How to Calculate Battery Round-Trip Efficiency
Round-trip efficiency (RTE) converts the physics of a battery system into a single number: the ratio of energy you can extract from a charge cycle to the energy you had to put in. Asset developers rely on it when modeling performance guarantees, utilities monitor it to calibrate dispatch algorithms, and financiers factor it into levelized cost of storage assessments. Accurate RTE calculations require disciplined data capture across metering points and an understanding of where auxiliary losses live.
This walkthrough codifies that process so engineers, analysts, and compliance teams can reproduce the metric confidently. We define the terms, align units, present the core formula, and detail a defensible step-by-step workflow. Along the way we highlight validation practices, common pitfalls, and how RTE interacts with diagnostics such as battery state of health analysis and state of charge reconciliation. The article closes with an embedded calculator that mirrors the standalone Battery Round-Trip Efficiency tool.
Definition and reporting boundary
Battery round-trip efficiency expresses the fraction of input energy that re-emerges as usable output energy over a defined charge–discharge cycle. It is dimensionless but typically reported as a percentage. The numerator captures the net energy delivered to the load or grid, excluding auxiliary consumption such as HVAC, pumping, or control electronics. The denominator reflects the gross electrical energy absorbed during charging, including conversion losses within the power electronics. Establish the time window explicitly—many operators evaluate RTE over one full cycle, while fleet dashboards aggregate across a day or week.
Always state the boundary conditions in documentation and dashboards. Specify whether measurements are taken on the AC side of the inverter or the DC bus, and whether auxiliary loads are captured through separate meters or estimated from manufacturer datasheets. When comparing RTE across assets, align these boundaries or normalise the data; otherwise, disparate assumptions can lead to misleading conclusions.
Variables, symbols, and units
Use consistent units across all quantities. Kilowatt-hours (kWh) are standard for utility applications, though laboratory tests may use watt-hours (Wh). Convert everything to kWh before computing the ratio to keep magnitudes intuitive and to align with performance contracts.
- Ech – Gross charge energy delivered to the battery during the interval (kWh). Measure on the AC side of the inverter unless your contractual obligations specify DC quantities.
- Edis – Discharge energy exported from the battery terminals in the same interval (kWh). Align timestamps with Ech.
- Eaux – Auxiliary energy consumed by supporting systems tied to the cycle (kWh). Set to zero if those loads are negligible or already netted out of Edis.
- ηrt – Round-trip efficiency, reported as a percentage (%).
- ΔSoC – Optional state-of-charge window used for the test (%). It is not required for the formula but helps interpret results if cycles differ in depth.
Keep a metadata log for each test: ambient temperature, battery chemistry, inverter firmware, and any curtailment events. These contextual variables matter when explaining deviations from contractual guarantees or reconciling RTE with warranty claims.
Primary formula and derived metrics
Round-trip efficiency divides net discharge energy by gross charge energy. Net discharge subtracts auxiliary loads you attribute to the battery during the cycle. Expressed formally:
Net discharge energy: Enet = max(Edis − Eaux, 0)
Round-trip efficiency (%): ηrt = (Enet ÷ Ech) × 100
Fractional loss (%): L = 100 − ηrt
If Enet exceeds Ech, the resulting ηrt will be greater than 100%. That usually indicates misaligned measurement windows, uncalibrated meters, or a failure to account for all auxiliary consumption. Flag and investigate these cases rather than publishing the inflated figure. Conversely, an ηrt below 60% is a strong signal of inverter faults, thermal derating, or dramatic state-of-charge swings that fall outside the intended operating envelope.
Step-by-step workflow
Step 1: Instrument the charge window
Capture Ech using revenue-grade meters on the AC feeder or through inverter telemetry exported at one-minute granularity. Confirm that timestamps, timezone handling, and data quality flags are consistent. If the system charges from multiple feeders, aggregate them before proceeding.
Step 2: Align discharge measurements
Pull Edis from the same metering layer used for Ech. For hybrid systems feeding both on-site load and the grid, separate the flows or document the mix. Ensure that the discharge interval mirrors the charge interval; mismatched windows are the most common root cause of misleading efficiencies.
Step 3: Quantify auxiliary loads
Determine whether HVAC, DC-DC converters, fire suppression systems, or control electronics are captured within the discharge meter. If not, meter them separately or allocate a proportion based on runtime logs. For preliminary studies you may approximate Eaux using manufacturer loss coefficients, but transition to measured data before entering performance guarantee negotiations.
Step 4: Calculate ηrt
Convert all energies to kWh and plug them into the formula above. Document the rounding rules used (two decimal places is typical). Record ηrt, Enet, and L side by side so reviewers can trace how much energy vanished to losses versus how much remained useful.
Step 5: Contextualise and store results
Archive every calculation with metadata: depth of discharge, battery temperature, charge/discharge C-rates, and any operational notes. This archive enables regression analysis later when diagnosing degradation or comparing vendor upgrades. Integrate the workflow into existing analytics pipelines alongside metrics like LCOS, SoH, and SoC to maintain a coherent performance narrative.
Validation and quality control
Validate the output against known baselines. Lithium-ion utility systems typically report 85–92% RTE in nominal conditions, while flow batteries range from 70–80%. Compare your result to vendor datasheets adjusted for the tested ΔSoC and ambient temperature. If your figure deviates by more than ±5 percentage points, revisit each input: verify meter calibration certificates, check for clock drift, and confirm that auxiliary loads are neither double-counted nor omitted.
Run sensitivity tests by perturbing each input ±2%. This quantifies how much meter error or logging latency would move the final efficiency. Cross-check that Ech minus Enet equals the estimated losses from inverter efficiency curves and thermal models. Where possible, reconcile the implied heat load with the facility's HVAC monitoring to ensure the energy balance closes.
Limits, assumptions, and interpretation
ηrt assumes a full charge–discharge cycle. Partial cycles or arbitrage strategies that float state of charge within a narrow band can distort the metric, especially if the calculation window captures more auxiliary runtime than delivered energy. For daily reporting, sum energy across all cycles before computing the ratio to avoid fragmentation.
Remember that RTE is a snapshot, not a warranty verdict. Seasonal temperature swings, inverter firmware updates, and cell aging all shift the value. Pair RTE trends with degradation models and operational KPIs—such as megawatt-hours dispatched or frequency regulation scorecards—to tell a complete performance story. When negotiating service-level agreements, specify how RTE will be measured, rounded, and validated to prevent disputes.
Embed: Battery round-trip efficiency calculator
Execute the workflow above inside CalcSimpler. The embedded calculator synchronises with the standalone tool, handles auxiliary defaults, and presents efficiency with consistent rounding so audit trails stay clean.