The Impact of Capacity Loss

Capacity loss in BESS can be either reversible or irreversible. Irreversible losses are typically due to battery aging, manufacturing discrepancies, or environmental conditions that cause permanent degradation of the battery cells. In contrast, reversible capacity losses—such as those caused by state-of-charge (SOC) imbalances or SOC estimation errors—can be mitigated and reclaimed through proper management strategies.

A reduction in usable capacity not only hampers a BESS's ability to perform but affects its financial performance. Even a small reduction in capacity can have outsized consequences. For example, a 5% reduction in capacity might seem minor, but when it constitutes a significant portion of a BESS's operational life, the financial impact can be considerable. Similarly, SOC estimation errors can lead to capacity losses that mimic end-of-life scenarios for the batteries, even though significant capacity remains recoverable.

Causes of Capacity Loss

‍1) Irreversible Capacity Losses Due to Different Cell Capacities
In a series-connected energy storage system, the weakest cell dictates the performance of the entire string, as the capacity of the string is limited by the cell with the lowest capacity (Figure 1). This variance arises from production quality differences, which lead to small discrepancies in individual cell capacities. Over time, this effect worsens due to uneven aging among the cells, further amplifying the disparity. As some cells degrade faster than others, the overall system capacity continues to decline irreversibly.

‍2) Reversible Imbalances Due to SOC Differences
Besides differences in cell capacities, variations in the State of Charge (SOC) can also lead to imbalances in series-connected BESS. These imbalances result in the cell with the lowest SOC determining the dischargeable capacity, while the cell with the highest SOC limits the chargeable capacity of the entire string (Figure 2). Such discrepancies are a major contributor to reversible capacity loss.

SOC differences in series-connected BESS primarily stem from two causes: production tolerances and balancing issues. Production tolerances lead to variations in internal resistances and self-discharge rates, causing inherent SOC disparities from the outset. Balancing issues, on the other hand, develop during operation and arise from uneven or insufficient charge balancing among cells. The positive aspect is that these capacity losses are typically reversible. Through effective internal or external balancing techniques, the system can regain lost capacity and maintain optimal performance.

‍3) SOC Estimation Errors
Another common cause of capacity loss is inaccurate SOC estimation, particularly in lithium iron phosphate (LFP) systems.  Battery Management Systems (BMS) typically rely on methods such as the voltage method and coulomb counting to estimate SOC. However, inaccuracies frequently occur due to the flat Open Circuit Voltage (OCV) curve characteristic of LFP batteries, which makes precise SOC determination difficult. These errors can result in significant capacity reductions, but with recalibration and improved estimation techniques, much of this capacity can be restored. Our latest white paper covers SOC error correction in detail.

Strategies for Reclaiming Lost Capacity

Balancing
Internal balancing mechanisms within battery modules can be triggered to reduce SOC imbalances. Active balancing is uncommon in BESS, but passive balancing can effectively discharge cells with the highest SOCs, bringing the system back into equilibrium. External balancing, though time-consuming, can also be used to address imbalances between battery modules.
‍

Recalibration
‍Recalibrating the SOC estimator can significantly reduce errors in SOC estimation—restoring some lost capacity. Although recalibration doesn't address imbalances, it helps update the SOC estimator to better reflect the actual state of the batteries.
‍

Predictive Battery Analytics
‍Advanced data analytics, such as those offered by ACCURE, provide insights into the root causes of capacity loss. With predictive analytics, BESS operators can identify and address reversible capacity losses through targeted interventions like recalibration and balancing.

‍

To learn more about capacity loss, what causes it, and how to reverse it, see our white paper on reclaiming lost capacity.

Conclusion

Reclaiming lost capacity in BESS is not only possible but essential for optimizing performance and maximizing financial returns. While irreversible losses are inevitable as batteries age, reversible losses caused by imbalances and estimation errors can be mitigated with the right strategies. Predictive battery analytics plays a crucial role in identifying and resolving these issues, unlocking hidden capacity and improving the long-term performance of BESS.

By proactively addressing capacity loss, operators can reclaim substantial portions of their BESS's lost potential, paving the way for improved efficiency, reliability, and profitability.