年末"翘尾效应"缺席，有利于 2026 年车市实现开门红 11 月乘用车批发量同比/环比增长 1.2%/2.6%至 304 万台，而上险量仅 203 万台，延续 10 月以来的同环比双降趋势，整体呈现高基数背景下的四季度 减速特征。叠加车企被动加库存行为，11 月行业库存水平进一步上行。 汽车行业 – 汽车 | 消息快报 2025 年 12 月 16 日 汽车行业 2026 年汽车行业展望：稳内需主基调明确；出口贡献 确定性增长亮点 展望 12 月，我们预计终端零售同比降幅可能会进一步加大，其核心原因在 于：（1）去年同期基数较高，（2）各地方 2025 年"两新"消费补贴从 9- 10 月开始陆续结束或暂停，政策拉动效应明显减弱，消费者在 2026 年补贴 政策落地之前持币待购，观望情绪浓厚。根据我们的渠道调研，双 11 之 后，全国大部分地区基本全面退出以旧换新补贴政策额度，11 月日均补贴规 模已降至 3 万左右。 纵观今年全年，由于"两新"补贴政策对前期车市起到了显著的逆周期刺激 效果，今年国内乘用车市场大致呈现"前高后稳、四季度承压"的特征。尽 管此前市场普遍预期，由于 2026 年起购置税优惠将减 ...

Core Viewpoint - The acquisition of Precision Energy by Longi Green Energy raises concerns about whether energy storage will become the next "photovoltaic" industry, especially given the historical price drops and competitive pressures seen in both sectors [1][3][19]. Industry Comparison - Energy storage has not experienced the same level of widespread losses across the entire industry as seen in photovoltaics, with leading companies maintaining strong profit margins despite competitive pressures [3][4][5]. - For instance, CATL's energy storage cell gross margin remains around 27%, while Sungrow's system gross margin is close to 40% [3][4]. - Tesla, despite not manufacturing cells or inverters, has consistently achieved over 30% gross margin on its energy storage systems [5]. Market Dynamics - The energy storage market is showing signs of "de-photovoltaicization," indicating a divergence in the paths of the two industries [6]. - The fundamental differences between energy storage systems and photovoltaic components lie in their risk profiles and operational complexities, with energy storage being a high-risk, non-linear, and highly integrated system [7][8]. Operational Challenges - Energy storage systems require more intensive maintenance compared to photovoltaic systems, which can lead to operational failures if not managed properly [9][10]. - Reports indicate that at least 20% of energy storage plants are underperforming, highlighting potential operational risks as the industry matures [9]. Technological Evolution - The shift towards software-defined energy storage systems is crucial, as the integration of advanced algorithms and management strategies can significantly enhance performance and longevity [13][16]. - Companies that can effectively manage data and operational strategies will have a competitive edge, making price competition less relevant [17]. Future Outlook - The industry must avoid a return to price wars that could undermine the value of energy storage as a high-end system asset [20]. - The focus should be on capturing "invisible value" through differentiation in technology and operational excellence rather than merely competing on hardware prices [20].

Core Insights - The 32nd China Society of Automotive Engineers Annual Conference and Exhibition (SAECCE2025) will be held from October 22 to 24 in Chongqing, focusing on the release of the "Energy-saving and New Energy Vehicle Technology Roadmap 3.0" and addressing industry hot topics [1][6] Group 1: Major Systemic Transformations in the Automotive Industry - The automotive industry in China is undergoing a comprehensive transformation driven by low-carbon, electrification, and intelligence, marking a shift in five major systems: technology, innovation, product, industry, and market [2] - The technology system has evolved from a mechanical engineering focus to a new paradigm integrating low-carbon, electrification, and intelligence, with vehicles becoming super intelligent mobile terminals [2] - The innovation system has transitioned from linear "chain R&D" to a networked structure empowered by AI, enhancing efficiency across the entire process from demand insight to product definition [2] Group 2: Product and Market Dynamics - The product system is shifting from primarily fuel vehicles to new energy vehicles, with sales projected to reach 12.866 million units in 2024, and market penetration increasing from 0.3% in 2014 to 40.9% [3] - The market system is transitioning from reliance on domestic growth to global expansion, with exports reaching 4.292 million vehicles in the first eight months of 2025, a 13.7% increase year-on-year, and new energy vehicle exports growing by 87.3% [3] Group 3: Highlights of the Conference - The conference will feature over 130 activities focusing on six major technology areas, with participation expected to exceed 10,000 attendees, including representatives from 200 exhibiting companies [4] - The event will emphasize the integration of AI in automotive applications, showcasing its role in transforming vehicles into "embodied intelligent agents" [5] - An international committee will be established to enhance global collaboration, with multiple international forums planned to elevate the conference's international profile [5]

Group 1 - The core viewpoint of the article emphasizes the transformation of traditional luxury automotive brands like Mercedes into software-centric companies, reflecting the broader changes in the semiconductor industry driven by AI and software [1][4][6] - Siemens EDA's annual technology summit highlighted the industry's challenges, including project delays and declining first-pass success rates, while projecting semiconductor industry revenue to reach $1 trillion to $1.2 trillion by 2030, with transistor counts exceeding 1 trillion [4][6] - The introduction of "software-defined, AI-empowered, chip-enabled" strategies by Siemens EDA signifies a profound insight into industry trends, with a notable emphasis on the increasing importance of AI in Electronic Design Automation (EDA) [4][7] Group 2 - The concept of "software-defined" in the semiconductor industry indicates a shift from hardware-centric approaches to software-driven differentiation, necessitating a change in design methodologies to incorporate software considerations early in the design process [6][9] - AI's role in EDA is characterized by its industrial-grade applications, focusing on five key features: verifiability, usability, universality, robustness, and accuracy, which are essential for ensuring reliable chip design [7][8] - Siemens EDA's development of a comprehensive digital twin system aims to support the entire digital ecosystem, integrating various design and verification processes across multiple domains, thereby enhancing the overall design and production lifecycle [9][10]