新周期 新技术 新生态！ 12月19日， 由起点锂电、起点储能、起点研究院SPIR主办的 2025起点用户侧储能及电池技术论坛 （ 同期： 2025 （第十届）起点锂电行业年会暨锂电金鼎奖颁奖典礼&起点研究十周年庆典）在深圳市维纳斯皇家酒店正式举办！现场 800+嘉宾参会，聚焦工 商业储能、便携式储能、户用储能、AIDC储能电池等核心议题，前瞻解析技术突破、破题安全挑战与价值链重构。 在下午的 工商储及电池技术专场 ， 德赛电池 系统和算法总监 闫垚锋 发表了以《 主动安全 -重新定义能源安全范式-基于实时感知与智能响 应的下一代技术方案 》为主题的演讲！ 以下为现场速记内容： 各位合作伙伴、 行业 同仁，大家下午好！ 今天我们直奔新能源行业的核心话题，安全！当前行业里的 "七重防护"等尝试，大多是"等风险冒头再处置"：出问题了靠消防，故障了再排 查。但是储能隐患藏得深，这种被动方式很难提前拦截风险，大家做项目也依然有所顾虑。 我们今天带来的主动安全技术体系，思路完全不同，将介入点前移至风险萌芽期。传统方案看电芯表面，我们深入内部；传统侧重单点防护，我 们构建从感知到处置的闭环。每一步都为了更早发现、更快拦截 ...

Core Viewpoint - The battery industry is entering an "intelligent transformation era" at an unprecedented speed, driven by AI technology that is fundamentally reshaping research and development, manufacturing processes, and safety standards in the sector [5][9]. Group 1: AI-Driven Transformation - AI is no longer just a buzzword; it is deeply integrated into every aspect of the battery industry, from energy management to intelligent manufacturing [4][5]. - The traditional battery R&D process, which relies on "first principles," is being revolutionized by AI, allowing for the discovery of complex mathematical patterns from experimental data, thus enhancing efficiency [6][8]. - SES AI's "smart box" integrates supercomputing and multiple modules to cover the entire R&D process, significantly reducing resource consumption and accelerating production capacity [8][9]. Group 2: Industry Trends and Challenges - The energy bottleneck for AI-driven products has shifted from "insufficient capacity" to an overall upgrade in structure, materials, and battery management [9][11]. - The industry is moving towards maximizing the value of individual battery cells, focusing on increasing energy density while ensuring safety [11][12]. - The trend in the battery industry is towards "active safety" at the cell level, moving from passive monitoring to proactive measures that can detect potential risks early [17][18]. Group 3: Innovations and Applications - Companies like Penghui Energy are integrating AI into battery lifecycle management, utilizing advanced algorithms for predictive maintenance and operational efficiency [14][15]. - Yigan Technology is proposing a Battery Design Automation (BDA) approach to overcome the complexities in battery R&D, aiming to enhance precision and efficiency through a combination of physical simulation and AI [20][21]. - Dayun Technology emphasizes the importance of X-ray detection in ensuring battery safety, leveraging AI to enhance defect identification and quality assurance processes [26][27]. Group 4: Future Directions - The future of the battery industry will depend on the successful integration of digital quality, AI platformization, and private deployment to create a stable and iterative infrastructure [23][24]. - The industry is urged to build a data-sharing ecosystem to address data silos, which will enhance the application of AI technologies in quality control and other areas [27][28].