Battery Life Calculator

How Long Will Your Battery Actually Last?

Battery life seems simple: divide capacity by current draw and you get hours. A 2500 mAh AA battery powering a 50 mA device should last 50 hours. In practice, you will get less. Sometimes much less. The rated capacity on a battery label is measured under specific lab conditions: moderate temperature, low constant discharge rate, and a voltage cutoff that may not match your circuit. Real-world performance depends on temperature, discharge rate, battery age, voltage regulation efficiency, and the Peukert effect, which causes high-drain devices to deplete batteries faster than the simple division predicts.

This calculator gives you both an adjusted estimate (accounting for efficiency losses) and a conservative estimate (70% of rated capacity) so you can plan for worst-case scenarios. For calculating the current draw of an LED circuit, see our LED Resistor Calculator.

What This Calculator Does

This tool estimates battery runtime from four inputs: battery capacity in mAh, battery voltage, device current draw in mA, and system efficiency. It returns the estimated life in hours and days, the usable energy in watt-hours, and a conservative estimate that accounts for real-world conditions. It includes presets for common battery types (AA, AAA, 18650, CR2032, 9V, lead-acid) so you do not have to look up capacity and voltage manually.

• Inputs: Battery capacity (mAh), battery voltage (V), device current draw (mA), system efficiency (%)
• Outputs: Estimated runtime in hours and days, usable energy in Wh, conservative estimate

How the Calculation Works

• Capacity (mAh): The total charge a battery can deliver, measured in milliamp-hours. A 2500 mAh battery can supply 2500 mA for 1 hour, or 50 mA for 50 hours, in theory. In practice, you get less
• Voltage (V): The nominal output voltage. Alkaline cells are 1.5 V, NiMH are 1.2 V, Li-ion are 3.7 V, lead-acid are 2.0 V per cell (12 V for a 6-cell battery). Voltage affects energy calculations but not the basic runtime formula
• Current (mA): The average current your device draws. This is the most important variable. A device that draws 200 mA will deplete a battery 4 times faster than one drawing 50 mA. Measure actual current with a multimeter for accurate results
• Efficiency (%): Accounts for voltage regulator losses (buck/boost converters are 80-95% efficient), Peukert effect (high drain reduces usable capacity), self-discharge, and the fact that manufacturers rate capacity optimistically. Use 80% as a starting point for regulated circuits, 90% for direct battery connection

How to Use the Calculator

1. Click a battery preset to auto-fill capacity and voltage, or enter your own values
2. Enter your device current draw in milliamps (measure with a multimeter for accuracy)
3. Set the efficiency percentage (80% is a good default for regulated circuits)
4. Click Calculate to see estimated runtime, usable energy, and conservative estimate

Example Calculations

Example 1: Arduino Weather Station on AA Batteries

Kevin, a hobbyist in Portland, is building a backyard weather station with an Arduino Pro Mini and a radio transmitter. The system draws 35 mA on average (including sleep modes). He powers it with 4 AA alkaline batteries in series (6 V, 2500 mAh). Using the calculator: hours = 2500 / 35 x 0.80 = 57.1 hours. That is only 2.4 days, which is not enough for an unattended station. He reduces the current to 5 mA by using deep sleep and waking every 10 minutes: hours = 2500 / 5 x 0.80 = 400 hours, about 16.7 days. Better, but still short. He switches to a 18650 Li-ion battery (3000 mAh, 3.7 V) with a buck converter: hours = 3000 / 5 x 0.85 = 510 hours, about 21 days. For the power calculations behind these numbers, use our Watt Calculator.

Example 2: Wireless Mouse Battery Life

Jennifer, a product designer at a peripherals company in San Jose, is estimating battery life for a wireless mouse. The mouse draws 8 mA when active and 0.1 mA in sleep mode. The user is active 4 hours per day, so the average current is (8 x 4 + 0.1 x 20) / 24 = 1.42 mA. She uses two AAA batteries (1000 mAh each, 1.5 V) in series. Hours = 1000 / 1.42 x 0.85 = 598.6 hours. Days = 598.6 / 24 = 24.9 days. That is less than a month, which is not competitive. She reduces active current to 3 mA with a more efficient sensor: average = (3 x 4 + 0.1 x 20) / 24 = 0.58 mA. Hours = 1000 / 0.58 x 0.85 = 1465.5 hours, about 61 days. Two months is acceptable for a wireless mouse.

Example 3: ESP32 IoT Sensor on 18650

Marcus, an IoT developer in Berlin, is deploying a temperature sensor using an ESP32 that sends readings via WiFi every 30 minutes. The ESP32 draws 80 mA during WiFi transmission (lasting 2 seconds) and 10 uA (0.01 mA) in deep sleep. Average current = (80 x 2 + 0.01 x 1798) / 1800 = 0.10 mA. He uses a 3000 mAh 18650 battery at 3.7 V. Hours = 3000 / 0.10 x 0.90 = 27,000 hours, about 1125 days (3.1 years). In practice, the battery self-discharge rate of about 2% per month will deplete the battery before the load does. After 1 year, self-discharge removes about 24% of capacity, leaving about 2280 mAh. At that point, the remaining life is 2280 / 0.10 x 0.90 = 20,520 hours, about 855 days. The sensor will run for about 2 years before needing a recharge, limited by self-discharge rather than load current.

Real-World Scenarios

Solar-Powered Remote Monitoring

Sarah, an environmental scientist in Colorado, is building a remote water level monitor powered by a 12 V lead-acid battery (7 Ah) with a 10 W solar panel. The monitor draws 120 mA continuously. Without solar: hours = 7000 / 120 x 0.85 = 49.6 hours, about 2 days. With solar, the panel provides about 10 W x 5 peak sun hours / 12 V = 4.17 Ah per day. The load consumes 120 mA x 24 h = 2.88 Ah per day. Net daily surplus = 4.17 - 2.88 = 1.29 Ah. The battery acts as a buffer for cloudy days. With 7 Ah capacity and 2.88 Ah daily load, the system can survive about 7 / 2.88 x 0.85 = 2.1 days without any sun. In Colorado, cloudy stretches rarely exceed 3 days, so she adds a second battery for 14 Ah total, giving 4.1 days of autonomy.

RC Car Run Time

David, an RC car enthusiast in Miami, wants to know how long his car will run on a 5000 mAh 7.4 V LiPo pack. The motor draws 25 A (25,000 mA) at full throttle. Hours = 5000 / 25000 x 0.80 = 0.16 hours = 9.6 minutes. But he does not drive at full throttle continuously. His average current is about 8 A during a typical run with acceleration, braking, and cornering. Hours = 5000 / 8000 x 0.80 = 0.5 hours = 30 minutes. The high discharge rate also triggers the Peukert effect, reducing usable capacity by another 10-15%. Realistic runtime: about 25 minutes. This matches his track experience. For high-drain applications, the Peukert effect is significant and the efficiency adjustment should be increased to account for it.

Emergency LED Lighting

Thomas, a building manager in New York, is designing emergency LED lighting for a stairwell. Each LED module draws 150 mA at 12 V (1.8 W). He needs 3 hours of backup power. Battery capacity needed = 150 mA x 3 h / 0.80 = 562.5 mAh. He uses a 12 V sealed lead-acid battery rated at 1.3 Ah (1300 mAh). Hours = 1300 / 150 x 0.85 = 7.4 hours. This provides more than double the required 3 hours, which accounts for battery aging over the 3-5 year service life. He sizes the system for the end-of-life battery capacity (about 80% of new), giving 1300 x 0.80 / 150 x 0.85 = 5.9 hours, still well above the 3-hour requirement.

Common Mistakes to Avoid

• Using rated capacity without derating: Battery labels show capacity under ideal lab conditions. Real-world capacity is typically 70-85% of the label, depending on discharge rate, temperature, and age. Always apply an efficiency factor. A 2500 mAh battery in a high-drain device at 0 degrees C may deliver only 1500 mAh
• Ignoring the Peukert effect: High discharge rates reduce usable capacity. A battery rated at 2500 mAh at 25 mA drain may deliver only 1800 mAh at 500 mA drain. This effect is significant for lead-acid and NiMH batteries and less pronounced for Li-ion. For high-drain devices, reduce efficiency to 60-70%
• Forgetting voltage regulator losses: If your device needs 3.3 V and you have a 12 V battery, the buck converter is 85-95% efficient. The remaining 5-15% is lost as heat. This directly reduces battery life. Enter the regulator efficiency in the efficiency field, or use 80% as a combined default
• Not accounting for self-discharge: All batteries lose charge over time even without a load. Alkaline batteries lose 2-3% per year. NiMH loses 1-4% per day (low-self-discharge variants lose 0.1-0.3% per day). Li-ion loses 2-3% per month. For ultra-low-power devices, self-discharge may dominate the load current
• Using peak current instead of average: A device that draws 500 mA during WiFi transmission and 0.01 mA in sleep does not have a 500 mA current draw. You must calculate the time-weighted average. Measure current in each operating mode and weight by the time spent in that mode

Limitations of This Calculator

This calculator provides an estimate based on average current draw and constant efficiency. It does not model the Peukert effect precisely, temperature effects, battery aging, or variable discharge profiles. Battery capacity varies with temperature: cold reduces capacity significantly (a battery at 0 degrees C may deliver 50-70% of its rated capacity), while high temperatures increase capacity but reduce cycle life. This tool does not account for the battery voltage curve, which means devices with a low voltage cutoff will stop drawing current before the battery is fully depleted. For mission-critical applications, always test with the actual battery and device under expected operating conditions.

Authoritative Research and Resources

• NIST: SI Units for Electric Current - The National Institute of Standards and Technology maintains the official definitions of the ampere, volt, and watt. These units underpin all battery capacity and runtime calculations. NIST also provides reference materials and procedures for battery testing.
• Battery University: Battery Runtime and Capacity - Battery University, maintained by Cadex Electronics, is a widely referenced educational resource on battery technology. Their articles cover Peukert effect, self-discharge, temperature effects, and discharge characteristics for all major battery chemistries including Li-ion, NiMH, and lead-acid.
• US Department of Energy: Battery Basics - The DOE provides educational resources on battery technology, including capacity ratings, discharge characteristics, and energy density comparisons across battery chemistries. Useful for understanding why different battery types behave differently under load.