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高保真降阶建模方法在中压驱动器及人工智能可兼容系统中的应用
High-Fidelity Reduced Order Modeling Approach for Medium-Voltage Drives and Artificial Intelligence Capable Systems
| 作者 | Bogdan C. Ionescu · Liviu Mihalache · Saeed Asgari · Satyajeet Padhi · Viral Gandhi · Mukul Rastogi |
| 期刊 | IEEE Journal of Emerging and Selected Topics in Power Electronics |
| 出版日期 | 2024年9月 |
| 技术分类 | 光伏发电技术 |
| 技术标签 | SiC器件 热仿真 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 中压驱动器 热管理 降阶模型 计算流体动力学 人工智能 |
语言:
中文摘要
中压驱动器的热管理设计依赖计算量大且耗时的仿真。本文提出一种基于计算流体动力学(CFD)与降阶模型(ROM)技术相结合的创新方法。引入一种物理信息感知的非侵入式ROM,利用系统的线性时不变(LTI)特性,预测冷却介质流量变化下中压驱动组件的热行为,构建线性参数变化(LPV)ROM。该ROM方法在中压驱动功率变换器上验证,并与实测数据对比,结果表明其在保持精度的同时显著降低计算资源与时耗。该技术为驱动控制器实时嵌入精确热模型提供了可能,推动人工智能系统的发展。
English Abstract
The design of thermal management for medium-voltage (MV) drives is an important subject that requires computationally intensive and time-consuming simulations. This article presents an innovative way of leveraging the power of computational fluid dynamics (CFD) simulations by using reduced order model (ROM) technology. A physics-aware nonintrusive ROM is introduced that leverages the linear and time-invariant (LTI) properties of the system to predict the thermal behavior of MV drive components under varying flow rates of the cooling medium to generate a linear parameter varying (LPV) ROM. The developed ROM creation technology is tested on a power converter that is part of an MV drive, and its results are compared with test measurements. Compared to a full-scale CFD simulation, the ROM approach results in a significant reduction in time and computing resources to obtain thermal responses. The availability of such ROMs opens the possibility of drive controllers implementing accurate thermal models in real time, thereby allowing further development of artificial intelligence (AI) systems.
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SunView 深度解读
该高保真降阶建模技术对阳光电源中压产品线具有重要应用价值。在ST系列储能变流器和PowerTitan大型储能系统中,SiC功率模块的热管理直接影响系统可靠性和功率密度。该ROM方法可将CFD热仿真从数小时压缩至秒级,使实时热模型嵌入控制器成为可能,实现动态功率解耦和预测性过载保护。对于1500V光伏逆变器和三电平拓扑设计,该技术可快速评估不同冷却策略下的器件温升,优化风冷/液冷方案。结合iSolarCloud平台,可构建AI驱动的热管理数字孪生系统,实现智能风机调速和故障预警,提升系统效率2-3%,延长IGBT/SiC模块寿命20%以上。