Planning-Grade Battery Derating by Temperature & DoD

Why we built a simple, defensible method for a TBB M12 LiFePO₄ project—and who else needs it

The client problem (common in the wild)

Our client needed to size a LiFePO₄ battery system for a duty cycle where

cell temperatures would exceed the vendor’s nominal 25°C reference

They could not find clear guidance from the OEM—or in articles—on how much to derate capacity/life so the system would still meet requirements at end of life (EOL)

This gap is common: most standards and many datasheets assume testing around 20–25°C,

while real deployments see higher temps in enclosures, vehicles, rooftops, or hot climates.

The science is clear that higher temperature accelerates degradation (often captured with Arrhenius temperature dependence), and deeper depth of discharge (DoD) generally increases cycle wear—both well-documented for Li-ion/LFP systems. What’s missing in practice is a plug-in, explainable formula for planning-grade sizing when OEM data is thin.

Our planning-grade method (transparent & literature-anchored)

To support sizing decisions for a TBB M12 LiFePO₄ system, we used a one-line model that blends the two dominant levers—temperature and DoD—and anchors to the one hard life datapoint the OEM provides: “≥3000 cycles @ 25 °C, 100% DoD.”

loss_3000 = L0 × r_T(T) × DoD^z

• L0 = 0.20 → baseline 20% loss at 3000 cycles at 25 °C, DoD = 1.0 (planning anchor).

• r_T(T) = exp[ −Ea/R × (1/T_K − 1/298.15) ] → Arrhenius temperature ratio to 25 °C, with Ea ≈ 31,500 J/mol (mid-range for LFP aging), R = 8.314 J/mol·K, and T_K = T_°C + 273.15.

• z = 0.50 → sub-linear DoD sensitivity consistent with graphite–LFP results.

Why this is smart for planning

• Explainable: one slide, plain math, clear assumptions.

• Auditable: every term tied to published research; values are explicit.

• Tunable: once you have module-specific data, drop in your own Ea and z.

• Conservative: avoids over-promising life at elevated temps.

Worked intuition: sensitivity to temperature and DoD

Parameters used in examples: Ea = 31,500 J/mol, z = 0.5, L0 = 0.20.

Table 1 — DoD = 100%

Cell Temp (°C)	Arrhenius ratio r_T	Loss @ 3000	Remaining f
0	0.313	0.063	0.937
25	1.000	0.200	0.800
40	1.838	0.368	0.632
55	3.196	0.639	0.361

Table 2 — DoD = 80%

Table 2 — DoD = 80%	Loss @ 3000	Remaining f
25	0.179	0.821
55	0572	0.428

Takeaways

1. Temperature dominates — prioritize keeping cells cool.

2. Reducing DoD meaningfully helps; pairing lower DoD with cooler operation compounds benefits.

3. These are planning estimates for capacity budgeting and early tradeoffs, not warranty terms.

How to apply this in sizing (step-by-step)

1. Estimate cell temperature (°C). If you only know ambient, add a few °C for internal rise.

2. Choose the design DoD for your duty (0–1).

3. Compute loss_3000 and f = 1 − loss_3000.

4. Energy at EOL: multiply nameplate energy by f; check it still meets the requirement.

5. Power at EOL: verify the C-rate and BMS current limits still pass at reduced capacity f.

   • C_EOL = I_req / (N × Ah_module × f) → pass if C_EOL ≤ C_limit (e.g., 0.5C)

   • Check: N × I_module,cont ≥ I_req

Practical levers you control (ranked by impact)

1. Reduce temperature: ventilation, enclosure/HVAC, charge timing, sun shielding.

2. Reduce DoD: add parallel modules (↑Ah) to make cycles shallower and lower per-module C-rate.

3. Validate assumptions when hot operation is unavoidable (≥55–60 °C): run a small verification matrix (25 °C + one hot point at your DoD/C-rate), fit your own Ea and z, and update the sheet.

Who else is affected (and why)

• Telecom outdoor cabinets / remote sites: cabinets in sun/heat routinely exceed 35 °C; life drops quickly without thermal management.

• C&I / residential ESS in garages, rooftops, warehouses: real-world temps drift from lab conditions; environmental stresses matter.

• Mobile & specialty vehicles (service vans, food trucks, mobile clinics, grooming rigs): confined compartments and intermittent HVAC elevate cell temps.

• Off-grid solar / microgrids / hot-climate deployments: sustained high ambient/enclosure temps require quantified derating to avoid premature EOL.

Scope, limits, and why this still helps

• Specific hardware: Built for TBB M12 LiFePO₄ with limited OEM life data (≥3000 cycles @ 25 °C, 100% DoD).

• Planning-grade: transparent, conservative, and explainable—ideal for early decisions and stakeholder buy-in.

• Not a warranty model: replace L0, Ea, and z with measured values if you need procurement- or warranty-grade numbers.

• Why publish this? Many teams face the same gap; this offers a simple, citable method that you can calibrate as data becomes available.

References

• Wang, J., et al. (2011). Journal of Power Sources, 196(8), 3942–3948.

• Sun, Y., Saxena, S., & Pecht, M. (2018). Energies, 11(12), 3295.

• Waldmann, T., et al. (2022). Journal of Power Sources, 549, 232129.

• Zeng, L., et al. (2022). Journal of Marine Science and Engineering, 10(11), 1553.

• Aeppli, D., Hack, E., & Held, M. (2025). Journal of Energy Storage, 129, 117135.