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AgniCycle™
EV Battery Suite

A coupled electrochemical–thermal battery simulator — equivalent circuit modeling, SOC/SOH estimation, CC-CV charge curves, and degradation analysis across 6+ cell chemistries. In your browser, no install.

No install
6+ cell chemistries
Export CSV + SVG
agnicycle · ev_battery · NMC-811 · 1C discharge
SOC
72.3%
SOH
91.4%
Temp
32.1°C
Voltage
3.84V
Current
−3.2A
Rint
12.4
Cycle #
247
6+
Cell chemistries
< 10ms
Per full cycle sim
ECM
Thevenin equivalent circuit
2-way
Thermal–electrical coupling
SOC/SOH
Real-time state estimation

Battery physics, not black-box curves

Every model is grounded in peer-validated electrochemistry — OCV lookup tables, Arrhenius degradation rates, and coupled thermal dynamics.

Equivalent Circuit Model (ECM)
R₀ internal resistance + R₁–C₁ Thevenin network. OCV–SOC lookup with temperature correction. Captures transient voltage response during pulse loads and regen braking.
🌡️
Coupled Thermal Model
Lumped capacitance thermal solver. Joule heating I²R₀ + exothermic reaction heat. Convective cooling boundary conditions. Temperature feeds back into ECM parameters.
📊
SOC & SOH Estimation
Coulomb counting with OCV correction for SOC. Capacity fade and internal resistance rise modeled over cycle number. Extended Kalman filter-ready architecture.
🔋
CC-CV Charge Simulation
Full constant-current / constant-voltage charge protocol. Visualize voltage, current, and SOC vs. time. Compare charge time across C-rates and temperature setpoints.
📉
Degradation & Aging
SEI layer growth (Arrhenius kinetics), lithium plating risk at low temperatures, calendar aging. Capacity fade and resistance rise vs. cycle count — plot lifetime trajectories.
🏗️
Pack Configuration
Define series–parallel cell arrangement. Compute pack-level voltage, capacity, energy, and internal resistance. Cell-to-cell variation and imbalance analysis.

6+ cell chemistries

OCV curves, capacity, and thermal parameters sourced from experimental datasets — not synthetic averages.

NMC 811 NMC 622 LFP NCA LCO LTO Li–S (coming) Solid-state (coming)

Real electrochemistry, not a spreadsheet curve-fit

Degradation and thermal behavior come from the same equations used in battery management system design — not a linear approximation.

// Arrhenius Degradation Rate
Capacity fade rate k as a function of temperature T. This is why a pack running 15°C hotter can degrade 2-3× faster — the exponential term dominates, not a linear derating.

That same thermal model couples to Joule heating from internal resistance — the dominant heat source during fast charging and high-current discharge:

6+
Cell chemistries
OCV
Curves from real datasets
0-D
Fast, not approximate

Same battery model, different reasons to open it

🎓
Students
See why fast charging heats a pack and how that heat feeds back into degradation — instead of just memorizing the Arrhenius equation.
🔬
Researchers
Compare chemistries on thermal and degradation behavior before committing to a cell-level experimental campaign.
⚙️
Industry Engineers
Get a fast first-pass estimate of pack heat generation and degradation under a duty cycle before scoping a full BMS simulation.

Ready to model your battery?

No install. Works in any browser. Set up your first cell simulation in under 60 seconds.

Launch EV Battery Suite
Runs in any browser
No install
Export CSV + SVG