How battery storage really ages and how we model it

Batteries do not age linearly; they follow a curve that depends on cell chemistry and usage intensity. In addition to capacity loss, efficiency also declines over the service life, something missing from many economic calculations. This article explains the physical background, compares cell chemistries, and shows, using a practical example, how realistic degradation modeling affects the business case.

How much capacity and efficiency does a battery storage system still have in year 10 or 15? The answer largely determines whether the investment pays off. At the same time, degradation is one of the hardest aspects to grasp in project planning; the data basis from manufacturer warranties is limited, and the underlying electrochemistry is complex.

However, there are now robust scientific models that represent real aging behavior far better than a constant annual deduction. In this article, we show what physically happens in the battery, why degradation follows a curve, and how this affects the business case.

What happens in the battery: SEI growth as the driver

The aging of lithium-ion batteries is largely determined by the growth of the so-called Solid Electrolyte Interphase (SEI). This thin layer forms on the graphite anode and binds lithium with each cycle, which is then no longer available for energy storage.

Crucially, the SEI does not grow evenly. The thicker the layer becomes, the more it slows its own growth, similar to an ice layer on a lake that thickens quickly at first and then more and more slowly.

A storage system therefore loses significantly more capacity in the first 1,000 cycles than between cycles 4,000 and 5,000. Degradation follows a flattening curve, not a straight line.

Capacity and efficiency: Two effects, one business case

When people think of battery degradation, most think of capacity loss. That's right, but only half the story.

Capacity loss depends on the chemistry

LFP cells (lithium iron phosphate) withstand significantly more cycles than NMC or NCA cells before they reach their end-of-life threshold. LTO cells are even more robust, but because of their higher cost they play a smaller role in the C&I sector.

An LFP system at 365 cycles per year still typically has significantly more usable capacity after 15 years than a comparable NMC system. The curves follow the same basic shape, but their slopes differ, which should be considered when selecting and designing a system.

Efficiency degradation: The often overlooked factor

In addition to capacity, the round-trip efficiency (RTE) also declines over the service life. The growing SEI layer increases the cell's internal resistance, causing greater losses in every charge and discharge cycle.

Both effects act simultaneously: less storable energy and poorer efficiency together result in significantly fewer usable kWh than a model that considers capacity alone shows.

Case study: What degradation means for revenue

To make the effect tangible, a typical C&I scenario:

Initial situation: LFP storage system, 100 kWh, 50 kW, 178 cycles per year, initial RTE 86%.

Without degradation the financial analysis shows constant savings over the entire operating period, the same usable capacity every year, the same efficiency.

With degradation model the picture is different: The capacity follows a chemistry-specific power law, initially it drops faster, then increasingly levels off. At the same time, the RTE declines depending on the cumulative equivalent full cycles (EFCs) from 86% to around 83%.

This directly affects revenue: while savings of around €10,600 are achieved in the first year, by the sixth year it is only about €10,100. Over the entire project lifetime, this decline adds up and changes the payback period and ROI compared with a calculation without degradation.

with degradation

without degradation

Conclusion: Degradation belongs at the center of planning

Battery degradation follows a curve that depends on cell chemistry and usage intensity. LFP systems age more slowly than NMC systems, and the efficiency loss significantly affects the usable amount of energy over the project lifetime.

For robust business cases, degradation models are needed that capture both effects, are parameterized by chemistry, and adapt to the usage profile. In Lumera, these models feed directly into the cash flow calculation so that the financial analysis reflects what actually happens in the battery.

Sources:

• Solid–Electrolyte Interphase During Battery Cycling: Theory of Growth Regimes by Lars von Kolzenberg, Arnulf Latz, and Birger Horstmann (Chemistry Europe, 2020)

• Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes Kandler Smith, Paul Gasper, Andrew M. Colclasure, Yuta Shimonishi, and Shuhei Yoshida (Journal of The Electrochemical Society, 2021)

• Eduardo Redondo-Iglesias, Pascal Venet, Serge Pelissier. Efficiency Degradation Model of Lithium-ion Batteries for Electric Vehicles. IEEE Transactions on Industry Applications, 2018, 55 (2), pp. 1932-1940. ⟨10.1109/TIA.2018.2877166⟩. ⟨hal-01898906v2⟩

• Theory of SEI Formation in Rechargeable Batteries: Capacity Fade, Accelerated Aging and Lifetime Prediction, Matthew B. Pinson and Martin Z. Bazant (Journal of The Electrochemical Society, 2012)