On-board modelling of gas turbine aero-engines over the life cycle is a promising solution for engine performance improvement and future aero-propulsion requirements. In this paper, an on-board modelling approach named Hybrid Wiener model (HWM) is proposed for gas turbine aero-engines using post-flight engine monitoring data, which aims at estimating the unmeasured safety-critical control parameters (i.e. thrust, surge margin, and turbine entry temperature) by monitoring the engine degradation effects. Common on-board models for nominal engines, i.e. piecewise linear model, novel generalized describing function, and Wiener model, are systematically tested on a validated turbofan engine aero-thermal model. Simulations demonstrate that Wiener model is the best candidate for nominal engines. HWM is therefore constructed with the integration of on-line Wiener models and an off-line adaptation approach. The on-line part computes the unmeasured safety-critical parameters in a real-time manner. Meanwhile, the off-line adaptation part serves to periodically update the nonlinear static blocks of on-line Wiener models using the post-flight data in order to match the particular degraded engine. Idle to full-power rapid transient simulations of HWM are carried on the turbofan engine aero-thermal model for degradation simulations using publicly available data. Results from the studied turbofan engine at different flight cycles demonstrate that HWM is not only able to guarantee the steady accuracy for thrust, surge margin, and turbine entry temperature, but also ensures that the maximum transient errors for these safety-critical parameters are less than 4.66% during rapid acceleration states. Moreover, the percent errors of peak values for surge margin and turbine entry temperature between HWM and the engine are within 0.50%. The performance of the proposed HWM over the engine life cycle is therefore confirmed.

在生命周期内对燃气轮机航空发动机进行机载建模是改善发动机性能和未来航空推进要求的有前途的解决方案。在本文中，使用飞行后发动机监测数据为燃气轮机航空发动机提出了一种称为混合维纳模型（HWM）的机载建模方法，旨在估算未测得的安全关键控制参数（即推力，喘振裕度） ，以及涡轮进口温度）。在经过验证的涡扇发动机空气热模型上系统地测试了标称发动机的常见车载模型，即分段线性模型，新颖的广义描述函数和维纳模型。仿真表明，维纳模型是标称发动机的最佳选择。因此，HWM是通过集成在线Wiener模型和离线自适应方法构建的。在线部分以实时方式计算未测量的安全关键参数。同时，离线适配部分用于使用飞行后数据周期性地更新在线维纳模型的非线性静态块，以匹配特定的退化发动机。涡轮风扇发动机的空气热模型对HWM进行了从空闲到全功率的快速瞬态仿真，并使用公开数据进行了退化仿真。涡轮风扇发动机在不同飞行周期下的研究结果表明，HWM不仅能够保证推力，喘振裕度和涡轮进入温度的稳定精度，而且还可以确保在快速加速状态下，这些安全关键参数的最大瞬态误差小于4.66％。此外，HWM与发动机之间的喘振裕度和涡轮进入温度峰值的百分比误差在0.50％以内。因此，可以确定提议的HWM在发动机寿命周期内的性能。