Liquid Cooling Systems for Humanoid Robots: Small Channels, Big Impact
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The liquid cooling systems for humanoid robots can meet the heat dissipation needs of high-power density components, providing technical support for robots to achieve more powerful functions (such as high-speed movement and complex task processing), and promoting the further development of robotics technology.
Definition of Liquid Cooling Systems For Humanoid Robots
The liquid cooling systems for humanoid robots are thermal management technologies designed to address the heat generated by high-power components inside humanoid robots. Its core principle involves using a liquid (such as water or specialized coolant) as a heat transfer medium, which circulates to transfer heat from the heating components to a heat dissipation device, and then dissipates it into the surrounding environment. The humanoid robot liquid cooling system boasts advantages such as high cooling efficiency and reliability, effectively mitigating heat issues during high-load operation, ensuring the robot’s performance and stability.
Recommended Related Reading from AI Robots Eidos
Efficient cooling technologies of humanoid robot motors are a key component that the cooling solutions for humanoid robots need to address. If you are interested in the cooling technologies of humanoid robot motors, please read this article discussing the heat dissipation technologies for humanoid robot motors. This article covers various mainstream humanoid robot motor cooling technologies, including air cooling, liquid cooling, and structural cooling.
Types of The Liquid Cooling Systems For Humanoid Robots
To meet the specific needs of robotic heat dissipation, the industry has primarily developed three main types of liquid cooling systems for humanoid robots: cold plate liquid cooling, immersion liquid cooling, and pump-free liquid cooling. Each system has its own specific implementation logic and suitable application scenarios.
Cold Plate Liquid Cooling System
This is currently the core choice for humanoid robot liquid cooling. The fundamental principle involves using micro-channel cold plates to directly contact and transfer heat from high-heat components (e.g., joint motors, AI chips). For example, micro-channel cold plates from companies like Tenglong use aluminum alloy material, with thickness controlled within 3mm, achieving a cooling power density of up to 800W/L. This system excels in cooling robot joint motors, effectively preventing overheating during continuous operation.
Immersion Liquid Cooling System
This system comes in two main forms: single-phase and two-phase immersion. Single-phase immersion submerges heat-generating components directly in coolant, dissipating heat through sensible heat change. Two-phase immersion utilizes the phase change of the coolant (liquid to gas) to absorb heat.
This technology is currently less applied in robotics, primarily constrained by the complexity of sealing design and subsequent maintenance challenges. However, its cooling efficiency advantage is significant, capable of achieving a cooling density exceeding 2000W/L.
Pump-Free Liquid Cooling System
Principle: Unlike traditional liquid cooling that relies on mechanical pumps to circulate coolant (facing challenges like energy consumption, noise, and reliability), pump-free technology takes a different approach. For example, it utilizes the heat-absorption principle of volatile liquid (e.g., water, alcohol) evaporation, storing and transporting the liquid through porous materials like sponges to achieve autonomous circulation and heat dissipation without a pump. This technology maintains cooling efficiency while significantly simplifying the system structure and improving lightweight design and integration.
Advantages of Liquid Cooling Systems for Humanoid Robots
The joints of humanoid robots can be described as “miniature high-temperature furnaces.” The joint motors of Optimus have already exceeded 500W in power. When all 22 joints operate simultaneously, the internal core temperature can easily soar above 80°C. Compounding this challenge is the extremely compact internal space of the robot, with less than 5 cm³ available for cooling systems in the joints. Air cooling systems are no longer suitable for humanoid robots due to the following reasons:
| Insufficient Cooling Efficiency of Air Cooling Systems: The cooling density of air cooling systems is only 100–200 W/L, which is inadequate for handling the concentrated heat generated by high-power motors. This can lead to frequent motor start-stop cycles and a sharp reduction in lifespan.
| Poor Spatial Compatibility of Air Cooling Systems: The thickness of fans in air cooling systems typically exceeds 10 mm, making them impossible to fit into Optimus’s joint gaps, which are less than 3 mm thick.
In contrast, liquid cooling systems for humanoid robots offer a cooling density of up to 800 W/L, which is 4–8 times that of air cooling. They can stabilize the joint core temperature below 40°C, and the pipeline thickness can be compressed to less than 3 mm—thinner than a credit card—perfectly meeting the technical requirements of the robot. Elon Musk once stated, “Optimus can achieve 8 hours of continuous operation, and the contribution of the liquid cooling systems for humanoid robots is no less significant than breakthroughs in battery technology.”
Technological Breakthroughs in Liquid Cooling Systems for Humanoid Robots
| Structural Miniaturization: Tesla customized liquid cooling pipelines for Optimus with diameters of only 2–3 mm, employing an aluminum alloy micro-channel cold plate design. The flow channels are directly integrated into the stator core, allowing the liquid cooling systems for humanoid robots to be highly integrated with the joint motor. This design not only avoids occupying additional space but also enables “zero-distance heat conduction,” improving cooling efficiency by over 30%.
| Dynamic Thermal Management: The cooling needs of robots are not constant. For instance, the hip joint generates less heat during walking due to lower loads, while heat production doubles instantly during running or heavy lifting due to sudden increases in joint load. Tesla developed a dynamic flow regulation algorithm that uses sensors to monitor joint temperature and load in real time, automatically adjusting the coolant flow rate. For example, the coolant flow rate for the hip joint increases by 50% during running and decreases during idle periods to save energy. This allows the liquid cooling system’s Power Usage Effectiveness (PUE) to be as low as 1.05–1.08, far superior to air cooling’s PUE of over 1.5.
| Sealing and Insulation: Robot joints require frequent rotation, making the sealing of liquid cooling pipelines paramount. Additionally, coolant leakage could cause motor short circuits, necessitating flawless insulation design. Tesla adopted a dual solution of “rotary sealing + insulating coolant”: the rotary joint uses ceramic sealing technology, offering a lifespan of over 100,000 cycles to meet the demands of long-term, high-frequency robot movements. The coolant is an electronic-grade fluorinated liquid, which is highly insulating and has a thermal conductivity three times that of traditional coolants, effectively addressing leakage risks.
Tesla has managed to control the cost of its liquid cooling system to $150–200 per unit, accounting for less than 5% of Optimus’s Bill of Materials (BOM) cost, laying the foundation for subsequent mass production.
Challenges Facing Humanoid Robot Liquid Cooling Systems
Despite the broad market prospects, the technical difficulty of the liquid cooling systems for humanoid robots is significantly higher than that of fixed scenarios like data centers, primarily due to three major challenges:
| Extreme Spatial Compatibility: Efficient heat dissipation must be achieved within extremely limited spaces (e.g., <5 cm³ for dexterous hand cooling modules), imposing millimeter-level requirements on miniaturized design, flow channel layout, and machining precision.
| Stringent Material Compatibility: Cooling components must coexist long-term with metal structures, lubricants, and circuits, requiring a balance of wear resistance, corrosion resistance, insulation, and chemical stability.
| Dynamic Thermal Management Precision: Joint movement generates transient and fluctuating thermal loads, requiring temperature control precision within ±1.5°C. This necessitates the integration of real-time sensors and intelligent flow algorithms to achieve dynamic responsiveness.’
| The maintenance cycle (e.g., 2 years) and failure rate (e.g., 0.1%) of liquid cooling systems must align with the overall lifespan of the robot (e.g., 5-10 years) to meet practical application requirements.
Applications of Liquid Cooling Systems for Humanoid Robots
Liquid cooling technology is extending from traditional data centers to the field of robotics, creating new market growth opportunities:
| In the humanoid robot sector, liquid cooling primarily targets high thermal-density components such as joint motors, AI computing units, and sensor systems. For instance, the joint motors of Tesla’s Optimus can exceed 500W in peak power, and the GPU/TPU chips in its AI computing unit also consume over 100W. These high-power components impose extremely demanding requirements for heat dissipation.
| In the industrialized robot sector, the lightweight biomimetic design of Hydraulic Drive Units (HDUs) is also opening new application scenarios for liquid cooling technology.
Development Directions for Humanoid Robot Liquid Cooling Systems
Material Innovation
Upgrading materials is key to improving liquid cooling efficiency and simplifying system structure.
| Promote the combination of graphene-based thermal interface materials (thermal conductivity 1500-2000 W/m·K) with micro-encapsulated phase change materials (particle size 5-22μm, embedding rate >70%). This can further enhance heat dissipation efficiency while reducing system complexity.
| Explore the application of flexible heat pipe technology (thermal conductivity up to 5000W/(m·K)) in confined spaces like finger joints, addressing the heat dissipation challenges of robotic end-effectors.
Structural Optimization
| The flow path structure of micro-channel cold plates is crucial. Designs like double-layer parallelogram pin-fins and trapezoidal channels significantly impact cooling performance. For instance, under the same heat flux density, a cold plate with a double-layer parallelogram pin-fin structure can have a maximum surface temperature 5.2°C lower than a single-layer version and 8.5°C lower than one with a rectangular channel design, although pressure drop increases accordingly. Finding the optimal balance between efficiency and pressure drop is necessary.
| Drawing inspiration from the fractal structure of human capillaries, develop biomimetic microvascular network designs, embedding 3D-printed micro-channel networks inside chips to further unlock cooling potential.
Intelligent Control
| Deepen the application of dynamic thermal management algorithms. For example, solutions based on deep reinforcement learning can predict thermal load using data on joint torque and ambient temperature/humidity, proactively adjusting coolant flow rate and compressing response time to within 10 seconds.
| Explore the integration of Physics-Informed Neural Networks (PINN) with Reinforcement Learning (RL) to make thermal load prediction and flow control more efficient, further reducing cooling energy consumption.
Market Scale of The Liquid Cooling Systems for Humanoid Robots
Multiple predictions indicate that the humanoid robot liquid cooling market will enter a phase of rapid growth between 2025 and 2030, achieving significant scale breakthroughs around 2030.
Tesla’s mass production plan for Optimus is the most important near-term market catalyst. Based on estimates of 5,000–10,000 units produced in 2025, with a liquid cooling value of $150–200 per unit, Optimus alone could create an incremental market of $100–200 million. Extrapolating from this point, global humanoid robot sales are expected to reach around 1 million units by 2030, corresponding to a liquid cooling market size potentially reaching $1.5 billion, with a projected Compound Annual Growth Rate (CAGR) of approximately 35% from 2025 to 2030.
More importantly, liquid cooling systems in humanoid robots have transitioned from an “optional configuration” to a “mandatory installation”—any humanoid robot with a power density exceeding 500W cannot bypass the support of liquid cooling technology.
Insight from AI Eidos Robots about Liquid Cooling Systems for Humanoid Robots
With technological advancements, humanoid robot liquid cooling systems will experience greater development.
| Thermal management, as a “secondary energy system”: In the future, liquid cooling systems for humanoid robots should not be viewed merely as cooling tools, but rather redefined as “precise thermal energy distribution and recovery networks.” The forward-looking perspective is that these systems can integrate thermoelectric conversion modules to convert waste heat from joints into a small amount of electrical energy to power low-power sensors, thus achieving “localized cycling” of energy and enhancing overall energy efficiency.
| The paradigm shift from “cooling” to “thermal shaping”: The goal of next-generation liquid cooling systems is not only to control temperature but also to achieve “thermal shaping”—optimizing material performance through active, programmable micro-zone temperature control. For instance, by precisely controlling the temperature of specific muscle-simulating actuators, the rigidity of their polymer materials can be altered, assisting in achieving more compliant and energy-efficient motion control.
| Cross-domain technology integration: Learning from biological thermoregulation mechanisms: In-depth research into mammalian blood circulation heat dissipation (such as heat loss through the ears) and gland evaporation cooling mechanisms can help develop bionic adaptive thermal regulation systems for humanoid robots. For example, developing flexible porous membranes that can controllably exude and evaporate cooling liquid at high temperatures and loads to achieve surface evaporation cooling.
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