What Is Battery State of Health (SOH)?
Learn what battery SOH means, how to calculate it, and how BMS estimates battery health for energy storage systems.
A lithium-ion battery can reach 100% state of charge (SOC) without storing as much energy as it did when new. This is because SOC describes the current charge level, while State of Health (SOH) measures battery condition relative to a defined reference state.Battery State of Health (SOH) is commonly expressed as a percentage and used to evaluate changes in capacity, power capability, and usable energy as a battery ages. For battery energy storage systems (BESS), SOH helps operators assess degradation, monitor performance, and plan maintenance.
Battery management systems (BMS) estimate SOH using electrical measurements, operating history, and estimation algorithms. Understanding these methods is essential for interpreting battery health data and evaluating long-term storage performance.
What Is Battery State of Health (SOH)?
Battery State of Health (SOH) describes the current condition of a battery compared with a defined reference condition, usually its beginning-of-life state. A value of 100% represents the selected reference condition, while a lower value indicates degradation according to the chosen health indicator.
SOH is not a single physical quantity measured directly by one sensor. It can be evaluated through capacity, power, energy, and internal resistance, with different indicators describing different aspects of battery performance.
Different Approaches to Evaluating Battery SOH
Different battery SOH indicators including capacity, power, energy, and internal resistance
| SOH Evaluation Approach | Main Indicator | What It Evaluates |
|---|
| Capacity-Based SOH | Capacity (Ah) | Remaining charge capacity relative to a reference |
| Power-Based SOH | Power (W or kW) | Ability to deliver or accept power |
| Energy-Based SOH | Energy (Wh or kWh) | Usable energy relative to a reference |
| Resistance-Based SOH | Internal resistance (Ω) | Changes in electrical resistance associated with aging |
Capacity-Based SOH measures how much charge a battery can deliver compared with its reference capacity. It is commonly used to quantify capacity degradation.
Power-Based SOH evaluates the battery's ability to deliver or accept power under specified conditions. Increased internal resistance can cause greater voltage drops under load, limiting power capability even when substantial capacity remains.
Energy-Based SOH compares usable energy with a defined reference value. It is particularly relevant to energy storage applications, where the amount of energy available for charging and discharging affects system operation.
Resistance-Based SOH evaluates changes in internal resistance relative to a baseline or degradation threshold. Higher resistance generally indicates deterioration, but resistance growth does not translate directly into an equivalent percentage of capacity loss.
These indicators are related but not interchangeable. A battery may retain relatively high capacity while experiencing reduced power capability, or show different usable energy depending on its voltage limits and operating conditions.
How Is Battery SOH Calculated?
Battery SOH calculation using lithium-ion battery capacity testing
A common method is capacity-based SOH, which compares current measured capacity with a defined reference capacity.
SOH_C (%) = (Current Measured Capacity / Reference Capacity) × 100%
Where:
Current Measured Capacity is the charge the battery can deliver under specified test conditions.
Reference Capacity is the original or designated capacity used as the comparison baseline.
SOH_C represents capacity-based State of Health.
For example, a lithium battery with a reference capacity of 100 Ah delivers 85 Ah during a controlled capacity test.
SOH_C = (85 Ah / 100 Ah) × 100% = 85%
The battery therefore has a capacity-based SOH of 85%.
The reference capacity matters because rated capacity and beginning-of-life measured capacity are not necessarily identical. If a battery initially delivers 104 Ah under controlled test conditions, a later measurement of 88 Ah produces the following result:
SOH_C = (88 Ah / 104 Ah) × 100% = 84.6%
The same battery measurement can therefore produce different SOH values when different reference capacities are used.
For meaningful comparisons, capacity tests should maintain consistent conditions:
Using the same nominal discharge current is not sufficient if starting conditions or cutoff voltage differ. Otherwise, measured capacity differences may reflect test conditions rather than permanent degradation.
Resistance-Based SOH
Battery aging can change internal electrochemical characteristics, causing internal resistance to increase. Higher resistance produces greater voltage drops under load and can increase resistive heat generation.
Resistance-based estimation evaluates this change relative to a defined baseline or threshold. It provides information about power capability and electrical degradation that capacity-based SOH alone may not capture.
The two indicators should not be treated as equivalent. A battery can experience significant resistance growth without an identical percentage reduction in capacity, and their relationship depends on battery chemistry, design, and operating conditions.
SOH vs. SOC vs. RUL: What Are the Differences?
State of Health (SOH), State of Charge (SOC), and Remaining Useful Life (RUL) describe different aspects of battery condition.
| Indicator | Full Name | What It Describes | Main Application |
|---|
| SOC | State of Charge | Current charge level relative to available capacity | Monitoring remaining charge |
| SOH | State of Health | Battery condition relative to a reference state | Evaluating degradation |
| RUL | Remaining Useful Life | Estimated operating life before a defined EOL condition | Predicting replacement needs |
SOC answers how much charge is currently available. SOH indicates how the battery's condition has changed, while RUL estimates how much longer it may remain suitable for a particular application.
For example, a battery that originally had a capacity of 100 Ah but now provides 80 Ah may still reach 100% SOC. However, its maximum available charge capacity has declined to approximately 80 Ah under comparable test conditions.
RUL cannot be calculated directly from SOH alone. Its prediction also depends on degradation history, expected future operating conditions, and the end-of-life criteria selected for the application.
What Causes Battery SOH to Decline?
Lithium-ion battery degradation results from chemical and physical changes inside the cells. Calendar aging and cycle aging are the two main categories, and they can occur simultaneously.
Calendar Aging
Calendar aging occurs over time, even when a battery is not actively charging or discharging.
Its main contributing factors include:
Storage temperature: Elevated temperatures accelerate unwanted chemical reactions inside battery cells.
Storage SOC: Prolonged storage at high SOC can accelerate degradation under certain battery chemistries and conditions.
Electrolyte side reactions: These reactions can consume active lithium and change electrode characteristics.
SEI layer growth: Continued growth of the solid electrolyte interphase (SEI) layer consumes cyclable lithium and can contribute to capacity loss and increased internal resistance.
Calendar aging matters in energy storage installations because batteries remain connected to systems for years, including periods of low utilization. Limited cycling does not prevent degradation during standby or storage.
Cycle Aging
Cycle aging results from repeated charging and discharging. Lithium-ion movement between the positive and negative electrodes creates electrochemical and mechanical stress that can gradually reduce battery performance.
Important operating factors include:
Depth of Discharge (DoD): Deeper discharge cycles can increase degradation depending on battery chemistry and operating conditions.
Charge and discharge rates: High C-rates can increase heat generation and electrochemical stress.
Operating temperature: Excessive heat and unsuitable low-temperature charging conditions can accelerate degradation.
Charging limits: Charging outside manufacturer-specified limits can contribute to permanent capacity loss and other forms of battery damage.
For example, charging a lithium-ion battery at high current under unsuitable low-temperature conditions may promote lithium plating on the negative electrode. This consumes active lithium, reduces capacity, and can create additional safety concerns.
The impact of these factors varies with battery chemistry, electrode materials, cell design, and thermal management.
Internal Resistance Growth
Lithium-ion battery degradation mechanisms affecting battery state of health
Internal resistance affects voltage stability, power delivery, and heat generation.
When resistance increases, a battery experiences a greater voltage drop under load. Resistive power loss can be approximated as:
P_loss = I² × R
Where:
At the same current, higher resistance produces greater power loss and heat generation. This can restrict charging and discharging performance in applications with demanding power requirements.
Resistance growth and capacity fade remain separate degradation indicators. A battery may retain considerable charge capacity while experiencing reduced power capability.
How Does a BMS Estimate Battery SOH?
A Battery Management System (BMS) monitors battery operation and helps maintain performance within defined electrical and thermal limits. Common functions include voltage, current, and temperature monitoring, charge-discharge management, cell balancing where supported, and protection against abnormal operating conditions.
For systems with SOH estimation capabilities, the BMS uses measurable battery characteristics and operating history to estimate degradation. SOH itself is not directly measured by a single sensor.
Battery Parameters Used for SOH Estimation
| Parameter | Role in SOH Estimation |
|---|
| Voltage | Identifies cell behavior and voltage changes during operation |
| Current | Tracks charging and discharging behavior |
| Temperature | Accounts for temperature-dependent performance and aging |
| Available Capacity | Provides a basis for capacity-based health assessment |
| Internal Resistance | Indicates changes in power delivery and electrical losses |
| Impedance | Provides information about electrochemical characteristics |
| Charge Throughput | Tracks cumulative charge transferred |
| Operating History | Records cycling and environmental conditions |
Voltage, current, and temperature are common BMS measurement inputs. Available capacity, internal resistance, and impedance may require dedicated tests, additional measurements, or estimation models.
The parameters available depend on battery chemistry, sensor configuration, BMS architecture, and algorithm design.
How SOH Estimation Works
A typical estimation process has three stages:
1. Data Collection
The BMS collects cell voltage, current, and temperature data. Historical charging and discharging records provide additional information about operating conditions and battery behavior.
2. Model-Based or Data-Driven Analysis
The collected data is processed using mathematical battery models, estimation algorithms, or trained data-driven models. These methods identify changes in capacity, resistance, impedance, and other characteristics associated with aging.
3. SOH Estimation and Updating
The algorithm calculates a health indicator relative to the selected reference condition. The estimate can then support degradation tracking and maintenance decisions.
Not every BMS provides a user-facing SOH value. Some focus on protection and basic battery management, while advanced configurations may include online health estimation.
Factors Affecting SOH Estimation Accuracy
An estimated SOH value may differ from the result of an independent capacity test. Important factors include:
Sensor accuracy: Current, voltage, and temperature measurement errors affect model inputs.
Battery model quality: Simplified models may not capture all electrochemical behavior.
Operating conditions: Temperature, load changes, and irregular charging patterns influence estimation.
Reference conditions: Different capacity or resistance baselines produce different SOH values.
Training data quality: Data-driven models may perform poorly on batteries or operating conditions outside their training datasets.
Cell variation: Differences between individual cells complicate pack-level estimation.
SOH should therefore be interpreted together with its estimation method, reference conditions, and operating history rather than as an isolated percentage.
How Are Battery SOH Estimation Methods Classified?
Battery SOH estimation methods generally include measurement and analysis, filter-based and model-based estimation, and data-driven approaches. Hybrid methods combine two or more techniques.
Measurement and Analysis Methods
These methods evaluate measurable battery characteristics to identify changes associated with aging.
Capacity Measurement
A controlled charge-discharge test measures the amount of charge a battery can deliver. Comparing this value with reference capacity provides a direct basis for capacity-based SOH.
Internal Resistance Measurement
Resistance testing evaluates the battery's voltage response to current flow. Changes can indicate electrical degradation and reduced power capability.
Electrochemical Impedance Spectroscopy (EIS)
EIS applies small electrical signals over a range of frequencies and analyzes the resulting impedance response. Changes in impedance characteristics provide information about internal electrochemical processes and battery aging.
Incremental Capacity Analysis (ICA)
ICA analyzes changes in the incremental capacity curve during charging. Characteristic curve features can help identify battery degradation.
Coulomb Counting
Coulomb counting integrates current over time to estimate the amount of charge transferred into or out of a battery. With suitable initial conditions, charge-discharge boundaries, and capacity references, it can support capacity-based SOH estimation.
These methods provide different information. Capacity testing evaluates charge retention, while resistance and impedance analysis provide additional insight into electrical and electrochemical characteristics. Results depend on test conditions and measurement accuracy.
Filter-Based and Model-Based Estimation
Model-based methods combine mathematical representations of battery behavior with measured operating data. Filter-based algorithms update state estimates as new measurements become available.
Common approaches include:
Kalman Filter (KF): Uses a mathematical model and measurement updates to estimate battery states.
Extended Kalman Filter (EKF): Handles nonlinear battery models through local linearization.
Unscented Kalman Filter (UKF): Uses representative sigma points to estimate nonlinear system behavior.
Particle Filter (PF): Uses weighted particles to represent probability distributions in nonlinear or non-Gaussian systems.
Some algorithms estimate SOC, SOH, and battery model parameters together. Dual estimation approaches can update battery states and model parameters simultaneously.
These methods support dynamic estimation but depend on model accuracy, parameter identification, noise assumptions, and computational resources.
Data-Driven Methods
Data-driven methods learn relationships between battery operating characteristics and degradation from historical data rather than relying entirely on predefined physical models.
Common techniques include:
Support Vector Machine (SVM): Classifies battery condition based on learned patterns.
Support Vector Regression (SVR): Predicts continuous values such as SOH.
Gaussian Process Regression (GPR): Produces predictions using probabilistic relationships in training data.
Neural Networks: Learn complex nonlinear relationships between battery operating characteristics and degradation.
These methods can identify complex aging patterns, but prediction quality depends on representative training data. Differences in battery chemistry, cell manufacturing, temperature, and cycling profiles can reduce accuracy when a model is applied outside its original training conditions.
Hybrid Estimation Methods
Hybrid methods combine physical battery models, filtering algorithms, or machine learning techniques.
For example, a physical model can represent battery behavior while a data-driven component identifies complex patterns or compensates for model errors. Other combinations use filtering algorithms and machine learning to improve state tracking and degradation prediction.
Hybrid methods offer flexibility but require additional model integration, data validation, and computational resources.
Comparison of SOH Estimation Methods
| Method | Main Inputs | Advantages | Limitations |
|---|
| Measurement and Analysis | Capacity, resistance, impedance, charging curves | Uses measurable battery characteristics | May require controlled tests and suitable equipment |
| Filter-Based and Model-Based | Voltage, current, battery models | Supports dynamic state estimation | Depends on model quality and algorithm design |
| Data-Driven | Historical operating data | Captures complex nonlinear relationships | Requires representative training data |
| Hybrid | Physical models, measurements, historical data | Combines complementary approaches | Increases integration and validation complexity |
No single method is suitable for every battery application. Selection depends on battery chemistry, available data, computational resources, monitoring requirements, and the intended use of the SOH estimate.
How Is Battery SOH Measured?
SOH is generally estimated rather than directly measured. Controlled tests provide capacity, resistance, and impedance data, while BMS-based online estimation tracks battery health during normal operation.
The two approaches serve different purposes:
Reference testing: Uses controlled conditions to obtain measured battery characteristics and evaluate health.
Online estimation: Uses operating data and algorithms to track degradation without requiring a complete capacity test each time.
Controlled Capacity Testing
A controlled capacity test is one of the most direct ways to determine capacity-based SOH.
The general procedure involves:
Charging the battery according to the manufacturer's instructions.
Completing required charging and cell-balancing processes.
Confirming battery temperature and test conditions.
Connecting a controlled electrical load.
Measuring discharged capacity in amp-hours (Ah).
Stopping at the specified discharge cutoff.
Comparing measured capacity with the reference value.
For meaningful comparisons, temperature, discharge rate, starting SOC, charging endpoint, and cutoff voltage should remain consistent.
A full capacity test may take a battery out of normal service. Large-scale storage systems should follow manufacturer procedures and applicable safety requirements.
Internal Resistance and Impedance Testing
DC internal resistance testing typically applies a current change or pulse and measures the resulting voltage response. This provides resistance information under specified test conditions.
EIS examines impedance across multiple frequencies and provides additional information about electrochemical characteristics.
Neither method directly determines remaining amp-hour capacity. Instead, they complement capacity testing by evaluating electrical and electrochemical changes associated with aging.
BMS-Based SOH Monitoring
A BMS with suitable estimation functions can track SOH during normal battery operation. This reduces the need for frequent full capacity tests and helps operators monitor degradation trends.
However, a BMS-based value remains an estimate. Its reliability depends on algorithm design, sensor accuracy, available operating data, and whether operating conditions provide sufficient information for the model to update its estimates.
For important maintenance or warranty decisions, BMS estimates may need to be evaluated alongside independent testing and manufacturer requirements.
How Does Battery SOH Affect Energy Storage Systems?
In battery energy storage systems, SOH helps operators evaluate changes in available capacity, power delivery, and long-term system operation.
Available Energy and Capacity Planning
As battery capacity declines, the amount of energy available for charging and discharging may also decrease. In a solar-plus-storage system, this affects how much excess solar generation can be stored and later supplied to building loads.
System designers should account for expected degradation, usable SOC windows, conversion losses, operating limits, and reserve requirements when evaluating long-term energy needs.
For residential applications, a stackable all-in-one energy storage system offers modular battery capacity configurations that can be selected according to household consumption and backup requirements. Capacity-based SOH remains an important input, but it does not independently determine the energy available at the system level.
Practical SOH Example for a Battery Energy Storage System
Consider a battery energy storage system with a reference usable energy capacity of 100 kWh. After a period of operation, a controlled capacity test measures 85 kWh under comparable test conditions.
The capacity-based SOH is:
SOH = (85 kWh / 100 kWh) × 100% = 85%
The battery has retained approximately 85% of its reference energy capacity, representing a 15% reduction.
However, 85 kWh of measured battery energy does not necessarily mean the connected load can receive 85 kWh of electricity. Deliverable AC energy also depends on the permitted SOC window, conversion efficiency, auxiliary consumption, discharge limits, and other system losses.
Energy measured at the battery DC terminals is therefore not necessarily equal to energy delivered at the inverter AC output.
Power Capability and System Operation
Increasing internal resistance can cause greater voltage drops and heat generation under high-current conditions. This may limit the charging or discharging power available within the battery's operating limits.
BMS protection functions and system control strategies help maintain electrical and thermal limits. Depending on system architecture, SOH information may also support adjustments to operating limits and power scheduling.
A battery can retain considerable energy capacity while having reduced power capability. In larger commercial and industrial projects, a containerized liquid-cooled energy storage system integrates BMS and EMS functions with liquid-cooled thermal management to support coordinated system operation.
Cell, Module, and Battery Rack Health
Individual cells and modules in a battery system do not necessarily age at the same rate.
For series-connected cells, a weaker cell may reach its upper or lower voltage limit before the others, restricting the usable operating range of the entire series string. In systems with multiple racks or clusters, differences in battery condition can also contribute to uneven performance.
However, cell voltage imbalance does not directly establish a difference in SOH. It can also result from SOC variation, internal resistance differences, temperature variation, or other operating conditions.
Pack-level SOH is more complex than simply averaging individual cell SOH values. Battery topology, cell consistency, the selected health indicator, and system operating limits all influence the overall assessment.
In modular storage configurations, understanding the relationship between individual cells, battery modules, and the complete system is also important when selecting equipment such as a rack-mounted LiFePO4 battery.
Maintenance and Lifecycle Planning
Tracking SOH over time helps identify persistent performance changes that may require inspection or capacity testing. Differences between cells or racks can also indicate the need for further investigation.
Combining SOH trends with temperature, voltage, current, and operating history provides a more complete basis for maintenance and replacement planning.
For larger commercial and industrial applications, an integrated energy storage cabinet combines battery management, energy management, and remote monitoring functions within one system architecture.
What Is a Good Battery SOH and When Is EOL Reached?
A battery's suitability for continued operation depends on its intended application, not just its SOH percentage.
The following values provide a general reference for capacity-based SOH:
| Capacity-Based SOH | General Interpretation |
|---|
| 100% | Capacity equals the selected reference value |
| 90% | Approximately 90% of reference capacity remains |
| 80% | Approximately 80% of reference capacity remains |
| Below 80% | Reduced capacity may require closer evaluation against application requirements |
An 80% SOH threshold is often discussed as an end-of-life reference in certain battery applications, but it is not a universal replacement standard for all lithium-ion batteries or energy storage systems.
Three different considerations affect end-of-life decisions:
Technical End of Life
Technical EOL occurs when a battery can no longer meet its application's performance or operating requirements. These may include capacity retention, power capability, and safety limits.
Warranty End
Warranty conditions define the period and performance requirements covered by the manufacturer. Reaching the end of a warranty period does not automatically mean the battery has reached technical EOL.
Economic End of Life
Economic EOL occurs when continued operation is no longer financially practical compared with maintenance, replacement, or alternative system options. A battery may remain technically functional but become uneconomical because of reduced performance or increased operating costs.
Replacement decisions should consider manufacturer warranty conditions, minimum application capacity, required charging and discharging power, safety limits, project lifetime, and the cost of continued operation.
A battery with 80% capacity-based SOH may remain suitable for an application with modest energy requirements but fail to meet the needs of a system requiring higher available energy or power.
Frequently Asked Questions
Can Battery SOH Be Restored?
Permanent degradation caused by active lithium loss, electrode changes, and other irreversible chemical reactions generally cannot be reversed through ordinary charging or maintenance. However, an estimated SOH value may change after recalibration or improved operating data becomes available. Temporary performance limitations caused by low temperature may also improve when operating conditions return to normal.
Does a BMS Measure SOH Directly?
No. A BMS measures parameters such as voltage, current, and temperature, then uses estimation algorithms to calculate battery health. Some systems also use internal resistance, impedance, charge throughput, and operating history. Not every BMS supports SOH estimation or displays a user-accessible percentage.
Can Voltage Determine Battery SOH?
No. Voltage changes with SOC, temperature, current, chemistry, and load conditions. A battery may show a normal resting voltage while having significantly reduced capacity, so voltage measurements must be combined with other health indicators.
How Often Should Battery SOH Be Tested?
There is no universal testing interval. Frequency depends on battery chemistry, operating conditions, manufacturer recommendations, system criticality, and maintenance requirements. Continuous BMS monitoring can track health trends, while controlled capacity tests can verify performance when required.
Does Temperature Affect Battery SOH?
Yes. High temperatures accelerate chemical aging, while unsuitable low-temperature charging conditions may promote lithium plating. Low temperatures can also temporarily reduce available capacity and power without causing an equivalent amount of permanent degradation. SOH assessments should therefore account for operating and testing temperatures.
Is 80% SOH Always the End of Battery Life?
No. An 80% capacity-based SOH means the battery retains approximately 80% of its reference capacity under comparable test conditions. Whether it has reached EOL depends on application requirements, manufacturer specifications, warranty conditions, power capability, and safety limits.
Can Two Batteries With the Same SOH Have Different Performance?
Yes. Two batteries with the same capacity-based SOH may have different internal resistance, power capability, usable energy, and temperature behavior. Differences in chemistry, cell design, operating history, and estimation methods also affect performance. Meaningful comparisons require the same SOH definition and comparable test conditions.
Conclusion
Battery State of Health (SOH) evaluates battery degradation through indicators such as capacity, power capability, usable energy, and internal resistance. Its interpretation depends on the selected reference condition and estimation method.
For energy storage systems, SOH helps operators assess available capacity, identify changes in power delivery, and plan maintenance. Reliable decisions also require operating history, battery chemistry, system limits, and application-specific EOL criteria.