证券日报网讯 2月6日，中国汽研在互动平台回答投资者提问时表示，公司投资建设的华东总部基地 2025年6月开园，目前重点推进实验设备的安装与联调工作，预计设备调试与资质核验完成后，产能将 逐步释放，进而助力长三角区域汽车产业实现高质量发展，成为华东地区智能网联新能源汽车产业发展 与共性技术推广的公共服务平台。 （文章来源：证券日报） ...

Core Viewpoint - The automotive industry in China is steadily advancing towards an era characterized by electrification, intelligence, low carbon emissions, and internationalization, with a continuous increase in the number of new products as indicated by the Ministry of Industry and Information Technology's announcements [1] Group 1: Industry Trends - The demand for technology services in the automotive sector is consistently growing, driven by the industry's transition towards new technological paradigms [1] - The number of new products in the automotive sector is on the rise, reflecting a positive trend in the industry [1] Group 2: Company Strategy - The company plans to focus on three main technological lines: safety, green technology, and user experience, while increasing research and development investments [1] - The company aims to strengthen customer collaboration and market expansion, concentrating on its core business and emerging sectors [1] - The company is committed to enhancing business synergy across various segments to improve its technological innovation and operational capabilities, thereby elevating its market position [1]

证券日报网讯 2月6日，中国汽研在互动平台回答投资者提问时表示，公司新增折旧摊销情况请以公司 后续公告披露信息为准。 （文章来源：证券日报） ...

国家知识产权局信息显示，中国汽车工程研究院股份有限公司;北京链宇科技有限责任公司申请一项名 为"评估动力电池健康状态的方法、装置和存储介质"的专利，公开号CN121454333A，申请日期为2025 年10月。 专利摘要显示，本申请涉及电数字数据处理领域，提供了评估动力电池健康状态的方法、装置和存储介 质。所述方法包括：执行全容量循环测试，基于动力电池的实际容量计算容量型健康状态SOH_C；执 行增量容量分析测试，基于增量容量曲线计算增量容量分析健康状态SOH_ICA；执行混合脉冲功率特 性测试，以基于直流内阻计算功率型健康状态SOH_P；在全容量循环测试、增量容量分析测试和混合 脉冲功率特性测试中的至少一个测试过程中，通过电池管理系统BMS通信单元实时记录动力电池的 BMS数据，并对BMS数据进行分析以获取一致性参数；基于SOH_C、SOH_ICA、SOH_P和一致性参 数，进行数据融合与综合健康状态评估，输出综合SOH评估结果。本申请的对动力电池SOH进行全面、 精准和可诊断的综合评估。 天眼查资料显示，中国汽车工程研究院股份有限公司，成立于2001年，位于重庆市，是一家以从事专业 技术服务业为主的企业。 ...

- The report introduces a quantitative model framework for market trend analysis, focusing on five asset style stages: external growth, quality growth, quality dividend, value dividend, and bankruptcy value. The model evaluates assets based on their intrinsic attributes and prioritizes them using the sequence of g > ROE > D, analyzing whether there are "good assets" and whether they are "expensive" [5][8][9] - The model incorporates key factors such as expected growth (gf), actual growth (g), profitability (ROE), high dividend (D), and bankruptcy value (B/P). Each factor is associated with specific market phases, e.g., expected growth is relevant across all phases, while profitability is emphasized during maturity phases [9][12] - The quantitative model has demonstrated strong historical performance, achieving an annualized return of 27.67% since 2009. It has shown consistent excess returns in most years, particularly post-2017, with limited effectiveness in years like 2011, 2012, and 2016 [19][22] - The model's backtesting results for specific years include notable excess returns, such as 51% in 2009, 36% in 2013, and 62% in 2022. However, it also recorded underperformance in years like 2011 (-11%) and 2014 (-4%) [22] - The report details six specific strategies derived from the model, each focusing on different factors: - **Expected Growth Strategy**: Selects industries with the highest analyst-forecasted growth rates. Recent recommendations include sectors like automotive sales, lithium equipment, and tungsten [38][39] - **Actual Growth Strategy**: Focuses on industries with the highest unexpected growth (△g). Current recommendations include photovoltaic equipment, insurance, and coal chemical sectors [40][41] - **Profitability Strategy**: Targets high-ROE industries with low valuations under the PB-ROE framework. Recommended sectors include copper, liquor, and non-dairy beverages [43][44] - **Quality Dividend Strategy**: Utilizes a DP+ROE scoring system to identify industries. Current recommendations include forestry, lithium equipment, and fiberglass [46][47] - **Value Dividend Strategy**: Employs a DP+BP scoring system. Recommended sectors include security, daily chemicals, and buses [49][50] - **Bankruptcy Value Strategy**: Focuses on industries with the lowest PB+SIZE scores. Current recommendations include automotive sales, ceramics, and cotton textiles [53][54]

[Table_Page] 公司深度研究|汽车服务 [Table_Title] 中国汽研（601965.SH） 卡位稀缺，受益于中国汽车标准做大做强 [Table_Summary] 核心观点： 盈利预测： | [Table_ 单位 Finance] :人民币百万元 | 2023A | 2024A | 2025E | 2026E | 2027E | | --- | --- | --- | --- | --- | --- | | 营业收入 | 4,007 | 4,697 | 4,967 | 5,866 | 7,171 | | 增长率（ % ） | 21.8% | 17.2% | 5.8% | 18.1% | 22.3% | | EBITDA | 1,306 | 1,678 | 1,956 | 2,278 | 2,673 | | 归母净利润 | 825 | 908 | 1,060 | 1,216 | 1,466 | | 增长率（ % ） | 19.7% | 10.0% | 16.8% | 14.7% | 20.6% | | EPS（元/股） | 0.82 | 0.90 | 1.06 | 1.21 | 1.46 | | ...

Core Insights - The safety and reliability requirements for core components of new energy vehicles (NEVs) are significantly higher than those of traditional fuel vehicles, driving demand for battery management system testing equipment and motor controller efficiency testing platforms as NEV penetration continues to rise [1][6] - The market for automotive electronic intelligent testing equipment in China is projected to reach 11.75 billion yuan by 2025, with a year-on-year growth of 13.3%, as NEVs evolve towards higher endurance, intelligence, and safety [1][6] Overview - Automotive electronic intelligent testing equipment integrates technologies such as electronic measurement, computer vision, artificial intelligence, IoT, and automation to test the performance, functionality, fault diagnosis, and quality of automotive electronic components and systems [2][3] - This equipment can automate high-precision testing processes, simulating full operational environments to identify performance defects and compatibility issues, making it essential for ensuring the reliability of automotive electronic products [2][3] Industry Barriers - The automotive electronic intelligent testing equipment industry has significant technical barriers due to its multidisciplinary nature, requiring companies to possess extensive knowledge across various fields and the ability to engineer complex technologies [3][4] - There are strict customer entry barriers, as downstream manufacturers demand high product quality and supply chain stability, leading to long-term partnerships once a supplier is integrated into the supply chain [4] Industry Chain - The upstream of the automotive electronic intelligent testing equipment industry includes suppliers of precision mechanical components, chips, sensors, and software services, while the midstream involves R&D and production, and the downstream consists of automotive manufacturers and third-party testing institutions [4][5] Current Development - The demand for intelligent testing equipment is increasing due to the rising safety and reliability requirements of NEV components, with high-end testing equipment becoming essential for R&D and mass production [1][6] Competitive Landscape - The market is structured in three tiers: international giants dominate the high-end market, domestic leaders are emerging as challengers, and regional manufacturers fill niche segments [7][8] - Leading companies include international firms like Keysight Technologies and domestic firms such as Beijing Oriental Zhongke and Hangzhou Wolai Intelligent Technology, which leverage cost advantages and rapid service response to capture market share [8] Development Trends - The industry is moving towards system-level and intelligent integration, with testing needs evolving from single-component tests to integrated system-level tests [10] - Domestic manufacturers are accelerating their penetration into high-end markets, driven by policy support and collaboration within the domestic supply chain [11] - Service models are evolving from single testing to comprehensive lifecycle solutions, enhancing product performance through customized testing and data analysis [12]

Market Overview - The automotive service sector experienced a decline of 1.73% on February 2, with 德众汽车 leading the drop [1] - The Shanghai Composite Index closed at 4015.75, down 2.48%, while the Shenzhen Component Index closed at 13824.35, down 2.69% [1] Stock Performance - Notable stock performances included 阿尔特, which rose by 3.60% to a closing price of 10.06, with a trading volume of 215,400 shares and a transaction value of 217 million [1] - 德众汽车 fell by 3.26% to a closing price of 6.53, with a trading volume of 26,700 shares and a transaction value of 17.72 million [2] - Other significant declines included 中国汽研, down 2.96% to 18.39, and 国机汽车, down 2.42% to 6.45 [2] Capital Flow - The automotive service sector saw a net inflow of 11.33 million from institutional investors, while retail investors experienced a net outflow of 40.06 million [2] - The sector's overall capital flow indicated that retail investors were withdrawing funds, contrasting with the inflow from institutional and speculative investors [3] Individual Stock Capital Flow - 阿尔特 had a net outflow of 35.82 million from institutional investors, while speculative investors contributed a net inflow of 6.11 million [3] - 德众汽车 faced a significant net outflow of 1.63 million from institutional investors, indicating weak institutional interest [3] - 中国汽研 saw a net inflow of 1.87 million from institutional investors, suggesting a relatively stable interest from this segment [3]

截至9月30日，中国汽研股东户数2.16万，较上期增加18.75%；人均流通股46048股，较上期减少 15.79%。2025年1月-9月，中国汽研实现营业收入30.24亿元，同比减少0.76%；归母净利润6.66亿元，同 比减少0.56%。 1月30日，中国汽研跌1.35%，成交额2.42亿元。两融数据显示，当日中国汽研获融资买入额1842.55万 元，融资偿还2023.22万元，融资净买入-180.68万元。截至1月30日，中国汽研融资融券余额合计2.18亿 元。 融资方面，中国汽研当日融资买入1842.55万元。当前融资余额2.13亿元，占流通市值的1.13%，融资余 额超过近一年90%分位水平，处于高位。 融券方面，中国汽研1月30日融券偿还3300.00股，融券卖出800.00股，按当日收盘价计算，卖出金额 1.52万元；融券余量24.55万股，融券余额465.22万元，超过近一年90%分位水平，处于高位。 资料显示，中国汽车工程研究院股份有限公司位于重庆市北部新区金渝大道9号，成立日期2001年1月11 日，上市日期2012年6月11日，公司主营业务涉及汽车技术服务和装备制造业务。主营业务收入构成 ...

| 代码 | 名称 | 收盘价 | 涨跌幅 | 成交量(手) | 成交额(元) | | --- | --- | --- | --- | --- | --- | | 600653 | 申博控股 | 1.92 | 0.00% | 21.97万 | 4219.28万 | | 000757 | 浩物股份 | 5.13 | -0.19% | 8.64万 | 4450.85万 | | 600386 | 北巴传媒 | 4.57 | -0.44% | 10.28万 | 4724.27万 | | 301215 | 中汽股份 | 6.98 | -1.41% | 14.90万 | 1.05亿 | | 300825 | 阿尔特 | 9.88 | -1.59% | 9.35万 | 9339.39万 | | 600676 | 交运股份 | 7.73 | -1.78% | 38.40万 | 3.01亿 | | 000701 | 厦门信达 | 6.29 | -2.02% | 19.61万 | 1.25亿 | | 600822 | 上海物贸 | 10.97 | -2.23% | 7.30万 | 8082.56万 | | 600335 | 国机 ...