Battery Pack 6-Cell Echem
ADVANTAGES3 · dim 106SolvSRK wins. At the comparison noise level, SolvSRK beats the best baseline by at least 10 percentage points of survival, or by at least 0.05 balanced score when survival is tied. Use SolvSRK for this class of problem. All verdicts →
6-cell echem-coupled stack with Butler-Volmer + diffusion + 4-stage TR (dim=106, S3)
Problem definition
Hatchard & Dahn (2001)
Canonical RHS excerpt from the registered callable used for this benchmark cell. Expand it to verify the state equations; it is not a standalone runnable fixture.
Show canonical RHS excerpt
def _butler_volmer(i0, eta, T):
f = _F / (_R_GAS * T)
arg_a = np.clip(_ALPHA_BV * f * eta, -_EXP_CLAMP, _EXP_CLAMP)
arg_c = np.clip(-_ALPHA_BV * f * eta, -_EXP_CLAMP, _EXP_CLAMP)
return i0 * (np.exp(arg_a) - np.exp(arg_c))
def _four_stage_decomposition(alpha_sei, alpha_ae, alpha_ca, alpha_el, T):
k_sei = _arrhenius_rate(_A_SEI, _E_SEI, T)
k_ae = _arrhenius_rate(_A_AE, _E_AE, T)
k_ca = _arrhenius_rate(_A_CA, _E_CA, T)
k_el = _arrhenius_rate(_A_EL, _E_EL, T)
d_sei = -k_sei * alpha_sei
d_ae = k_ae * alpha_ae * (1.0 - alpha_ae)
if alpha_ae < 1e-12 and alpha_sei < 0.15 - 1e-6:
d_ae = k_ae * 1e-6
d_ca = k_ca * (1.0 - alpha_ca)
d_el = k_el * (1.0 - alpha_el)
q_dot = (_Q_SEI * _W_SEI * abs(d_sei)
+ _Q_AE * _W_AE * d_ae
+ _Q_CA * _W_CA * d_ca
+ _Q_EL * _W_EL * d_el)
return d_sei, d_ae, d_ca, d_el, q_dot
def _radial_diffusion_3node(c, D_s, r_p):
dr = r_p / 2.0
dc = np.zeros(3)
dc[0] = 6.0 * D_s * (c[1] - c[0]) / (dr * dr)
r_m = dr
flux_out = D_s * ((r_m + 0.5 * dr) ** 2) * (c[2] - c[1]) / dr
flux_in = D_s * ((r_m - 0.5 * dr) ** 2) * (c[1] - c[0]) / dr
dc[1] = (flux_out - flux_in) / (r_m * r_m * dr)
r_s = r_p
flux_in_s = D_s * ((r_s - 0.5 * dr) ** 2) * (c[2] - c[1]) / dr
dc[2] = -flux_in_s / (r_s * r_s * dr)
return dc
def _single_cell_echem(state):
"""Full echem cell dynamics. Returns dy[16] and q_gen."""
alpha_sei = np.clip(state[0], 0.0, 1.0)
alpha_ae = np.clip(state[1], 0.0, 1.0)
alpha_ca = np.clip(state[2], 0.0, 1.0)
alpha_el = np.clip(state[3], 0.0, 1.0)
T = np.clip(state[4], 250.0, 2000.0)
eta_a = state[5]
eta_c = state[6]
c_a = np.clip(state[7:10], 0.0, _CS_MAX_A)
c_c = np.clip(state[10:13], 0.0, _CS_MAX_C)
Q_total = state[13]
P_gas = state[14]
R_int = state[15]
d_sei, d_ae, d_ca, d_el, q_dot_decomp = _four_stage_decomposition(
alpha_sei, alpha_ae, alpha_ca, alpha_el, T)
i_bv_a = _butler_volmer(_I0_ANODE, eta_a, T)
i_bv_c = _butler_volmer(_I0_CATHODE, eta_c, T)
tau_relax = 1.0
theta_a = c_a[2] / _CS_MAX_A
theta_c = c_c[2] / _CS_MAX_C
U_a = 0.6 - 0.5 * theta_a
U_c = 4.2 - 0.8 * theta_c
V_cell = U_c - U_a
d_eta_a = (-eta_a + (V_cell * 0.5 - U_a)) / tau_relax
d_eta_c = (-eta_c + (U_c - V_cell * 0.5)) / tau_relax
dc_a = _radial_diffusion_3node(c_a, _DS_ANODE, _RP_ANODE)
dc_c = _radial_diffusion_3node(c_c, _DS_CATHODE, _RP_CATHODE)
dc_a[2] += i_bv_a / _F
dc_c[2] -= i_bv_c / _F
q_echem = abs(i_bv_a * eta_a) + abs(i_bv_c * eta_c)
q_gen = q_dot_decomp * _M_CELL + q_echem * _A_SURF
q_cool = _H_CONV * _A_SURF * (T - _T_AMB)
dT = (q_gen - q_cool) / (_M_CELL * _CP)
dQ = q_gen
n_gas_max = 0.01
n_gas = alpha_el * n_gas_max
dn_gas = n_gas_max * d_el
dP = (dn_gas * _R_GAS * T + n_gas * _R_GAS * dT) / _V_HEAD
dR = _R0 * (0.5 * abs(d_sei) + 2.0 * d_ae)
dy = np.empty(16)
dy[0] = d_sei
dy[1] = d_ae
dy[2] = d_ca
dy[3] = d_el
dy[4] = dT
dy[5] = d_eta_a
dy[6] = d_eta_c
dy[7:10] = dc_a
dy[10:13] = dc_c
dy[13] = dQ
dy[14] = dP
dy[15] = dR
return dy, q_gen
def _bp6e_rhs(t, y):
cells = [y[i * _CELL_DIM_ECHEM:(i + 1) * _CELL_DIM_ECHEM]
for i in range(_BP6E_N_CELLS)]
T = np.array([np.clip(cells[i][4], 250.0, 2000.0)
for i in range(_BP6E_N_CELLS)])
flux_offset = _BP6E_CELL_BLOCK
contact_offset = flux_offset + _BP6E_N_FLUX
q_tracked = y[flux_offset:contact_offset]
Tc = y[contact_offset:contact_offset + _BP6E_N_FLUX]
dy = np.zeros(_BP6E_DIM)
cell_dy = []
for i in range(_BP6E_N_CELLS):
cdy, _ = _single_cell_echem(cells[i])
cell_dy.append(cdy)
for i in range(_BP6E_N_FLUX):
q_cond = _K_CONTACT * _A_CONTACT * (T[i] - T[i + 1]) / _D_GAP
q_rad = _SIGMA * _EMISSIVITY * _A_CONTACT * (T[i]**4 - T[i + 1]**4)
q_total = q_cond + q_rad
cell_dy[i][4] -= q_total / (_M_CELL * _CP)
cell_dy[i + 1][4] += q_total / (_M_CELL * _CP)
dy[flux_offset + i] = (q_total - q_tracked[i]) / 0.1
dy[contact_offset + i] = (0.5 * (T[i] + T[i + 1]) - Tc[i]) / 1.0
for i in range(_BP6E_N_CELLS):
dy[i * _CELL_DIM_ECHEM:(i + 1) * _CELL_DIM_ECHEM] = cell_dy[i]
return dy- Parameters
- _ALPHA_BV = 0.5
- _A_AE = 2.5e+13
- _A_CA = 6.667e+13
- _A_CONTACT = 0.0004
- _A_EL = 5.14e+25
- _A_SEI = 1.667e+15
- _A_SURF = 0.000818
- _BP6E_CELL_BLOCK = 96
- _BP6E_DIM = 106
- _BP6E_N_CELLS = 6
- _BP6E_N_FLUX = 5
- _CELL_DIM_ECHEM = 16
- _CP = 830
- _CS_MAX_A = 31370
- _CS_MAX_C = 51410
- _DS_ANODE = 3.9e-14
- _DS_CATHODE = 1e-13
- _D_GAP = 0.001
- _EMISSIVITY = 0.8
- _EXP_CLAMP = 80
- _E_AE = 135080
- _E_CA = 139600
- _E_EL = 274000
- _E_SEI = 135080
- _F = 96485
- _H_CONV = 10
- _I0_ANODE = 10
- _I0_CATHODE = 1
- _K_CONTACT = 0.5
- _M_CELL = 0.044
- _Q_AE = 1.714e+06
- _Q_CA = 314000
- _Q_EL = 155000
- _Q_SEI = 257000
- _R0 = 0.02
- _RP_ANODE = 1.25e-05
- _RP_CATHODE = 8.5e-06
- _R_GAS = 8.314
- _SIGMA = 5.67e-08
- _T_AMB = 298
- _V_HEAD = 1e-06
- _W_AE = 0.5
- _W_CA = 0.25
- _W_EL = 0.217
- _W_SEI = 0.033
- Initial condition
- y(0) = [0.15, 0, 0, 0, 450, 0, …] [shape=(106,), min=0, max=101325]
- Horizon
- t ∈ [0, 900]
Canonical RHS excerpt captured from the same registered callable used for the published benchmark. Frozen closure values are summarized below; helper imports and solver settings are intentionally omitted.
Fingerprint
Spread: extreme
Default noise: high
Recommendation snapshot
Clean best: SolvSRK
Noisy best: SolvSRK
Coverage
14 solver arms · clean + 5 noise levels
Ranked on survival, precision, and speed
Versions & freeze
Methodology →- Freeze
- 2026-08-13
- libsolvsrk
- 2.3.0
- SciPy
- 1.14
- SUNDIALS
- CVODE (bundled backend)
20 seeds/cell default · 14 arms · TRL 4–5 · simulation-lab validated · this page: Battery Pack 6-Cell Echem (battery-pack-6-cell-echem)
Governed SolvTune benchmark freeze; per-arm medians only. RHS definitions and raw trial rows are not published.
Self-reported by Resonix Labs · not independently verified
Results matrix
Pick an objective and a noise level to rank all arms on survival, median SCD, median nfev, and median wall time. Medians across seeds.
Objective
Best overall trade-off of survival, precision, and speed.
Noise level
| # | Solver | Survival | SCD | nfev | Wall | Score |
|---|---|---|---|---|---|---|
| 1 | SolvSRK | 100% | 6.0 | 29,812 | 5.45 s | 0.761 |
| 2 | SciPy LSODASciPy | 100% | 5.9 | 18,945 | 6.47 s | 0.759 |
| 3 | SciPy RK23SciPy | 100% | 5.6 | 27,014 | 9.27 s | 0.753 |
| 4 | CVODE BDFexternal | 100% | 5.5 | 8,960 | 3.08 s | 0.750 |
| 5 | SciPy RadauSciPy | 100% | 5.4 | 48,605 | 17.06 s | 0.748 |
| 6 | SciPy RK45SciPy | 100% | 4.8 | 22,736 | 7.80 s | 0.732 |
| 7 | SciPy DOP853SciPy | 100% | 4.7 | 22,838 | 7.78 s | 0.730 |
| 8 | Tsit5external | 100% | 4.5 | 20,184 | 9.55 s | 0.727 |
| 9 | CVODE Adamsexternal | 100% | 4.2 | 10,338 | 3.53 s | 0.720 |
| 10 | SciPy BDFSciPy | 100% | 0.6 | 11,309 | 4.20 s | 0.634 |
At Clean, best balanced arm is SolvSRK.
Values are medians across seeds, measured by Resonix Labs on Resonix hardware and not independently verified; nfev and wall are on reference lab hardware (indicative). Under injected noise only SolvSRK and the SciPy arms are run. How we measure accuracy → · Verification status →
Cite this page
Replace the access date. Pin the freeze ID and library versions when comparing against a later export. Cite it as what it is - a self-reported vendor benchmark, not an independently verified result. The note field says so; please keep it.
@misc{resonix_evidence_battery_pack_6_cell_echem_2026,
title = {Resonix Evidence Portal: Battery Pack 6-Cell Echem},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonixusa.com/evidence/problems/battery-pack-6-cell-echem}},
note = {Self-reported vendor benchmark; internally generated by Resonix Labs and not independently verified. Accessed YYYY-MM-DD. Freeze 2026-08-13; libsolvsrk 2.3.0; SciPy 1.14.}
}Related
TRL 4–5 · simulation-lab validated · 398 problems · 14 solver arms · clean + 5 noise levels
Freeze: 2026-08-13 · scipy 1.14 · libsolvsrk 2.3.0 · Methodology
Self-reported by Resonix Labs · not independently verified · Verification status