🤖 AI Summary
This study addresses the long-standing reliance on expert knowledge in constructing digital twins for low dew-point air conditioning systems, which hinders industrial deployment. The authors propose an automated modeling framework based on declarative topological specifications that leverages a library of physical components to generate dynamic models, solvers, and telemetry interfaces automatically. By integrating adsorption–heat transfer coupling mechanisms with parameter identifiability analysis, the framework achieves calibration using only three humidity measurement nodes. It enables rapid generation and automatic calibration of digital twins directly from natural language descriptions and characterizes unknown commercial desiccants via equivalent adsorption isotherms, ensuring high-fidelity prediction rather than empirical curve-fitting. Experimental results demonstrate a 15-fold acceleration in model generation compared to manual methods, with dew-point temperature prediction errors below 0.1°C under bypass conditions, regeneration heating power errors under 5%, and accurate reproduction of step-response dynamics.
📝 Abstract
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.