HPPC testing uses controlled SOC stepping, rest periods, and short current pulses to measure how a battery’s voltage responds dynamically. A programmable battery testing system records current, terminal voltage, time, and usually temperature while the cell is moved through SOC points—commonly in 10% increments. The resulting voltage response is used to identify open-circuit voltage, ohmic resistance, polarization resistance, and RC time constants for an equivalent circuit model.

The essential workflow is: establish the OCV–SOC relationship, step the battery through defined SOC levels, apply discharge and charge pulses at each level, and fit the measured voltage response to an equivalent circuit model.

What the HPPC Test Is Designed to Measure

Dynamic power response

The HPPC protocol evaluates the battery’s ability to deliver and accept power at different SOC levels. It separates the immediate voltage response caused by ohmic resistance from the slower response caused by electrochemical polarization.

SOC-dependent model parameters

Battery parameters are not constant across the operating range. The test therefore produces parameter maps such as:

• (U_{OCV}(SOC)) or (V_{OC}(SOC))
• Ohmic resistance, (R_0)
• Polarization resistance, (R_P)
• Polarization capacitance, (C_P)
• RC time constant, (\tau = R_P C_P)

More complex models may use multiple polarization branches, such as (R_1,C_1) and (R_2,C_2).

How the Battery Testing System Executes the Protocol

Configure the test channel

The cell or module is connected to a programmable battery cycler with controlled current output, voltage and current measurement, temperature monitoring, and automated sequence control.

The system must be able to generate rapid current transitions and sample the resulting voltage response at sufficiently short intervals. The reference procedure uses approximately 0.1-second data intervals during the pulse sequence.

Fully charge and stabilize the battery

The test begins by charging the battery to its defined full-charge condition using the selected charge protocol. The battery is then placed at rest, commonly for approximately 2 hours, to allow voltage, temperature, and electrochemical states to approach equilibrium.

This step establishes a reproducible starting condition and provides a practical estimate of the full-charge open-circuit voltage.

Move through SOC levels

The system discharges the battery in controlled increments, commonly 10% SOC steps, using a constant current such as 0.3 C.

After each discharge increment, the system pauses for a rest period, commonly about 1 hour. The rest allows transient voltage effects to decay before the next pulse test.

The sequence is repeated until the required SOC range has been characterized.

Apply the pulse sequence

At each SOC point, the automated test system applies a composite pulse sequence:

1. Discharge pulse: approximately 10 seconds at 1 C
2. Open-circuit rest: approximately 40 seconds
3. Charge pulse: approximately 10 seconds at 0.75 C

The exact pulse magnitude and duration can be adapted to the cell, module, test objective, and equipment limits. Some HPPC implementations specify pulse levels relative to the allowable maximum current rather than using fixed C-rates.

Record synchronized test data

The system records time-synchronized:

• Terminal voltage
• Applied current
• SOC or accumulated charge throughput
• Cell and ambient temperature
• Test-state markers, such as pulse start and pulse end

Accurate synchronization is important because the parameter calculations depend on voltage changes occurring immediately after a current step and during subsequent relaxation.

Establishing the OCV–SOC Relationship

Use rest voltage as the OCV estimate

At each SOC level, the voltage measured after sufficient rest is used as an approximation of the open-circuit voltage:

[ U_{OCV}(SOC) \approx U_{\text{rest}} ]

The resulting table or fitted curve defines the battery’s equilibrium voltage as a function of SOC.

Recognize the limits of short rest periods

A one-hour rest may provide a useful engineering approximation, but it does not always produce complete electrochemical equilibrium. For high-accuracy OCV characterization, longer rests or a dedicated OCV test may be required.

The OCV curve should therefore be treated separately from the dynamic pulse response whenever the application requires high SOC-estimation accuracy.

Extracting Equivalent Circuit Parameters

Identify the instantaneous ohmic voltage change

When a current pulse begins, the terminal voltage changes abruptly. This immediate step is primarily associated with the battery’s ohmic resistance, including contributions from the electrolyte, current collectors, contacts, and other fast resistive effects.

A basic resistance estimate is:

[ R_0 = \frac{\Delta U}{\Delta I} ]

For a pulse sequence containing both discharge and charge transitions, a combined estimate can be written as:

[ R_0 = \frac{(U_0-U_1)+(U_3-U_2)}{2I_1} ]

The exact voltage labels depend on how the data points are defined, but the principle is the same: divide the instantaneous voltage step by the corresponding current step.

Fit the transient polarization response

After the instantaneous voltage jump, the voltage continues to change more gradually. This transient behavior is attributed to polarization and is modeled using one or more resistor-capacitor branches.

For a first-order Thevenin model, a representative response equation is:

[ y(t)=a-bI-cI\left(1-e^{-t/d}\right) ]

The fitted terms are interpreted as:

• (a): open-circuit voltage, (U_{OCV})
• (b): ohmic resistance, (R_0)
• (c): polarization resistance, (R_P)
• (d): RC time constant, (\tau)

The polarization capacitance is then calculated from:

[ C_P=\frac{\tau}{R_P} ]

Fit charge and discharge responses separately when necessary

The battery may not respond identically during discharge and charge. Therefore, the test data can be used to identify separate parameters such as:

• Discharge resistance: (R_{\text{discharge}})
• Charge or regeneration resistance: (R_{\text{charge}})

This distinction is useful when calculating both discharge power capability and regenerative charge acceptance.

Extend the model for multiple time scales

A single (R_P C_P) branch may not represent all of the battery’s dynamic behavior. If the voltage response contains multiple relaxation time scales, the model can be expanded:

[ R_0 + (R_1 \parallel C_1) + (R_2 \parallel C_2) ]

The testing system still executes the same basic pulse experiment, but the parameter-estimation stage fits multiple exponential components instead of one.

Applying Parameter Estimation to Each SOC Point

Segment the pulse data

For every SOC level, the analysis software identifies:

• The pre-pulse rest voltage
• The current transition
• The instantaneous voltage step
• The transient voltage decay or recovery
• The end of the pulse
• The subsequent relaxation response

The data are then separated into discharge and charge segments where appropriate.

Estimate parameters using regression or curve fitting

Least-squares linear regression, nonlinear least squares, or exponential curve fitting can be applied to the segmented response.

The fitted parameters are calculated independently at each SOC point, producing parameter functions such as:

[ R_0=f(SOC) ]

[ R_P=f(SOC) ]

[ C_P=f(SOC) ]

[ U_{OCV}=f(SOC) ]

These functions can be stored as lookup tables, polynomial fits, spline curves, or other forms suitable for a battery-management-system model.

Validate the fitted model

The identified model is simulated using the same current pulses applied during the experiment. Its predicted terminal voltage is compared with the measured voltage.

A credible parameter set should reproduce both:

• The immediate voltage jump at the current transition
• The slower transient response during and after the pulse

Large fitting errors may indicate inadequate rest time, inaccurate pulse timing, temperature drift, measurement noise, or an equivalent circuit model that is too simple.

Calculating Pulse Power Capability

Determine allowable voltage and resistance

The measured resistance can be combined with voltage limits to estimate the battery’s pulse power capability.

For discharge, a representative calculation is:

[ P_{\text{discharge}}

\frac{U_{\min}\left(U_{OCV}-U_{\min}\right)} {R_{\text{discharge}}} ]

For charge, a representative calculation is:

[ P_{\text{charge}}

\frac{U_{\max}\left(U_{\max}-U_{OCV}\right)} {R_{\text{charge}}} ]

Here:

• (U_{\min}) is the minimum allowable discharge voltage
• (U_{\max}) is the maximum allowable charge voltage
• (U_{OCV}) is the equilibrium voltage at the tested SOC

These calculations estimate how much power can be delivered or accepted before reaching the voltage constraints.

Interpret power results with care

The power equations are model-based estimates, not universal limits. Thermal constraints, current limits, aging, pulse duration, cell imbalance, and battery-management-system protections can impose stricter limits.

Understanding the Trade-offs

Short pulses improve dynamic resolution

Short current pulses isolate fast voltage behavior and make the ohmic voltage step easier to identify. However, they may not fully reveal slower polarization mechanisms.

Longer pulses reveal more dynamics

Longer pulses provide more information about transient and diffusion-related behavior. They also increase the risk of SOC drift, heating, and departure from the nominal test condition.

Higher current improves signal strength

Larger pulses produce larger voltage changes, improving resistance-identification sensitivity. Excessive current, however, can cause heating, nonlinear behavior, or cell stress that distorts the parameters.

Rest duration affects OCV accuracy

Insufficient rest can cause the measured “OCV” to include residual polarization. Excessively long rest periods improve equilibrium but substantially increase test duration.

Temperature must be controlled

Equivalent circuit parameters vary with temperature. If temperature changes during the SOC sweep, the resulting parameter map may combine SOC effects with thermal effects.

Testing should therefore record temperature continuously and, where possible, repeat characterization at the temperatures relevant to the intended application.

One model may not fit every operating condition

Parameters identified at one C-rate, temperature, aging state, or pulse duration should not automatically be treated as universal. The model is valid only within the conditions represented by the test data unless additional validation supports broader use.

Making the Right Choice for Your Goal

The most reliable implementation is a repeatable automated sequence that combines controlled SOC stepping, adequate rest periods, precise pulse control, synchronized high-speed acquisition, and parameter fitting at every SOC point.

• If your primary focus is equivalent circuit modeling: Use the pulse response to separate the instantaneous ohmic step from the slower polarization transient, then fit (R_0), (R_P), and (C_P) or multiple RC branches at each SOC.
• If your primary focus is SOC estimation: Perform a dedicated OCV characterization with sufficiently long rests and use HPPC data to capture the dynamic voltage correction.
• If your primary focus is discharge power capability: Extract discharge resistance at each SOC and combine it with the minimum allowable voltage and the measured OCV.
• If your primary focus is regenerative charging: Identify charge-side resistance separately and calculate the allowable charge power using the maximum voltage limit.
• If your primary focus is model accuracy: Control temperature, verify pulse timing, validate the fitted model against measured voltage, and use a multi-time-constant model when a single RC branch is inadequate.

A properly executed HPPC test converts controlled pulse measurements into SOC-dependent electrical parameters that can directly support battery models, power-limit calculations, and battery-management algorithms.

Summary Table:

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