ESC Dynamics with Thermal Derating (8-state)
PARITYS3 · dim 8No clear winner. The survival gap is under 10 percentage points and the balanced-score gap is under 0.05, so neither SolvSRK nor the best baseline clears the win threshold. Either works - choose on cost, licensing, or integration effort. All verdicts →
8-state ESC dynamics: output voltage/current, MOSFET/board temperatures, duty cycle, DC bus capacitor, cumulative energy. PWM switching tau ~0.001s vs thermal tau ~60s → stiffness ~60000:1.
Problem definition
Mohan, Undeland & Robbins, 'Power Electronics'; STMicroelectronics AN4070
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 _duty_command(t: float) -> float:
"""Simulated flight controller PWM commands."""
if t < 0.5:
return 0.3 # idle / spin-up
elif t < 2.0:
return 0.65 # hover throttle
elif t < 4.0:
return 0.85 # climb / aggressive manoeuvre
elif t < 6.0:
return 0.65 # back to hover
elif t < 8.0:
return 0.4 # descent
else:
return 0.1 # motor brake / idle
def _motor_omega(duty: float) -> float:
"""Approximate motor speed from duty cycle for back-EMF."""
return duty * _V_BUS / _KE * 0.85
def rhs_esc_dynamics(t, y):
"""8-state ESC dynamics with current limiting and thermal derating."""
dy = np.zeros(8)
V_out = y[0]
I_out = y[1]
T_mos = y[2]
T_brd = y[3]
duty = y[4]
I_cap = y[5]
V_cap = y[6]
# PWM filter: track commanded duty with first-order lag
d_cmd = _duty_command(t)
# Thermal derating
if T_mos > _T_DERATE:
derate = max(0.0, 1.0 - (T_mos - _T_DERATE) / (_T_SHUTDOWN - _T_DERATE))
else:
derate = 1.0
d_limited = d_cmd * derate
# Current limiting (soft)
if I_out > _I_SOFT:
i_limit_factor = max(0.1, 1.0 - (I_out - _I_SOFT) / (_I_MAX - _I_SOFT))
d_limited *= i_limit_factor
dy[4] = (d_limited - duty) / _TAU_PWM
# Output voltage
omega = _motor_omega(duty)
V_bemf = _KE * omega
V_applied = V_cap * duty
dy[0] = (V_applied - V_out) / (_TAU_PWM * 10)
# Output current: V = I*R + L*dI/dt + V_bemf
if _L_MOTOR > 0:
dy[1] = (V_out - I_out * _R_MOTOR - V_bemf) / _L_MOTOR
else:
dy[1] = 0.0
# Clamp current
if I_out >= _I_MAX and dy[1] > 0:
dy[1] = 0.0
# MOSFET conduction + switching losses
P_cond = I_out**2 * _R_DS_ON * 2 # 2 FETs in current path
P_sw = 0.5 * V_cap * I_out * 20e-9 * _F_SW * 2 # switching loss estimate
P_total = P_cond + P_sw
# Thermal dynamics: junction
dy[2] = (P_total - (T_mos - T_brd) / _R_TH_JC) / _C_TH_J
# Thermal dynamics: board
dy[3] = ((T_mos - T_brd) / _R_TH_JC - (T_brd - _T_AMB) / _R_TH_BA) / _C_TH_B
# DC bus capacitor
I_bus = I_out * duty
dy[5] = (I_bus - I_cap) / (_TAU_PWM * 5)
dy[6] = (I_cap - I_bus) / _C_BUS if _C_BUS > 0 else 0.0
# Cumulative energy dissipated
dy[7] = P_total
return dy- Parameters
- _C_BUS = 0.00047
- _C_TH_B = 15
- _C_TH_J = 0.5
- _F_SW = 16000
- _I_MAX = 30
- _I_SOFT = 25
- _KE = 0.007
- _L_MOTOR = 0.0001
- _R_DS_ON = 0.008
- _R_MOTOR = 0.1
- _R_TH_BA = 20
- _R_TH_JC = 3
- _TAU_PWM = 6.25e-05
- _T_AMB = 25
- _T_DERATE = 100
- _T_SHUTDOWN = 150
- _V_BUS = 14.8
- Initial condition
- y(0) = [0, 0, 25, 25, 0, 0, 14.8, 0]
- Horizon
- t ∈ [0, 10]
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: low
Recommendation snapshot
Clean best: SciPy BDF
Noisy best: SciPy RK45
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: ESC Dynamics with Thermal Derating (8-state) (esc-dynamics-with-thermal-derating-8-state)
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 | SciPy BDFSciPy | 100% | - | 8,420 | 266 ms | 0.809 |
| 2 | SciPy RadauSciPy | 100% | - | 22,660 | 467 ms | 0.809 |
| 3 | SciPy RK45SciPy | 100% | - | 95,450 | 793 ms | 0.809 |
| 4 | SciPy LSODASciPy | 100% | - | 8,559 | 45 ms | 0.809 |
| 5 | SciPy DOP853SciPy | 100% | - | 304,730 | 2.34 s | 0.809 |
| 6 | SciPy RK23SciPy | 100% | - | 73,943 | 741 ms | 0.809 |
| 7 | CVODE BDFexternal | 100% | - | 8,709 | 80 ms | 0.809 |
| 8 | CVODE Adamsexternal | 100% | - | 5,453 | 52 ms | 0.809 |
| 9 | Tsit5external | 100% | - | 98,142 | 8.61 s | 0.809 |
| 10 | SolvSRK | 100% | - | 20,125 | 98 ms | 0.809 |
At Clean, best balanced arm is SciPy BDF · SolvSRK survival 100%.
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_esc_dynamics_with_thermal_derating_8_state_2026,
title = {Resonix Evidence Portal: ESC Dynamics with Thermal Derating (8-state)},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonixusa.com/evidence/problems/esc-dynamics-with-thermal-derating-8-state}},
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