孚能科技（688567.SH）：攻克电池寿命验证瓶颈，有望加速产品研发迭代

Core Viewpoint - The recent publication of the research paper "Discovery Learning predicts battery cycle life from minimal experiments" by Fulin Technology and a professor from the University of Michigan introduces a groundbreaking machine learning method that significantly reduces the time and energy required for battery life validation, addressing high development costs and long cycles in battery development [1][3][4]. Group 1: Discovery Learning Method - The "Discovery Learning" method compresses traditional battery life validation to 33 days and 0.468 MWh, saving 98% of time and 95% of energy, thus shortening the R&D cycle from years to months [3]. - Only 51% of the prototype's first 50 cycle data is needed to achieve results that exceed current mainstream methods, significantly reducing trial and error costs in R&D and manufacturing [3]. Group 2: Impact on Fulin Technology - The introduction of "Discovery Learning" not only represents a technological breakthrough but is also closely linked to the overall development of Fulin Technology, enhancing its competitiveness in the battery technology R&D field [4]. - Fulin Technology has established a flexible manufacturing platform capable of commercializing various battery types and materials, including high-nickel ternary, lithium iron phosphate, and sodium-ion batteries [3][4]. Group 3: Future Directions and Market Position - Solid-state batteries are viewed as the next core direction for power batteries, with Fulin Technology aiming to lead in this area through extensive R&D and industrialization efforts [5]. - The company has developed a diverse and high-quality customer ecosystem, including major clients such as GAC, Dongfeng, and a leading eVTOL company, which positions it well to expand market share and strengthen growth [5][6]. - Fulin Technology plans to continue its innovation-driven development approach, deepening collaborations with top research institutions and integrating cutting-edge technologies into its multi-material battery R&D and production processes [6].