基于声明式拓扑规格的除湿型低露点空调系统的实验验证数字孪生自动生成
Automated generation of experimentally validated digital twins for desiccant-based low-dew-point air-conditioning systems from declarative topology specifications
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中文总结 AI 辅助
该研究提出一种框架，可从声明式拓扑规格自动生成HVAC系统的动态数字孪生，其生成速度比手动构建快15倍，仅用三个湿度节点即可实现高精度预测，缩短了从设备描述到验证孪生模型的路径。
中文摘要 AI 辅助
在电池制造中，干燥室的低露点空调是最大的能源消耗环节之一，基于物理模型的数字孪生可为超出已安装监测点的运行点优化提供洞见。构建数字孪生并将其校准到现场数据需要不同的专业知识，这限制了其在工业中的应用。我们提出了一种框架，可从声明式拓扑规格生成HVAC系统的动态数字孪生，该规格足够简洁，可通过自然语言设备描述草拟，并针对专用物理组件库进行编译，自动合成接线、求解器和遥测功能。这些模型具备设备级物理特性：除湿轮通过可互换的吸附等温线组件耦合热质传递，因此未公开的商用吸附剂被校准为有效等温线，而非作为材料进行断言。为进行实验验证，我们构建了一个工业级的十组件低露点系统，其商用除湿轮单元将腔室维持在-40°C的霜点附近，并在除湿和旁通两种工况下运行。生成可运行模型的速度比专家手动构建快15倍，且仅拟合三个闭环湿度节点的单一参数集，可将旁通工况预测误差控制在0.1°C以内，再加热功率误差控制在5%以内，并能预测实测输入阶跃响应。可识别性分析表明这是预测而非拟合：普通运行点仅约束一个参数组合，而再循环回路的深度干燥平衡水平提供了缺失的信号。该框架缩短了从设备描述到经测量验证的孪生模型的路径；其基于准则的校准是实现不仅能构建还能自动校准的孪生模型的一步。
英文摘要
In battery manufacturing, the low-dew-point air conditioning of dry rooms is among the largest energy consumers, and a physics-based digital twin offers insight for operating-point optimization beyond the installed monitoring points. Building one and calibrating it to field data each demand distinct expertise, which limits industrial uptake. We present a framework that generates a dynamic digital twin of an HVAC system from a declarative topology specification, concise enough to draft from a natural-language plant description, compiled against a purpose-built physical component library with wiring, solver, and telemetry synthesized automatically. The models carry equipment-level physics: the desiccant wheel couples heat and mass transfer through an interchangeable sorption-isotherm component, so an undisclosed commercial sorbent is calibrated as an effective isotherm rather than asserted as a material. For experimental validation we built an industrial-grade, ten-component low-dew-point system whose commercial desiccant-wheel unit holds a chamber near -40 °C frost point, and operated it in both dehumidification and bypass regimes. Generation reached a runnable model fifteen times faster than expert manual construction, and a single parameter set, fitted only to three closed-loop humidity nodes, predicts the bypass regime within 0.1 °C, the reactivation-heater power within 5%, and measured input-step responses. Identifiability analysis shows why this is prediction, not fitting: ordinary operating points constrain only one parameter combination, and the deep-dry equilibrium level of the recirculating loop supplies the missing signal. The framework shortens the path from plant description to measurement-validated twin; its criteria-based calibration is a step toward twins calibrated, not only constructed, automatically.
