Exact component characteristics are required for establishing an accurate component level aeroengine model. When component characteristics is lacking, the dynamic coefficient method based on test data, is suitable for establishing a single-input and single-output aeroengine model. When it is applied to build multiple-input, multiple-output aeroengine models, some parameters are assumed to be unchanged, which causes large error. An improved modeling method based on rig data is proposed to establish a double-input, double-output model for a micro variable-pitch turboprop engine. The input variables are fuel flow and pitch angle, and the output variables are rotational speeds of the core engine and the propeller. First, in order to gather modeling data, a test bench is designed and rig tests are carried out. Then, two conclusions are obtained by analyzing the rig data, based on which, the power turbine output is taken as the function of the core speed and the propeller speed. The established model has the property that the input variables can vary arbitrarily within the defined domain, without any restriction to the output variables. Simulation results showed that the model has a high dynamic and steady-state accuracy. The maximum error was less than 8%. The real-time performance was greatly improved, compared to the component level model. regulating mechanism is designed and a micro turboprop engine test platform is built.The mathematical model of the aeroengine plays an important role in the design and verification of the aeroengine control system, which can effectively reduce the development time, risk, and cost [8,9]. Micro gas turbine engines are widely used as low-cost solutions, therefore, fewer sensors are usually available than in standard gas turbines [8]. An accurate model can offer reference signals to the control system of micro engines. The modern aeroengine control systems adopt model-based ones, to fully utilize their performance. Modern aeroengine control methods such as performance seeking control, life extending control, and fault-tolerant control require an on-board engine model to track unmeasured parameters [10,11]. Aeroengine modeling methods can be divided into three categories-analytical methods based on operating principles (white box method), system identification methods based on test data (black box method), and gray box methods, which consider synthetic test data and operating principles.A component level model is built based on analytical methods, by using component characteristics and engine operating principles. It is the most common aeroengine modeling method. Fitzgerald et al. from Georgia Tech Institute built a component level model, based on the component characteristics of SPT5 [12,13]. The component characteristics are obtained via rig tests carried out in their own test platform. The model obtained by the analytical method has a high precision and can simulate both steady-state and dynamic engine outputs in the full envelope. However, this method requires accurate component ch...