Page 1 of 2

What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Thu Jan 23, 2025 4:58 pm
by kwilliams
This came up in a Discord I'm in and I wanted a more permanent place to discuss it. DC-DC conversion losses across all the individual actuator drivers add up across a whole robot - it's a less glamorous efficiency question than battery chemistry, but power electronics efficiency meaningfully affects real-world runtime too. Idle/standing power draw is often surprisingly close to a meaningful fraction of active walking power draw once you account for onboard compute, sensors, and balance-holding torque - 'doing nothing' still costs real energy on a humanoid. There's no widely standardized safety certification specific to humanoid battery packs yet in most jurisdictions - deployments generally lean on adapted versions of existing standards for industrial battery systems and electrical safety rather than a purpose-built humanoid standard. What's everyone else's take?

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Thu Jan 23, 2025 7:56 pm
by chloe_jack
Small correction on one detail: Battery placement (torso-centered vs backpack vs distributed through the limbs) is a real tradeoff between center-of-mass/balance considerations and thermal/cooling access - a torso-centered pack helps balance but is harder to cool than a more exposed backpack placement. This whole thread is a good reminder how young this field still is.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Thu Jan 23, 2025 8:21 pm
by choi98
That's the official framing, at least - reality tends to lag a bit. Solid-state battery claims from platforms like XPeng's IRON, GAC's GoMate, and EngineAI's T800 are genuinely promising on paper for energy density and safety margins, but independent, large-scale field validation of those runtime claims is still fairly limited as of 2026 - it's real progress, not yet fully proven at scale.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Fri Jan 24, 2025 12:04 am
by emilyperez
@choi98 One nitpick - The average humanoid in 2026 carries under 2.5 kWh of battery capacity, with real-world runtimes clustering between two and four hours depending on how dynamic the workload is - static, low-motion tasks stretch runtime much further than continuous walking or lifting. Thermal margin in a densely packed humanoid chassis is often the real limiting factor on sustained performance, not raw motor power - actuators get thermally throttled well before they'd hit their absolute torque limits, especially during repeated high-load cycles like continuous lifting. Totally unrelated but has anyone else noticed how fast component costs are dropping this year.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Fri Jan 24, 2025 2:02 am
by scott21
@emilyperez Slight correction, though the overall point stands: Hot-swappable battery packs solve the runtime bottleneck for continuous operations (like a 24/7 warehouse shift) without needing a much bigger, heavier pack, but they add mechanical complexity, a failure-prone connector interface, and logistics overhead for managing spare packs. Distributed power architectures (multiple smaller packs or local capacitor buffering near high-draw actuators) can reduce peak current demands on the main bus and improve fault isolation, at the cost of added complexity versus a single central pack.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Sat Jan 25, 2025 12:19 am
by park44
+1 to this. Worth adding: Tesla's Optimus Gen 2 reportedly carries roughly a 2.3 kWh pack and manages about two hours of dynamic work, while Unitree's H1 runs a smaller 0.864 kWh pack good for under four hours of largely static operation - a useful illustration of how battery size and workload type both drive runtime.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Mon Jan 27, 2025 9:32 pm
by kwilliams
@park44 From hands-on experience, A BMS (battery management system) has to guard against transient current spikes from sudden gait changes or lifting motions, not just steady-state draw - peak current headroom and fast-acting protection logic matter as much as total capacity for real-world duty cycles.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Tue Jan 28, 2025 7:19 pm
by park44
@kwilliams Can I ask a dumb follow-up - Higher-voltage power architectures reduce resistive losses and current draw through the wiring harness for a given power level, which is part of why some newer platforms are moving away from lower-voltage packs as total system power demand climbs. Fast charging accelerates capacity fade over repeated cycles, so fleet operators generally have to choose between minimizing downtime (fast charging) and maximizing pack lifespan (slower charging or swap-based approaches) rather than getting both for free.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Wed Jan 29, 2025 3:09 pm
by choi98
@park44 This lines up with my experience. Best-in-class lithium-ion cells used in humanoids are currently landing around 280-300 Wh/kg, which is respectable but still leaves battery mass as one of the largest single contributors to total robot weight. Regenerative braking on humanoid joints can recover some energy during deceleration phases of walking, but the actual energy recovered is modest compared to a vehicle, since humanoid joints don't sustain the same continuous high-speed rotation that makes regen worthwhile in EVs.

Re: What's underrated: cell chemistry or BMS software, for overall pack reliability?

Posted: Fri Jan 31, 2025 10:07 am
by jwang
This lines up with my experience. Solid-state battery claims from platforms like XPeng's IRON, GAC's GoMate, and EngineAI's T800 are genuinely promising on paper for energy density and safety margins, but independent, large-scale field validation of those runtime claims is still fairly limited as of 2026 - it's real progress, not yet fully proven at scale. This whole thread is a good reminder how young this field still is.