Battery Life Calculator
Estimate how long a battery will last. Enter capacity in mAh, load current (or power + voltage), and an efficiency factor — get runtime in hours, minutes and days.
Last updated: May 2026
Enter capacity and load to estimate battery runtime.
Hours = capacity (mAh) × efficiency ÷ current (mA)
Common scenarios
Battery runtime — what the numbers actually mean
The basic formula is simple: divide capacity (mAh) by current (mA) to get hours. A 2,000 mAh battery at 200 mA = 10 hours. But real devices do not draw constant current — they sleep, spike, and idle. The efficiency factor accounts for voltage regulator losses (a linear LDO wastes voltage as heat; a buck converter at 85% efficiency keeps most of it).
For projects with deep-sleep modes, calculate the average current: (active_mA × active_seconds + sleep_mA × sleep_seconds) ÷ total_cycle_seconds. Enter that average current for a realistic runtime estimate.
Typical current draws
| Device / mode | Typical current |
|---|---|
| ESP32 deep sleep | 10–20 µA |
| ESP32 active (Wi-Fi transmit) | 160–260 mA peak |
| Arduino Uno active | ~50 mA |
| Raspberry Pi Zero 2W (idle) | ~120 mA |
| LoRa module (transmit) | ~100 mA peak |
| LoRa module (receive) | ~12 mA |
| Small OLED display | 10–25 mA |
| GPS module | 20–30 mA |
Frequently Asked Questions
Why does a 2000 mAh battery not last exactly 2000/load hours?
Several factors reduce real runtime below the theoretical figure: (1) Voltage cut-off — batteries are not fully dischargeable; lithium cells cut off at ~3.0 V, losing 5–10% of rated capacity. (2) Temperature — cold reduces effective capacity significantly (Li-ion loses ~20% at 0°C). (3) Regulator losses — a linear LDO dissipates the voltage difference as heat; the efficiency field in this calculator accounts for this. (4) Peukert effect — drawing more current reduces effective capacity; rated mAh is typically at a 0.2C or 1C discharge rate.
What efficiency value should I use for a LiPo with a boost converter?
A good switching boost converter runs at 85–92% efficiency at moderate loads. At very light loads (<10 mA output), efficiency can drop to 70–75% due to switching losses. Use 85% as a conservative starting estimate for projects using a boost regulator from a 3.7 V LiPo to 5 V. If the datasheet shows an efficiency curve, use the value at your expected output current.
How do I extend battery life for a microcontroller project?
The single most effective technique is using deep sleep aggressively. An ESP32 drawing 200 mA active but sleeping 99% of the time averages just ~2 mA — a 100× improvement. After that: (1) reduce clock speed when full performance is not needed; (2) turn off unused peripherals (Wi-Fi, Bluetooth, ADC); (3) switch from a linear LDO to an efficient buck converter; (4) use lower system voltage if the MCU supports it (3.3 V instead of 5 V); (5) replace polling loops with interrupt-driven wakeup from sensors.
Can I use this calculator for AA or AAA alkaline batteries?
Yes. A AA alkaline battery is approximately 2,400–3,000 mAh at low drain rates (<50 mA). At higher drain (200–500 mA), effective capacity drops due to the Peukert effect — use 1,500–2,000 mAh as a more realistic value. AAA batteries are roughly 1,000–1,200 mAh at low drain. Alkaline chemistry also shows significant voltage sag under load — if your device has a minimum supply voltage, it may cut out before the battery is technically empty.