Battery Life Calculator
Reviewed by Hamza Gujjar, Algorithm Architect & Software Developer
Last updated: August 19, 2026Capacity Alone Doesn't Predict Runtime
A battery's rated capacity, whether in milliamp-hours or watt-hours, only tells half the story: runtime depends just as much on how fast the device draws power. A 4000 mAh phone battery lasts vastly different amounts of time depending on whether the screen is off and the radio idle, or the camera and display are both running at full brightness. This calculator divides capacity by draw — in either the mAh/mA or Wh/W convention — to get an estimated runtime.
The Formula
Both modes are the same relationship expressed in different units, adjusted for conversion efficiency:
Life (h) = Capacity (Wh) × Efficiency / Power Draw (W)
Efficiency accounts for the fact that not all stored energy converts into usable output — voltage regulation, heat, and battery age all reduce the effective capacity available. Leaving it at 100% gives the theoretical maximum runtime.
Where This Calculation Matters
- Comparing devices before buying — converting a manufacturer's mAh or Wh rating alongside a typical power draw figure into a real-world runtime estimate.
- Portable electronics design — sizing a battery to hit a target runtime for a known current draw, such as an IoT sensor or wearable.
- Power bank sizing — estimating how many charge cycles a portable battery pack can deliver to a device with a known draw.
- Field and travel planning — predicting how long equipment like a drone, radio, or camera will run on a given battery before needing a swap or recharge.
Runtime Examples
| Device Type | Capacity | Draw | Runtime |
|---|---|---|---|
| Smartphone, light use | 4000 mAh | 200 mA | 20.0 hours |
| Smartphone, heavy use | 4000 mAh | 500 mA | 8.0 hours |
| Laptop, light use | 60 Wh | 15 W | 4.0 hours |
| Laptop, heavy use | 60 Wh | 30 W | 2.0 hours |
Real-world runtime is typically shorter than the 100%-efficiency figure, since regulator losses, battery aging, and temperature all reduce usable capacity.
How to Use This Calculator
- Choose a mode: From Capacity (mAh) & Current Draw or From Energy (Wh) & Power Draw.
- Enter the battery's Capacity in mAh or Wh, matching the mode.
- Enter the device's Current Draw (mA) or Power Draw (W).
- Optionally set Efficiency % (defaults to 100 if left blank).
- Select Calculate to get the estimated runtime in hours.
Related Calculations
Need to know how long a recharge takes instead of a discharge? Use the Charging Time Calculator. Sizing a capacitor rather than a battery? See the Capacitor Charge Calculator.
Principles of Battery Capacity and Discharge Kinetics
A battery life calculator determines the operational runtime of a battery-powered electronic device, electric vehicle, or off-grid solar energy storage system based on battery cell storage capacity, nominal voltage, load current draw, and chemical discharge efficiency. Battery capacity is rated in milliampere-hours (mAh), ampere-hours (Ah), or energy Watt-hours (Wh), where Watt-hours accounts for cell nominal voltage:
The Ideal Runtime Formula and Peukert's Law
For low-power constant-current applications, theoretical runtime is calculated as:
However, in high-drain applications (such as power tools or EV motors), available capacity drops non-linearly due to internal electrochemical cell resistance, governed by Peukert's Law:
Where C is rated battery capacity at discharge hour rating H (typically 20 hours), I is actual discharge current, and k is the Peukert constant (typically 1.05 to 1.15 for Lithium-ion, and 1.20 to 1.35 for Lead-Acid).
Battery Chemistry Performance Comparison
| Battery Chemistry | Nominal Cell Voltage | Usable Depth of Discharge (DoD) | Typical Cycle Lifespan |
|---|---|---|---|
| Lithium-Ion (NMC / NCA) | 3.6V to 3.7V | 80% to 90% | 800 to 1,500 cycles |
| Lithium Iron Phosphate (LiFePO4) | 3.2V | 90% to 100% | 3,000 to 6,000+ cycles |
| Nickel-Metal Hydride (NiMH) | 1.2V | 70% to 80% | 500 to 1,000 cycles |
| Sealed Lead-Acid (AGM / Gel) | 12.0V (6 cells × 2V) | 50% maximum | 300 to 500 cycles |
Step-by-Step Worked Calculation Example
Example: Calculating Runtime for an IoT Environmental Sensor Node
Problem: A wireless IoT weather sensor is powered by an 18650 rechargeable Lithium-ion battery rated at 3,200 mAh (3.7V nominal). The device has two operational states: Active Transmission Mode (draws 120 mA for 2.0 seconds every minute) and Deep Sleep Mode (draws 0.05 mA for 58.0 seconds every minute). Assuming 85% usable battery discharge efficiency, calculate: (1) Average continuous current draw; and (2) Total operational battery life in days.
Step 1: Calculate time-weighted average current draw:
Active Phase Consumption = 120 mA × (2.0 s / 60.0 s) = 4.00 mA
Sleep Phase Consumption = 0.05 mA × (58.0 s / 60.0 s) = 0.0483 mA
Average Current (Iavg) = 4.00 + 0.0483 = 4.0483 mA
Step 2: Calculate usable battery capacity:
Usable Capacity = 3,200 mAh × 0.85 = 2,720 mAh
Step 3: Compute total runtime:
Runtime in Hours = 2,720 mAh / 4.0483 mA = 671.88 Hours
Runtime in Days = 671.88 / 24 = 27.99 Days (approx. 28 days)
Conclusion: The sensor node will operate for approximately 28 consecutive days on a single battery charge.
Common Traps in Battery Life Estimations
- Overestimating Usable Lead-Acid Capacity: Discharging lead-acid batteries beyond 50% Depth of Discharge causes permanent plate sulfation and cuts battery cycle life in half.
- Temperature Degradation: Sub-freezing winter temperatures (-10°C) reduce available lithium-ion capacity by 20% to 40% due to sluggish liquid electrolyte ion diffusion.
Coulomb Counting and State of Charge (SoC) Estimation
In advanced battery management systems (BMS), real-time State of Charge estimation is performed through Coulomb Counting: integrating instantaneous electrical current over time:
Because pure current integration accumulates drift over time due to sensor measurement noise and changing internal cell resistance, modern automotive BMS algorithms combine Coulomb counting with extended Kalman filters (EKF) and open-circuit voltage (OCV) look-up tables to achieve SoC accuracy within ±1.0%.
Self-Discharge Rates and Storage Preservation
All electrochemical batteries undergo spontaneous internal self-discharge even when disconnected. Storing lithium-ion batteries at 100% full charge at high ambient temperatures (>30°C) accelerates electrolyte oxidation and permanent capacity loss. Optimal storage protocol requires keeping cells at 40% to 50% State of Charge (approx. 3.80V per cell) in a cool (15°C) dry environment.
Internal Resistance (ESR) and Voltage Sag Under Load
Every real battery cell exhibits internal Equivalent Series Resistance (ESR). When a high-current load draws power from the cell, internal resistance produces an instantaneous voltage drop (Voltage Sag = I × ESR). If voltage sag causes cell terminal voltage to dip below the low-voltage cutoff threshold of the device protection circuit (typically 3.0V for Li-ion), the device will abruptly shut down even when significant chemical energy remains in the battery.
Active Cell Balancing in High-Voltage Battery Packs
Electric vehicle battery management systems utilize active capacitive and inductive cell balancing circuits to shuttle energy from higher-voltage cells to weaker adjacent cells, maximizing total usable pack energy capacity.