Enabling Physical AI: How LG Energy Solution Powers the Next Generation of Intelligent Systems

Supplementary Stories

Enabling Physical AI: How LG Energy Solution Powers the Next Generation of Intelligent Systems

• As physical AI continues to expand, energy emerges as the key that will shape system performance and scalability.
• LG Energy Solution is developing application-specific battery solutions to address the diverse requirements of robotics, drones, and UAM.

From robotics and drones to urban air mobility (UAM), AI is accelerating a shift across industries, moving beyond digital environments into physical AI capable of perception, reasoning, and action in real-world environments.

The World Economic Forum defines physical AI as a combination of advances in AI, robotics, and sensing technologies that enable machines to operate autonomously in physical settings. McKinsey & Company notes that recent work in the field is opening new possibilities for these robots to interact directly with the physical world.

The growing sophistication of physical AI also brings more demanding requirements, extending beyond computing performance to include operating time, safety, and reliability. Battery technology sits at the center of those needs as critical infrastructure supporting continuous and stable operation.

In this context, the ability to deliver sufficient energy is critical. When battery energy density and performance fall short, physical AI systems face limitations in operating time and overall efficiency.

Across sectors, energy autonomy is consistently identified as the key that determines the capability, reliability, and scalability of physical AI systems. However, as physical AI spans a diverse range of applications, battery requirements can vary significantly depending on operating environments and use cases.

To address these requirements, LG Energy Solution is developing application-specific battery solutions tailored to the different needs of physical AI systems.

In the robotics sector, LG Energy Solution's broad battery portfolio offers optimized solutions based on each specific robot type. Within the humanoid robot segment, the company is advancing both cell- and pack-level technologies to enable stable, high-performance operation in practical scenarios.

At the cell level, LG Energy Solution is using high-capacity, long-life 2170 cylindrical batteries to support the early expansion of the humanoid robotics market. With a strong balance of energy density and durability, these cells are well-suited to continuous operation and repetitive motion. The company also plans to introduce next-generation all-solid-state batteries (ASSBs) to further enhance performance and support wider adoption of high-performance humanoid robots.

To maximize operational continuity and safety, LG Energy Solution is developing robot-specific battery pack technologies, including hot-swappable battery systems that enable seamless battery replacement without interruption. Advanced safety-focused designs also feature immersion cooling-based battery packs to improve thermal management and stability.

In autonomous service robotics, LG Energy Solution entered a partnership with Bear Robotics, providing advanced materials, including high-quality NCMA cathodes and reinforced ceramic-coated separators, to ensure high levels of safety and performance. Similarly, LG Electronics' home service robot LG CLOiD uses LG Energy Solution's high-performance cylindrical batteries, supporting longer operation time, improved efficiency, and enhanced thermal stability.

Beyond robotics, LG Energy Solution batteries are also applied to drones for blood delivery and CubeSat satellites. In these use cases, both high power output and a lightweight design are essential. Achieving a lightweight form factor requires the use of high energy density materials in the cell design.

Building on its extensive battery technology and collaborations with leading robotics and UAM partners, LG Energy Solution is further strengthening its role as a key energy solution partner to accelerate the commercialization of physical AI.

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