Intellectual Property in Battery Cell Production: A Step-By-Step Regional Analysis
Authors: Greitemeier Tim , Lux Simon 
Published: December 2024

The decision to establish lithium-ion batteries (LIBs) as the technology of choice for electric vehicles (EVs) led to a remarkable and continuous growth in global demand for LIBs, further driven by the promotion of low-carbon transport. This promotion stimulated numerous technological innovations along the cell production value chain of LIBs, building on the implicit and explicit knowledge of the stakeholders in the sector. The assessment of this knowledge is enabled by data science methods that analyze innovative intellectual property (IP) and specialized Know-How, offering acceleration of development and cost savings. While previous data science approaches have focused on either materials in LIBs or holistic approaches to EVs, a void remains in the analysis of LIB cell production patents and the identification of less pronounced technology areas and potential white spots along the value chain. This work aims to address this void by identifying development pathways and investment opportunities for stakeholders and policy makers in LIB cell production. To achieve this, a new patent-based analysis framework is implemented, which addresses three sub-questions. First (1), the technological maturity of the state-of-the-art production processes from a regional perspective. Secondly (2), the international patenting trends to identify processes with the greatest potential for innovation. Finally (3), a network analysis approach to qualitatively assess the impact and competitiveness of various regions within each process and along the entire cell production value chain.
To conduct the quantitative analysis, patent data from 1989 to 2023 was gathered and keywords were used to classify each cell production step. The patent quality was determined by calculating the mean eigenvector centralities for each region from the generated process-dependent networks. Eigenvector centralities are a valuable tool for gauging the impact of patents, as they describe the extent of connections between a single patent and other patents in the network.
The study's results answered each sub-question, showing that (1) Japan’s technology lead was reversed after 2008 and overtaken by China in total patent numbers in 2018. Japan's former leadership and pioneering role in this field is reflected by a significant number of patents granted since 1993. In 2021, China holds the dominant position in technology patents across the whole production value chain with a share of 49%, witnessing the highest growth rate internationally since 2014. Moreover, the findings demonstrate (2) a maturation in the component production, expressed by a decrease in annual patenting, accompanied by a steady increase in patents for cell assembly processes to this date. The conditioning processes of the LIBs were identified as the most promising steps for innovation, with high potential to reduce costs and energy consumption. Finally, the qualitative analysis revealed (3) that the United States and Japan possess the broadest IP portfolios with the highest impact. The impact of China’s patent portfolio seems to be limited to partial connections within individual processes, thereby suggesting a preference on targeted innovations in one production step.
In conclusion, this work has enabled the assessment of the state-of-the-art LIB cell production and identified technology areas and white spots. It will assist stakeholders and policy makers in selecting potential investments that can give them a competitive edge over other entities in the LIB market. In future work, the emphasis will be on the component production by implementing an analysis of the dry coating landscape. The introduction of dry coating can potentially eliminate the drying step, which is a major contributor to costs and energy consumption. Patent analysis will be adapted to evaluate trends in the key processes and the respective companies and institutions in this technology area.