Passive Self-Heating Is a Natural Equalizer: Quantitative Characterization, Capability Boundaries, and the Gain Surface of Consistency Flattening in Series Sodium-Ion Battery Packs

Problem. Cell-to-cell internal-resistance dispersion is amplified at sub-zero temperatures and is widely regarded as the root cause of pack-level capacity loss and lifetime divergence. Industry and academia converge on one idea: eliminate the dispersion—active balancing, external preheating, and stringent dual-parameter sorting. A reversed proposition has been largely overlooked: in a series string, where current is common, resistance dispersion itself drives a passive self-homogenization mechanism—the highest-resistance cell dissipates the most Joule heat, warms the most, and its resistance drops the most, so it “catches up” with its lower-resistance neighbours. Ref. [1] proved that the sign of this compression is locked solely by 𝜕R/𝜕T<0. This paper answers the follow-up questions: how much? when does it fail? is it stable in the long run? can a quantitative surface be provided to guide sorting? Contributions. Using a physics-based sandbox calibrated against published measurements (second-order RC + VTF viscosity + Arrhenius coupling + lumped thermal model including entropic heat + concentrationpolarization truncation + dual capacity/resistance dispersion), we report six results: 1. First systematic quantification: at −30 °C/0.5C the capacity COV is flattened by 39.7% (3.47%→2.09%) with mean capacity +9.9%; the high-resistance group’s capacity rises +12.2% versus +8.0% for the low-resistance group, narrowing the high–low gap by 33.9%. Results are consistent before and after completing the physical model (40.7%→39.7%), excluding a modeling artifact. 2. Capability boundary: the mechanism is a resistance corrector, not a capacity corrector—it fails (and even mildly reverses) once capacity COV reaches about 3%; yet even when flattening is marginal, mean usable capacity still rises by about 5%. 3. C-rate sweet spot: a narrow window of 0.5–0.8C with threshold activation rather than gradual enhancement (a 12.7 pp jump from 0.45C to 0.5C); at 0.8C the flattening reaches 92.4% (isothermal COV 31.7% versus thermal 2.4%) and usable capacity is recovered by a factor of 5.5; at 1.0C everything is extinguished. 4. Full-temperature applicability domain: short-term flattening decreases monotonically from 69.4% at −30 °C to zero at 40 °C—it is a low-temperature-specific tool; at room temperature cells are already highly consistent and need no flattening. 5. Long-term stability: after 500 cycles the COV has not widened at all (both groups 4.46%)—the negative feedback exactly offsets the aging positive feedback of the central cells (aging-rate ratio 1.27×). Entropy generation—the industry’s universal villain—turns out to be a benefactor in lowtemperature self-heating. 6. Gain surface 𝜂=f(COV_Q,COV_R): capacity COVcontributes 69.1%of the variance (dominant) and resistance COV 30.9%; a threefold change in resistance COV perturbs the residual COV by ≤0.06 pp—resistance dispersion is “eaten clean” by self-heating, and the residual floor is set by capacity.

Authors

Publication Details

Journal
ChemRxiv
Published
2026-10-27
DOI
https://doi.org/10.26434/chemrxiv.15011108/v1
Primary Topic
Advanced Battery Technologies Research
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Passive Self-Heating Is a Natural Equalizer: Quantitative Characterization, Capability Boundaries, and the Gain Surface of Consistency Flattening in Series Sodium-Ion Battery Packs

yangbo, 杨博 杨
2 links
ChemRxiv
Advanced Battery Technologies Research
preprint

Passive Self-Heating Is a Natural Equalizer: Quantitative Characterization, Capability Boundaries, and the Gain Surface of Consistency Flattening in Series Sodium-Ion Battery Packs

yangbo, 杨博 杨
preprint en

Abstract

Problem. Cell-to-cell internal-resistance dispersion is amplified at sub-zero temperatures and is widely regarded as the root cause of pack-level capacity loss and lifetime divergence. Industry and academia converge on one idea: eliminate the dispersion—active balancing, external preheating, and stringent dual-parameter sorting. A reversed proposition has been largely overlooked: in a series string, where current is common, resistance dispersion itself drives a passive self-homogenization mechanism—the highest-resistance cell dissipates the most Joule heat, warms the most, and its resistance drops the most, so it “catches up” with its lower-resistance neighbours. Ref. [1] proved that the sign of this compression is locked solely by 𝜕R/𝜕T<0. This paper answers the follow-up questions: how much? when does it fail? is it stable in the long run? can a quantitative surface be provided to guide sorting? Contributions. Using a physics-based sandbox calibrated against published measurements (second-order RC + VTF viscosity + Arrhenius coupling + lumped thermal model including entropic heat + concentrationpolarization truncation + dual capacity/resistance dispersion), we report six results: 1. First systematic quantification: at −30 °C/0.5C the capacity COV is flattened by 39.7% (3.47%→2.09%) with mean capacity +9.9%; the high-resistance group’s capacity rises +12.2% versus +8.0% for the low-resistance group, narrowing the high–low gap by 33.9%. Results are consistent before and after completing the physical model (40.7%→39.7%), excluding a modeling artifact. 2. Capability boundary: the mechanism is a resistance corrector, not a capacity corrector—it fails (and even mildly reverses) once capacity COV reaches about 3%; yet even when flattening is marginal, mean usable capacity still rises by about 5%. 3. C-rate sweet spot: a narrow window of 0.5–0.8C with threshold activation rather than gradual enhancement (a 12.7 pp jump from 0.45C to 0.5C); at 0.8C the flattening reaches 92.4% (isothermal COV 31.7% versus thermal 2.4%) and usable capacity is recovered by a factor of 5.5; at 1.0C everything is extinguished. 4. Full-temperature applicability domain: short-term flattening decreases monotonically from 69.4% at −30 °C to zero at 40 °C—it is a low-temperature-specific tool; at room temperature cells are already highly consistent and need no flattening. 5. Long-term stability: after 500 cycles the COV has not widened at all (both groups 4.46%)—the negative feedback exactly offsets the aging positive feedback of the central cells (aging-rate ratio 1.27×). Entropy generation—the industry’s universal villain—turns out to be a benefactor in lowtemperature self-heating. 6. Gain surface 𝜂=f(COV_Q,COV_R): capacity COVcontributes 69.1%of the variance (dominant) and resistance COV 30.9%; a threefold change in resistance COV perturbs the residual COV by ≤0.06 pp—resistance dispersion is “eaten clean” by self-heating, and the residual floor is set by capacity.

ChemRxiv
Affordable and clean energy
Advanced Battery Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon