Battery Runtime Estimator
Estimate runtime based on load type, internal resistance, temperature, and capacity adjustments.
Tool Purpose & README
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Inputs
Choose a chemistry preset, then set pack or cell specs. Use the load tab to define current, power, or resistance, and refine runtime with environment and degradation factors.
Enter parameters and click Calculate to estimate runtime.
Discharge Curve (Placeholder)
Battery Runtime Estimation
This tool estimates the runtime of a battery pack under specified load conditions, accounting for internal resistance losses, temperature effects, capacity degradation, and the nonlinear behavior captured by Peukert's law.
The model uses a constant nominal open-circuit voltage with a lumped internal resistance to approximate the loaded terminal voltage. While real battery discharge curves are nonlinear, this simplified approach provides practical estimates for initial design and feasibility studies.
Key Capabilities
- Multiple load types: Constant current, constant power, and constant resistance loads
- Cell-to-pack aggregation: Derive pack parameters from individual cell specs
- Temperature correction: Adjust capacity based on ambient temperature deviation
- Peukert effect: Model capacity reduction at high discharge rates
- Degradation modeling: Account for state-of-health and depth-of-discharge limits
- Efficiency losses: Include converter/regulator efficiency in power calculations
Model Assumptions
- The open-circuit voltage remains constant throughout discharge (nominal voltage approximation)
- Internal resistance is constant and does not vary with state-of-charge or temperature
- Temperature effects are linear around the reference temperature
- Duty cycle averaging accurately represents intermittent loads
- All cells in the pack are identical and balanced
When to Use This Tool
This estimator is ideal for preliminary sizing, feasibility studies, and comparative analysis between battery chemistries or configurations. For detailed design validation, always verify results against manufacturer discharge curves and, where possible, empirical testing.
Parameter Glossary
Complete reference for all input parameters and output values used in the estimator.
Pack Configuration
chemistryuse_cell_specspack_nominal_voltage_vpack_capacity_ahpack_internal_resistance_ohmpack_cutoff_voltage_vCell Configuration
series_cellsparallel_cellscell_nominal_voltage_vcell_capacity_ahcell_internal_resistance_ohmcell_cutoff_voltage_vLoad Parameters
load_typeload_current_aload_power_wload_resistance_ohmconverter_efficiencyduty_cycleEnvironment & Degradation
ambient_temperature_creference_temperature_ccapacity_temp_coeff_per_cpeukert_exponentreference_current_adepth_of_dischargestate_of_healthOutput Values
runtime_hours, runtime_minuteseffective_capacity_ahaverage_current_aaverage_power_wenergy_delivered_whloaded_voltage_vvoltage_sag_vc_ratepower_loss_wBattery Fundamentals
The Basic Runtime Equation
At its simplest, battery runtime is capacity divided by current: t = C / I. A 10 Ah battery discharged at 2 A runs for 5 hours. However, real batteries are more complex due to voltage variations, efficiency losses, temperature effects, and rate-dependent capacity.
Open-Circuit Voltage vs. Loaded Voltage
A battery's open-circuit voltage (OCV) is measured with no current flowing. Under load, the terminal voltage drops due to internal resistance:
V_terminal = V_OCV - I * R_internal
This voltage sag reduces available power and causes energy to be dissipated as heat inside the battery. High-power applications require low internal resistance cells.
Internal Resistance
Internal resistance has multiple components: ionic resistance in the electrolyte, charge-transfer resistance at electrode surfaces, and ohmic resistance in current collectors. For simplified modeling, these are lumped into a single DC resistance value.
Internal resistance increases with age and decreases with temperature (within safe operating limits). Cold batteries have higher resistance and more voltage sag.
Series and Parallel Cell Combinations
Battery packs combine cells in series (S) and parallel (P) to achieve desired voltage and capacity:
- Series (S): Increases voltage. V_pack = N_s * V_cell. Resistance adds: R_series = N_s * R_cell.
- Parallel (P): Increases capacity. C_pack = N_p * C_cell. Resistance divides: R_parallel = R_cell / N_p.
- Combined: For a pack with S cells in series and P cells in parallel: R_pack = (N_s / N_p) * R_cell.
Pack notation like "4S2P" means 4 cells in series (voltage x4) with 2 parallel groups (capacity x2).
Peukert's Law
Wilhelm Peukert observed in 1897 that lead-acid batteries deliver less total charge when discharged rapidly. This is expressed as:
C_effective = C_rated * (I_ref / I_actual)^(k-1)
where k is the Peukert exponent (k >= 1). Lead-acid batteries have k = 1.1-1.4; lithium batteries are closer to ideal with k = 1.02-1.10. At 2x the reference current, a battery with k = 1.2 delivers only (0.5)^0.2 = 87% of rated capacity.
Temperature Effects
Battery capacity is temperature-dependent. The electrochemical reactions slow at low temperatures, reducing available capacity. A typical Li-ion cell may lose 10-20% capacity at 0 C compared to 25 C.
The linear approximation used here is:
C_temp = C_rated * [1 + alpha * (T - T_ref)]
This is accurate for moderate deviations (e.g., 0-40 C) but breaks down at extreme temperatures.
State of Health and Cycle Life
Batteries degrade over time and with use. State of Health (SOH) represents the current capacity as a fraction of original capacity. A battery with SOH = 0.80 has lost 20% of its original capacity.
Degradation accelerates with:
- High temperatures (especially when fully charged)
- Deep discharge cycles
- High charge/discharge rates
- Storage at high or very low state-of-charge
Depth of Discharge
Depth of Discharge (DoD) is the fraction of capacity used per cycle. Using 80% of capacity (DoD = 0.80) leaves a 20% buffer. Limiting DoD significantly extends cycle life - a Li-ion cell cycled to 80% DoD may last 2-3x longer than one cycled to 100% DoD.
C-Rate
The C-rate normalizes discharge current to capacity. A 10 Ah battery:
- At 1C (10 A): depletes in 1 hour
- At 2C (20 A): depletes in 30 minutes
- At 0.5C (5 A): depletes in 2 hours
- At C/10 (1 A): depletes in 10 hours
Maximum continuous C-rate is a key cell specification. High-power cells may support 3-5C continuous; high-energy cells may be limited to 1C.
Constant Power Loads
Many modern devices use DC-DC converters that draw constant power regardless of input voltage. As the battery voltage drops, current must increase to maintain power output:
I = P / V
This creates a feedback loop: lower voltage -> higher current -> more voltage sag -> even lower voltage. If internal resistance is too high, the battery cannot deliver the requested power.
Mathematical Model
The following equations define the battery runtime estimation model.
Battery Chemistry Comparison
Different battery chemistries have distinct characteristics that affect runtime, power capability, cycle life, and safety. This comparison helps select the appropriate chemistry for your application.
| Property | Li-ion NMC/NCA | LiPo | LiFePO4 | NiMH | Lead-Acid |
|---|---|---|---|---|---|
| Nominal Voltage | 3.6-3.7 V | 3.7 V | 3.2 V | 1.2 V | 2.0 V |
| Cutoff Voltage | 2.5-3.0 V | 3.0-3.2 V | 2.5 V | 1.0 V | 1.75 V |
| Energy Density | 150-250 Wh/kg | 150-200 Wh/kg | 90-120 Wh/kg | 60-120 Wh/kg | 30-50 Wh/kg |
| Cycle Life | 500-1000 | 300-500 | 2000-5000 | 500-1000 | 200-500 |
| Peukert Exponent | 1.02-1.05 | 1.02-1.04 | 1.03-1.06 | 1.05-1.15 | 1.10-1.30 |
| Temp Coefficient | 0.3-0.5%/C | 0.3-0.4%/C | 0.2-0.4%/C | 0.4-0.6%/C | 0.5-1.0%/C |
| Self-Discharge | 2-3%/month | 3-5%/month | 1-3%/month | 15-30%/month | 3-20%/month |
| Max C-Rate | 1-3C | 3-10C | 1-3C | 1-2C | 0.2-1C |
| Best For | EVs, laptops, power tools | Drones, RC, high-power | Solar storage, EVs, safety-critical | Hybrid vehicles, consumer devices | UPS, SLI, low-cost storage |
Representative Discharge Curves
The shape of the discharge curve varies significantly by chemistry. Flat curves provide stable voltage; sloped curves give better state-of-charge indication.
Li-ion NMC/NCA
LiFePO4
Lead-Acid
NiMH
Chemistry Selection Guidelines
- Maximum energy density: Li-ion NMC/NCA - best for weight/volume constrained applications
- High power bursts: LiPo - drones, RC vehicles, peak power applications
- Long cycle life: LiFePO4 - stationary storage, commercial EVs, where longevity matters
- Safety-critical: LiFePO4 - thermal stability, no thermal runaway risk
- Low cost: Lead-acid - UPS, backup power, automotive starting
- Extreme cold: Lithium with heating or lead-acid (tolerates cold better when charged)
References & Further Reading
Authoritative sources for battery modeling, characterization, and application design.