AI数据中心，转向800V直流电力架构

半导体产业纵横01-27

公众号记得加星标⭐️，第一时间推送不会错过。一座AI工厂可集成数千块GPU，功耗水平达到兆瓦级。人工智能模型的广泛应用正推动数据中心基础设施迎来重构。传统数据中心正逐步被 “AI工厂” 取代，这类设施专为满足当今机器学习和生成式AI工作负载对计算能力与电力供应的需求而设计。传统数据中心依赖以CPU为核心的架构，支撑云计算、数据存储及通用计算需求。然而，随着大型语言模型和生成式AI应用的问世，该架构...

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取代，这类设施专为满足当今机器学习和生成式AI工作负载对计算能力与电力供应的需求而设计。传统数据中心依赖以CPU为核心的架构，支撑云计算、数据存储及通用计算需求。然而，随着大型语言模型和生成式AI应用的问世，该架构已无法跟上AI模型对计算能力、功率密度及供电效率日益增长的需求。相比之下，AI工厂是为机器学习模型的大规模训练、推理和微调量身打造的专用设施。一座AI工厂可集成数千块GPU，功耗水平达到兆瓦级。根据国际能源署（IEA）的报告，全球数据中心耗电量预计将从2024年的约 415 太瓦时（TWh）增至 2030 年的约 945 太瓦时，占全球总耗电量的比重接近 3%。仅通过简单升级数据中心，已无法满足如此庞大的电力需求。因此，必须引入一种兼具高效率与高功率密度的新型架构。借鉴汽车行业已有的技术趋势，英伟达在2025年台北国际电脑展（Computex 2025）上推出了800V直流（800-VDC）供电架构，旨在高效支撑下一代AI工厂计算机架所需的兆瓦级电力需求。AI工厂的电力需求特征AI工厂的电力需求与传统数据中心存在显著差异。由于部署了大量GPU，AI工厂的架构需满足高功率密度、低延迟和大带宽三大核心要求。为最大化计算吞吐量，需在更小空间内集成更多 GPU，并通过高速铜质链路实现互联。这不可避免地导致单机架功耗大幅攀升，传统数据中心单机架功耗仅数十千瓦，而AI工厂单机架功耗可达数百千瓦。若采用 12 伏、48 伏、54 伏等传统低压供电轨传输如此高的电流，在技术和经济上均不现实。如以下公式所示，电阻损耗（Presistive loss）随电流平方呈指数增长（P= V × I = R × I²），这会导致效率显著下降，且需要使用横截面积极大的铜质连接线。为实现多GPU间的高速互联，英伟达研发了 NVLink 点对点互联系统。该系统已迭代至第五代，支持数千块GPU共享内存和计算资源，协同完成训练与推理任务，仿佛运行在同一地址空间内。基于 Blackwell 架构的单块英伟达 GPU支持多达18个NVLink 连接，速度为 100 GB/s，总带宽达 1.8 TB/s，是上一代产品的2倍，较 PCIe Gen5 高出14倍。800V直流供电架构传统数据中心的配电系统通常包含多级级联的电力转换环节，包括市电中压交流（MVAC）、低压交流（LVAC）、不间断电源（UPS）和配电单元（PDU）。在 IT 机架内部，多个电源供应单元（PSU）先完成AC-to-DC转换，再在计算托盘上进行最终的DC-to-DC转换（如 54 伏直流转 12 伏直流）。这种架构效率低下，主要源于三方面问题：一是每级转换都会产生损耗，限制整体效率；二是低压供电轨需传输大电流，要求配备大型铜质母线和连接器；三是三相交流电源的管理（包括相位平衡和无功功率补偿）设计复杂。相比之下，采用800V直流供电主干网可最大限度降低 I²R 电阻损耗。将行业标准高压上限翻倍至800V直流后，系统在输出相同功率的情况下，电流可减半（P = V × I）。对于给定导体电阻，电力损耗可降至原来的四分之一。采用该方案后，下一代AI工厂将在IT数据大厅外设置集中式一级交流 - 直流转换系统，直接将中压交流转换为稳定的800V直流母线电压。随后，800伏直流可通过更简洁的双导体直流母线槽（正极和回路）直接分配至计算机架，省去了交流开关设备、低压交流 PDU 以及机架内效率低下的交流 - 直流电源供应单元。英伟达的Kyber机架架构专为适配这种简化母线设计。机架内的电力转换简化为单级高比率直流 - 直流转换（800伏直流转GPU所需的 12 伏直流轨），通常采用高效的 LLC 谐振转换器。这种后端转换方式最大限度减少了电阻损耗，为机架内计算设备腾出更多空间，并改善了热管理效果。该方案还能在现有基础设施基础上，将单机架供电能力从当前的 100 千瓦扩展至 1 兆瓦以上，确保AI工厂的供电基础设施能够满足未来GPU能耗增长的需求。此外，800V直流架构还能缓解同步AI工作负载的波动性。这类负载具有短时高功率尖峰特征。机架附近部署的超级电容器可衰减亚秒级峰值，而连接至直流母线的电池储能系统则能应对秒级至分钟级的功率波动，使AI工厂的电力需求与电网稳定性要求解耦。宽禁带半导体的核心作用800V直流架构的落地，可充分借助碳化硅和氮化镓等宽禁带半导体的卓越性能与效率优势。碳化硅 MOSFET 是高压前端转换环节的首选技术。碳化硅器件的额定电压通常为 1200 伏及以上，在该电压等级下，即便工作在中等开关频率，也比硅基器件具有更高的击穿电压和更低的导通损耗。其成熟度和稳定性使其成为数据中心主电源输入环节的理想选择。而GaN HEMTs适用于 IT 机架内的高密度、高频直流 - 直流转换环节（如800V直流转 54 伏直流或 54 伏直流转 12 伏直流）。氮化镓的材料特性使其开关频率可达到兆赫兹级别。这种高频工作特性允许使用更小的无源组件（电感器和电容器），从而减小转换器的尺寸、重量和体积。基于氮化镓的转换器已实现超过 4.2 kW/l的功率密度，确保必要的电力转换环节能够适配GPU负载附近有限的物理空间，最大化计算能力与供电效率的比值。市场成熟度与产业链支持元器件制造商、系统集成商和硅基器件供应商等半导体企业，正与英伟达积极合作，开发涵盖碳化硅、氮化镓及专用硅基元器件的完整产品组合，为800V直流架构的转型提供供应链支持。例如，专注于先进氮化镓解决方案的EPC公司推出 EPC91123 评估板 —— 这是一款紧凑型氮化镓基 6 千瓦转换器，专为新兴AI数据中心向800V直流配电转型而设计。该转换器采用输入串联 - 输出并联（ISOP）配置的 LLC 拓扑结构，将800V直流降压至 12.5 伏直流。其氮化镓设计实现了高功率密度，占地面积不足 5000 平方毫米，高度仅 8 毫米，非常适合高密度封装的服务器主板。将转换环节靠近负载部署，可减少电力损耗并提升整体效率。同时提供碳化硅和氮化镓器件的纳微半导体也与英伟达合作，为新兴的 Kyber 机架平台开发800V直流架构。该系统采用纳微半导体的 GaNFast、GaNSafe 和 GeneSiC 技术，提供适配高负载AI工作负载的高效、可扩展供电方案。纳微半导体推出了采用双侧冷却封装的 100 伏氮化镓场效应晶体管，适用于GPU电源板上的低压直流 - 直流转换环节；同时推出了全新系列的 650 伏氮化镓场效应晶体管和 GaNSafe 功率集成电路，集成了控制、驱动、传感和内置保护功能。此外，基于该公司专有沟槽辅助平面技术的 GeneSiC 器件，电压范围覆盖 650 伏至 6500 伏（为行业最宽范围之一），已应用于多个兆瓦级储能系统和并网逆变器项目。AOS也提供适用于AI工厂800V直流架构高要求电力转换环节的元器件组合。其中，第三代 AOM020V120X3 和顶侧冷却型 AOGT020V120X2Q 碳化硅器件，均适用于电源侧挂配置或单级系统 —— 可在数据中心边缘直接将 13.8 千伏交流电网输入转换为800V直流。在机架内部，AOS 通过其 650 伏和 100 伏氮化镓场效应晶体管系列支持高密度供电，高效将800V直流母线降压至GPU所需的低压轨。此外，该公司的 80 伏和 100 伏堆叠裸片 MOSFET 与 100 伏氮化镓场效应晶体管采用统一封装尺寸。这种通用性使设计人员能够在 LLC 转换器的次级环节以及 54 伏至 12 伏母线架构中，灵活平衡成本与效率。AOS 的堆叠裸片封装技术进一步提升了次级 LLC 插槽的可实现功率密度。其他半导体企业也宣布已做好支持800V直流供电架构转型的准备，包括瑞萨电子、英诺赛科、安森美半导体、德州仪器以及英飞凌科技。德州仪器近期发布了一款 30 千瓦AI服务器供电参考设计。该设计采用两级架构，以三相三电平飞跨电容功率因数校正（PFC）转换器为核心。根据系统需求，该单元可配置为输出统一的800V直流，或拆分为多个隔离输出。英飞凌除了提供 CoolSiC、CoolGaN、CoolMOS 和 OptiMOS 系列功率器件外，还推出了 48 伏智能电子保险丝（eFuse）系列和热插拔控制器参考板，专为AI数据中心的 400 伏和800V供电架构设计。这一方案使开发人员能够设计出可靠、稳健且可扩展的解决方案，实现对能量流的保护与监控。该参考设计以英飞凌的 XDP 热插拔控制器为核心。在适用于直流母线的高压器件中，1200 伏 CoolSiC JFET 在低导通电阻和热插拔工作稳定性之间实现了出色平衡。结合该碳化硅 JFET 技术，数字控制器可驱动器件工作在线性模式，确保电源系统在过压条件下仍保持安全稳定。该参考板还允许设计人员根据器件的安全工作区编程设置浪涌电流曲线，支持 12 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