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Home›Thermodynamics›State of Charge
Process / pipelineBattery Management

State of Charge

State of Charge Estimation for Energy Storage Systems · Also known as: SOC, charge estimation

State of Charge (SOC) is the amount of energy available in a battery or energy storage system, expressed as a percentage of its maximum capacity. Accurate SOC estimation is critical for safe operation: underestimating SOC can cause unsafe discharges, overestimating can cause overcharging. SOC estimation combines current integration (coulomb counting), voltage-based methods, and Kalman filtering to achieve accuracy despite measurement noise and model uncertainties.

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State of Charge
Battery Equivalent Circu…Maximum Power Point Trac…State of Health

When to use it

Use SOC estimation in any battery-powered application: electric vehicles, renewable energy storage systems, portable electronics, and power tools. Essential for safety (preventing overcharge/over-discharge) and performance (maximizing usable energy). Avoid using simple coulomb counting alone in noise-prone environments.

Strengths & limitations

Strengths
  • Kalman filter-based methods are robust to sensor noise and model uncertainties
  • Provides both estimate and confidence bound
  • Can detect and compensate for systematic errors
  • Works with commodity sensors (current, voltage, temperature)
Limitations
  • Requires accurate battery model (OCV-SOC curve, internal resistance)
  • Model parameters change with temperature and aging
  • Convergence can be slow at low discharge rates
  • Faults or failures (sensor stuck, open circuit) can cause large errors

Frequently asked

Why can't I just use a fuel gauge from terminal voltage?

Terminal voltage changes with current (voltage drop across internal resistance) and temperature, so a single voltage measurement doesn't uniquely determine SOC. The relationship V(SOC) is also nonlinear and hysteretic. Combining voltage with integrated current (coulomb counting) provides much better accuracy.

What happens when coulomb counting drifts due to sensor error?

Sensor bias (shunt resistor drift, ADC offset) causes coulomb counting to gradually diverge from true SOC. The Kalman filter detects this as a growing mismatch between predicted and measured voltage, and slowly corrects the SOC estimate. Regular voltage-based corrections prevent long-term drift.

How often should I reinitialize SOC when the battery is fully charged or discharged?

During charging to full capacity or discharging to zero (cutoff), SOC should be set exactly to 100% or 0%. This periodic reinitialization prevents drift accumulation. Some systems use 'fuel cell' discharge to precisely know empty state. In EVs, charger communication can signal when charging is complete.

Sources

  1. Plett, G. L. (2004). Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs. Journal of Power Sources, 134(2), 252-261. DOI: 10.1016/j.jpowsour.2004.02.031 ↗
  2. He, H., Xiong, R., & Fan, J. (2011). Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an extended Kalman filter. Journal of Power Sources, 196(6), 3365-3373. link ↗

How to cite this page

ScholarGate. (2026, June 3). State of Charge Estimation for Energy Storage Systems. ScholarGate. https://scholargate.app/en/thermodynamics/state-of-charge

Related methods

Battery Equivalent Circuit ModelMaximum Power Point TrackingState of Health

Which method?

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Referenced by

Battery Equivalent Circuit ModelMaximum Power Point TrackingState of Health

Similar methods

State of HealthBattery Equivalent Circuit ModelEnergy Storage Dispatch OptimizationSmart Grid State EstimationKalman Filter for Signal TrackingKalman FilterKalman Filter with Measurement ErrorPower System State Estimation

Related reference concepts

SupercapacitorsElectrochemical Energy Storage and ConversionBatteries and Secondary CellsBattery and Electrode MaterialsElectrochemical Impedance SpectroscopyExchange Current and Overpotential

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — State of Charge (State of Charge Estimation for Energy Storage Systems). Retrieved 2026-07-21 from https://scholargate.app/en/thermodynamics/state-of-charge · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Gregory Plett
Subfamily
Battery Management
Year
2004
Type
Estimation algorithm
Related methods
Battery Equivalent Circuit ModelMaximum Power Point TrackingState of Health
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