unexpectedly.
3. Battery chemistry and temperature behavior
Battery curves vary significantly by temperature. If deployments see winter conditions, capacity assumptions must be derated.
Also account for pulse-current limits during radio bursts.
4. Regulator and peripheral overhead
Common hidden drains:
- always-on regulator quiescent current
- sensor modules that never fully sleep
- indicator LEDs
- USB-UART bridges left powered
These are often bigger than MCU sleep current.
5. Firmware power patterns
Power-friendly firmware rules:
- batch sensor reads in one wake window
- avoid unnecessary RX listening windows
- compress payload to reduce airtime
- disable debug interfaces in release builds
Tiny code choices can add months of battery life.
6. Reliability vs power tradeoffs
More retries improve data delivery but cost power. Define acceptable loss rate and tune retransmission policy accordingly.
For non-critical telemetry, controlled loss can be preferable to rapid battery depletion.
7. Field validation plan
Lab numbers are not enough. Validate with:
- real gateway distance
- environmental temperature variation
- expected RF interference
- long-run discharge observation
Track battery voltage and event counters over weeks.
8. Maintenance and replacement policy
Set replacement thresholds and maintenance cadence from measured degradation, not optimistic calculations.
Document expected runtime bands, not a single number.
Final note
A reliable LoRa power budget is built from measurement, realistic airtime assumptions, and field data feedback. When these are in place, battery predictions become trustworthy.