Battery Runtime Calculator
Battery Runtime Calculator
Enter rated capacity, then select unit: mAh, Ah, or Wh
Lead-acid: 50%. Li-ion: 80%. LiFePO4: 90%.
Account for inverter/DC-DC converter losses (typically 85–95%)
Used for the ProgressRing — how long do you need it to last?
Enter Battery Details
Select a mode, enter your battery capacity and load, then see how long your battery will last — with energy breakdown and scenario comparison.
How long will your battery last?
The Battery Runtime Calculator is a free, instant tool that answers the single most common battery question: how long will it last? Whether you are sizing a backup power system, designing an IoT sensor node, choosing between lead-acid and lithium chemistries, or simply trying to figure out how far your laptop will take you on a cross-country flight, this calculator gives you a practical, accurate estimate in seconds. Most basic runtime calculators use the simplest possible formula — capacity divided by current — and stop there. That estimate ignores three real-world factors that can cut your actual runtime by 30 to 60 percent: Depth of Discharge (DoD), system efficiency losses, and the non-linear Peukert effect in lead-acid batteries. Our calculator incorporates all of these, plus an IoT duty-cycle mode that estimates runtime in days or years for low-power embedded devices. The Standard Mode handles everyday use cases. Enter your battery capacity in mAh, Ah, or Wh; select your load as watts or amps; adjust the Depth of Discharge slider to reflect how deeply you want to cycle the battery; and set the system efficiency to account for inverter or DC-DC converter losses. The calculator instantly shows your runtime, the usable energy in watt-hours, the energy lost to DoD reserve and efficiency, and a scenario comparison table showing how runtime changes at 25%, 50%, 75%, and 100% of your entered load. A ProgressRing charts your result against a user-settable target — useful when you need to verify that a battery will last through an 8-hour shift or a 24-hour deployment. The Peukert Mode is designed for lead-acid battery users. Lead-acid batteries suffer from a well-documented non-linear discharge behavior: drawing current at twice the rated rate does not simply halve the runtime — it reduces runtime by a factor greater than two, described by the Peukert equation. The Peukert exponent varies by chemistry: flooded lead-acid typically ranges from 1.2 to 1.6, AGM from 1.05 to 1.15, Gel from 1.1 to 1.25, and lithium chemistries are nearly ideal at 1.01 to 1.04. Enter your battery's rated capacity, the actual discharge current, the rated hour (C-rate base, usually 20 hours), and the Peukert exponent. The calculator computes the Peukert-corrected runtime alongside the uncorrected estimate so you can see exactly how much capacity is lost to high-rate discharge. The IoT / Duty-Cycle Mode addresses the unique needs of embedded system designers and makers working with microcontrollers, ESP32 or Arduino boards, wireless sensors, and remote monitoring devices. These devices alternate between an active (transmitting or processing) state drawing tens or hundreds of milliamps, and a deep-sleep state drawing just microamps. By modeling both states and the fraction of time spent in each, the calculator computes a weighted average current draw and projects runtime in hours, days, and years — the timescales that actually matter for a field-deployed sensor. Chemistry presets (Li-ion, LiFePO4, Lead Acid AGM, Gel, Flooded, NiMH) auto-populate the DoD, efficiency, and Peukert exponent fields based on the typical characteristics of each technology. Device load presets (Smartphone, Tablet, Laptop, LED Bulb, Fan, Router, Raspberry Pi) quickly fill the load field with representative wattage values. An optional 15% aging deration checkbox applies a conservative capacity reduction to account for battery aging — particularly useful when estimating runtime for a battery that has already completed several hundred charge cycles. All calculations run entirely in your browser with no data sent to any server. Results update instantly as you change any input, so you can explore different scenarios interactively.
Understanding Battery Runtime
What Is Battery Runtime?
Battery runtime is the duration a battery can supply power to a load before its voltage drops below the device's minimum operating threshold. It is not simply capacity divided by current — three key factors reduce the theoretical runtime in practice. First, Depth of Discharge (DoD) limits how much of the rated capacity you actually use: lithium batteries are commonly discharged to 80% DoD, while lead-acid batteries are often limited to 50% DoD to preserve cycle life. Second, system efficiency accounts for energy lost in DC-DC converters, inverters, wiring resistance, and internal battery resistance — typically 85–95% for well-designed systems. Third, the Peukert effect (most relevant for lead-acid) means high discharge rates yield less usable energy than the rated Ah figure suggests. Accounting for all three factors gives a significantly more accurate runtime estimate than the naive calculation.
How Is It Calculated?
The standard runtime formula is: Runtime (h) = (Capacity_Wh × DoD × Efficiency) / Load_W. In current mode, it becomes: Runtime (h) = (Capacity_Ah × DoD × Efficiency) / Load_A. For Peukert's Law (lead-acid non-linear discharge), the BatteryGuy form is used: t = H × (C / (I × H))^n, where H is the rated hour (e.g., 20), C is rated capacity in Ah, I is actual discharge current in A, and n is the Peukert exponent. For IoT duty-cycle estimation, the weighted average current is: Avg_mA = Active_mA × (active_pct / 100) + Sleep_mA × (1 − active_pct / 100), and Runtime_h = (Capacity_mAh × DoD) / Avg_mA. Days and years are derived by dividing hours by 24 and 8,760 respectively. The C-rate (discharge current as a fraction of capacity) is also computed to indicate how aggressively the battery is being discharged.
Why Does Runtime Estimation Matter?
Accurate battery runtime estimation has practical consequences across many domains. For off-grid solar installations and UPS systems, undersizing the battery bank means blackouts; oversizing wastes money. For IoT deployments, accurately projecting battery life in the field determines service intervals and total cost of ownership — a sensor that needs battery replacement every 6 months instead of every 2 years requires four times as many maintenance visits. For lead-acid battery users in electric vehicles, forklifts, and marine applications, understanding the Peukert effect prevents over-discharge that permanently reduces battery capacity and lifespan. For consumer electronics, a quick runtime check confirms whether a power bank is adequately sized for a camping trip or international flight. Understanding DoD also directly impacts battery longevity: lithium cells kept between 20% and 80% state of charge can last 3–5 times longer than cells regularly cycled from 0% to 100%.
Limitations and Accuracy Notes
This calculator provides theoretical estimates based on the inputs provided and standard models. Several real-world factors can significantly affect actual runtime. Temperature is a major variable: at 0°C, lithium-ion batteries typically deliver 70–80% of their rated capacity; at −20°C this can drop to 50% or less. Conversely, high temperatures accelerate self-discharge and chemical degradation. Battery age progressively reduces available capacity — a battery at end-of-life may deliver only 70–80% of its original rated capacity. Self-discharge matters for devices left in storage: NiMH loses 1–3% per day at room temperature, while lithium loses roughly 0.5–1% per month. The Peukert equation is an empirical approximation and is most accurate for flooded lead-acid batteries in the middle of their discharge range; it becomes less accurate near full charge and near cutoff voltage. Variable loads (motors, transmitters, displays) draw current unevenly, while this calculator assumes a constant load. For critical applications, add a 20–30% safety margin to the calculated runtime.
Battery Runtime Formulas
Basic Runtime (Watt-hours)
Runtime (h) = Capacity (Wh) / Load (W)
The simplest runtime estimate — divide the battery's energy capacity in watt-hours by the power draw in watts. Does not account for DoD, efficiency, or Peukert effect.
Runtime with DoD and Efficiency
Runtime (h) = (Capacity × DoD × Efficiency) / Load
A more realistic estimate that accounts for depth of discharge (how much capacity you actually use) and system efficiency losses from inverters or DC-DC converters.
Amp-hour Runtime
Runtime (h) = (Ah × DoD × Efficiency) / Load (A)
When capacity is in amp-hours and load is in amps, divide directly. Useful for 12V/24V/48V systems where loads are specified as current draw.
Peukert's Law
t = H × (C / (I × H))ⁿ
Models non-linear discharge in lead-acid batteries. H is rated hour (e.g., 20h), C is rated capacity in Ah, I is actual discharge current, and n is the Peukert exponent (1.1–1.6 for lead-acid).
Battery Reference Tables
Common Battery Capacities
Typical battery capacities for popular devices and systems, with nominal voltage and energy in watt-hours.
| Device/System | Typical Capacity | Voltage | Energy (Wh) |
|---|---|---|---|
| Smartphone | 3,000–5,000 mAh | 3.7 V | 11–19 Wh |
| Tablet | 7,000–10,000 mAh | 3.7 V | 26–37 Wh |
| Laptop | 50–100 Wh | 11.1–14.8 V | 50–100 Wh |
| Power Bank (small) | 10,000 mAh | 3.7 V | 37 Wh |
| Power Bank (large) | 26,800 mAh | 3.7 V | 99 Wh |
| UPS (home office) | 12V 7–9 Ah | 12 V | 84–108 Wh |
| Solar Battery (LiFePO4) | 100 Ah | 12.8 V | 1,280 Wh |
| Car Battery | 50–80 Ah | 12 V | 600–960 Wh |
Typical Device Power Draws
Average power consumption for common devices to help estimate battery runtime.
| Device | Idle/Sleep (W) | Typical Use (W) | Peak/Heavy (W) |
|---|---|---|---|
| Smartphone (screen on) | 0.5 | 2–3 | 5–8 |
| Laptop (office work) | 5–8 | 15–30 | 45–65 |
| LED Bulb (10W) | — | 10 | 10 |
| Wi-Fi Router | 5 | 8–12 | 15 |
| Raspberry Pi 4 | 2.7 | 3.5–5 | 6.5 |
| 32" LED TV | 20 | 30–40 | 50 |
| Mini Fridge | 30 | 50–70 | 90 |
| CPAP Machine | 15 | 30–60 | 80 |
Worked Examples
Power Bank Runtime for Phone Charging
A 10,000 mAh power bank (3.7V cells) charges a phone at 10W. Assume 85% efficiency for the DC-DC conversion and 100% DoD.
Convert capacity to Wh: 10,000 mAh × 3.7 V / 1000 = 37 Wh
Apply efficiency: Usable energy = 37 Wh × 0.85 = 31.45 Wh
Calculate runtime: 31.45 Wh / 10 W = 3.15 hours
In practice: This delivers about 1.5–2 full phone charges (phones have ~15 Wh batteries)
The 10,000 mAh power bank provides approximately 3.15 hours of continuous 10W charging, accounting for 85% conversion efficiency. This is enough for roughly 1.5 to 2 full smartphone charges.
UPS Runtime for 500W Desktop Load
A home UPS has two 12V 9Ah batteries in series (24V system). The load is a desktop computer drawing 500W. System efficiency is 90%, and DoD is limited to 50% to protect the lead-acid batteries.
Total energy: 2 × 12V × 9Ah = 216 Wh
Apply DoD: 216 Wh × 0.50 = 108 Wh usable
Apply efficiency: 108 Wh × 0.90 = 97.2 Wh delivered to load
Runtime: 97.2 Wh / 500 W = 0.194 hours = 11.7 minutes
The UPS provides approximately 11.7 minutes of runtime for a 500W desktop load. This is enough time to save work and perform a graceful shutdown, but not for extended operation.
IoT Sensor Battery Life (ESP32)
An ESP32 sensor node runs on a 2,000 mAh LiPo battery. It wakes every 15 minutes, transmits for 3 seconds (drawing 240 mA), then sleeps at 10 µA. DoD is 80%.
Active duty cycle: 3 s / (15 × 60 s) = 0.33%
Average current: (240 mA × 0.0033) + (0.01 mA × 0.9967) = 0.792 + 0.010 = 0.802 mA
Usable capacity: 2,000 mAh × 0.80 DoD = 1,600 mAh
Runtime: 1,600 mAh / 0.802 mA = 1,995 hours = 83.1 days = 2.7 months
The ESP32 sensor node will run for approximately 83 days (2.7 months) on a 2,000 mAh battery with a 15-minute wake interval. To achieve 1+ year runtime, reduce wake frequency to once per hour or use a larger battery.
How to Use the Battery Runtime Calculator
Choose Your Mode
Select Standard for everyday batteries (phone, laptop, power bank, UPS), Peukert for lead-acid batteries (car, marine, solar), or IoT / Duty Cycle for microcontrollers and embedded sensors like ESP32 or Arduino.
Enter Battery and Load Values
In Standard mode, enter your battery capacity (mAh, Ah, or Wh) and your device load (W or A). Use the chemistry preset buttons to auto-fill DoD and efficiency for your battery type. Use device presets to quickly set common load values.
Adjust DoD and Efficiency
Slide the Depth of Discharge to reflect how deeply you plan to cycle the battery — 50% for flooded lead-acid, 80% for Li-ion, 90% for LiFePO4. Adjust efficiency for your inverter or DC-DC converter losses (typically 85–95%).
Read Results and Compare Scenarios
The hero value shows your runtime in hours (or days/years for IoT). The energy breakdown bar shows usable energy vs. DoD reserve vs. efficiency loss. The scenario table compares runtime at 25%, 50%, 75%, and 100% of your entered load so you can plan for different usage intensities.
Frequently Asked Questions
Why does my actual battery runtime differ from the calculated estimate?
Several real-world factors reduce actual runtime below the theoretical estimate. Temperature is the biggest variable — cold weather (below 0°C) can reduce lithium battery capacity by 20–50%, and lead-acid performance degrades even faster. Battery age also plays a major role: a battery at 200 cycles may deliver only 80% of its original capacity. Peukert effect in lead-acid batteries means high discharge rates reduce available capacity significantly. Variable loads (motors, backlights, radios) cause current spikes that the calculator cannot model. For safety margins, add 20–30% extra capacity over the calculated runtime requirement when sizing a battery for critical applications.
What is Depth of Discharge (DoD) and why does it matter?
Depth of Discharge (DoD) is the percentage of a battery's rated capacity that is discharged before recharging. Using more of a battery's capacity per cycle reduces its total cycle life significantly. Lead-acid batteries discharged below 50% DoD can suffer permanent sulfation damage and may lose 30–50% of their total cycle life. Lithium-ion batteries are more tolerant but still benefit from shallower cycles — keeping lithium cells between 20% and 80% state of charge can extend cycle life from 500 cycles to over 1,500 cycles. LiFePO4 batteries are the most tolerant and are commonly discharged to 90% DoD without significant cycle life penalties.
When should I use Peukert mode vs. Standard mode?
Use Peukert mode for flooded lead-acid, AGM, or gel batteries, especially when the discharge current is high relative to the battery's rated capacity (C-rate above 0.1C). The Peukert effect is most pronounced for flooded lead-acid batteries discharging at 0.2C or higher — for example, a 100Ah battery at 20A (0.2C). At this rate, the actual runtime can be 20–30% shorter than simple division predicts. For lithium-ion and LiFePO4 batteries, the Peukert exponent is so close to 1.0 that the correction is negligible, and Standard mode is perfectly adequate. AGM and Gel fall between these extremes.
How do I estimate runtime for an ESP32 or Arduino IoT sensor?
Use IoT / Duty Cycle mode. Measure or look up your device's active current (ESP32 during Wi-Fi transmission draws about 240 mA; during CPU-active processing about 50–80 mA). Enter the deep sleep current (ESP32 deep sleep draws about 10 µA = 0.01 mA). Set the active time percentage — for a sensor that wakes every 10 minutes and takes 5 seconds to transmit, the active fraction is 5 / (10×60) = 0.8%. Enter your battery capacity in mAh. The calculator computes weighted average current and projects runtime in days or years. A 2,000 mAh battery powering an ESP32 at 0.8% duty cycle with 0.01 mA sleep current can last well over a year.
What does the C-rate mean in the results?
C-rate is the discharge current expressed as a multiple of the battery's rated capacity. A 100 Ah battery discharged at 10 A has a C-rate of 0.1C — meaning it would discharge in 10 hours at that rate. A C-rate of 1C would discharge the same battery in 1 hour (100 A). C-rate matters because high C-rates cause greater internal heating, accelerated aging, and (for lead-acid) stronger Peukert effect. Lithium batteries can typically handle 1C to 2C continuous discharge without performance issues. Lead-acid batteries are most efficient at low C-rates (0.05C to 0.1C). Very high C-rates (above 1C for lead-acid) significantly reduce delivered capacity and should be avoided for longevity.
What is the 15% aging deration option?
The aging deration checkbox applies a 15% reduction to your entered battery capacity before calculating runtime. This accounts for capacity fade in batteries that have completed many charge-discharge cycles. A new 100 Ah battery might deliver 98 Ah in practice, but after 500 cycles it may only deliver 80 Ah or less. The 15% deration is a conservative mid-life estimate — appropriate for batteries with 200–500 cycles, or batteries of unknown age. For new batteries, leave this unchecked. For batteries approaching end of life (typically defined as 80% of original capacity), you may want to apply a larger manual deration by simply reducing the capacity value you enter.
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