Battery Pack 6-Cell Echem

ADVANTAGES3 · dim 106

SolvSRK 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)

Batteries & energy storage

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

#SolverSurvivalSCDnfevWallScore
1SolvSRK
100%
6.029,8125.45 s0.761
2SciPy LSODASciPy
100%
5.918,9456.47 s0.759
3SciPy RK23SciPy
100%
5.627,0149.27 s0.753
4CVODE BDFexternal
100%
5.58,9603.08 s0.750
5SciPy RadauSciPy
100%
5.448,60517.06 s0.748
6SciPy RK45SciPy
100%
4.822,7367.80 s0.732
7SciPy DOP853SciPy
100%
4.722,8387.78 s0.730
8Tsit5external
100%
4.520,1849.55 s0.727
9CVODE Adamsexternal
100%
4.210,3383.53 s0.720
10SciPy BDFSciPy
100%
0.611,3094.20 s0.634

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 →

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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://resonix.tech/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