Recently, Peking University’s School of Advanced Materials, in collaboration with Shenzhen Eacomp Technology and other partners, has advanced industry-academia-research cooperation by proposing an AI-driven next-generation Lithium-Ion Battery Design Automation (BDA) software architecture and reporting its development progress. The related review paper was published in China’s authoritative academic journal National Science Open. This milestone signifies that China has taken the global lead in establishing a new battery R&D paradigm centered on the integration of artificial intelligence with multi-scale physical simulations. It injects strong “China-powered” momentum into the global renewable energy industry upgrade.

AI-Driven Next-generation Lithium-Ion Battery Design Automation (BDA) Software

1. Research Background

Artificial intelligence (AI), as the core driving force of the new wave of technological revolution and industrial transformation, is reshaping industrial patterns worldwide. General Secretary Xi Jinping has explicitly emphasized that AI is a strategic technology leading this round of scientific and technological revolution, exhibiting a significant “lead goose” effect. Currently, China’s AI industry has surpassed a scale of 900 billion RMB, demonstrating strong growth momentum. Whether the current AI wave can overcome the historical challenge of “shifting away from the real economy toward the virtual” depends critically on its deep integration with the manufacturing sector. As the foundation of national development and the cornerstone of a strong country, manufacturing represents the primary battlefield for the practical application of AI technologies.

The AI wave

Currently, the global energy structure is accelerating its transition toward clean and low-carbon sources. China has already achieved a leading position worldwide in both advanced technologies and shipment volumes in the new energy sector. As the core carrier of electrochemical energy storage, lithium-ion batteries (LIBs) play a critical role, as breakthroughs in their performance and development efficiency directly affect national energy security and industrial competitiveness. According to information released by the Ministry of Industry and Information Technology (MIIT) in February, based on industry-standard enterprise data and industry association estimates, domestic lithium-ion battery shipments are expected to reach 1,170 GWh in 2024, with the total industry output exceeding 1.2 trillion RMB.

However, mainstream LIBs in current industrial applications have approached their theoretical limits in energy density. Next-generation lithium-metal battery (LMB) systems, which hold ultra-high energy density potential (>500 Wh/kg), face significant challenges. These include safety risks such as lithium deposition and dendrite growth during fast charging, as well as poor environmental adaptability and capacity degradation. These inherent difficulties stem from the complexity of the LIB development process. Although China is already the world’s largest producer and consumer of lithium-ion batteries, the R&D phase still relies heavily on experimental trial-and-error, confronting formidable “cross-scale, long-process, multi-factor” challenges in new energy research. This underscores an urgent need for artificial intelligence to drive innovative breakthroughs in battery development paradigms.

multi-scale, long-process, multi-factor challenges in battery R&D

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2. A New Paradigm for Battery Design Automation (BDA)

Looking across the history of global industrial transformation, Electronic Design Automation (EDA) software ushered semiconductor development into a digital and automated era, significantly improving chip R&D efficiency and strongly supporting the industry’s rapid growth.

Similarly, the new Battery Design Automation (BDA) paradigm, developed jointly by Eacomp Technology and Peking University, leverages the deep integration of multi-scale simulations with artificial intelligence algorithms to establish a fully intelligent R&D platform spanning from atomic-level materials design to system-level performance prediction.

At the microscopic level, the platform can precisely elucidate material mechanisms; at the mesoscopic level, it enables optimized electrode structure design; and at the macroscopic level, it allows scientific prediction of full-cell performance. This forms an efficient automated “design–simulate–validate” closed-loop system. Research shows that this paradigm can not only significantly enhance the safety and energy density of existing battery products but also dramatically shorten the development cycle of next-generation battery technologies—just as EDA revolutionized chip design—bringing battery R&D into a digital, automated, and intelligent era and providing strong support for industrial technology upgrading.

Battery Design Automation (BDA) software

The breakthroughs in BDA technology represent a vivid example of China’s commitment to staying at the forefront of global science and technology while focusing on key economic sectors. They also constitute an important achievement in enhancing the overall effectiveness of the nation’s strategic scientific and technological capabilities. By providing a “new-quality productivity” tool for the upgrading of China’s new energy industry, BDA technology helps the sector transition from a “scale-based manufacturing advantage” to a “core-technology advantage,” thereby sustaining long-term leadership in the global market.

multi-scale parameter transfer and intelligent coupling

3. Outlook

As an emerging technological force within China’s national strategic framework, Eacomp Technology consistently upholds both idealism and a sense of social mission. Leveraging the robust innovation and entrepreneurship ecosystem in Nanshan, Shenzhen, Eacomp Technology fully harnesses its core technological and engineering capabilities and collaborates closely with Peking University’s top-tier research teams to establish a dual-driven model of “academic exploration + industrial incubation.” Actively implementing the “artificial intelligence + manufacturing” approach, the company addresses critical bottlenecks in battery design through a new paradigm that integrates multi-scale physical simulation with AI, developing truly practical BDA software. This innovation path, deeply rooted in the real economy, not only aligns with the strategic direction of advancing new industrialization but also further strengthens and enhances the core competitiveness of China’s new energy industry.

The new BDA paradigm