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ENGINE TEST RESULTS FOR THE T55-L-714 ENGINE ADVANCED ADAPTIVE CONTROL SYSTEM TESTING AT REDSTONE AVIATION PROPULSION TEST AND RESEARCH (RAPTR) FACILITY

机译:T55-L-714发动机测试结果在Redstone航空推进试验和研究(RAPTR)设施下的T55-L-714发动机先进自适应控制系统测试

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Under a US Army Applied Aviation Technology Directorate (AATD) sponsored engine test program, Goodrich Engine Controls, teamed with Honeywell Engine Systems, demonstrated the feasibility of utilizing an adaptive, fully nonlinear, realtime, aero-thermodynamic (AT) engine model. This model was embedded in the production EMC-100 ECU for the T55 engine, to successfully control the RAPTR engine test facility's T55-L-714 workhorse engine using model synthesized engine parameters. Prior Goodrich research effort demonstrated the ability to adapt a physics-based, aero-thermodynamic model to produce real-time outputs which accurately represent a specific physical engine. Traditional engine control units are designed to govern engine speed, limit engine temperature and maximize engine life based on direct measurement of physical data provided by engine sensors. This research effort has demonstrated the ability to use model based operating data-computed in the embedded aero-thermodynamic engine model, to safely control that engine. The advanced control can use model-based data to diagnose and replace faulted sensors, or synthesize normally unobservable operating states to enhance control capability, and potentially improve engine performance. This paper will present these engine test results under model based control as well as discuss the implications this testing has on future gas turbine engine control in the areas of enhanced engine performance, improved sensor fault detection, engine failure diagnostics, condition based maintenance and increased survivability utilizing model-based data.
机译:根据美国陆军应用航空技术董事会(AATD)赞助的发动机测试计划,与霍尼韦尔引擎系统合作的Goodrich发动机控制,展示了利用自适应,完全非线性,实时,航空热力学(AT)发动机模型的可行性。该模型嵌入在生产EMC-100 ECU的T55发动机中,以便使用型号合成发动机参数成功控制RapTR发动机测试设施的T55-L-714主管引擎。之前的Goodrich研究工作表明,能够适应基于物理的Aero-ThermoG动力学模型,以产生准确代表特定物理发动机的实时输出。传统的发动机控制单元设计用于控制发动机速度,限制发动机温度,并根据发动机传感器提供的物理数据的直接测量最大化发动机寿命。这项研究努力证明了在嵌入式航空热力发动机模型中使用基于模型的操作数据,以安全地控制该发动机。高级控制可以使用基于模型的数据来诊断和更换故障传感器,或者合成通常不可观察的操作状态以增强控制能力,并可能提高发动机性能。本文将在基于模型的控制下提出这些发动机测试结果,并讨论该测试对未来燃气涡轮发动机控制的影响,在增强的发动机性能,改进的传感器故障检测,发动机故障诊断,条件的维护和增加的存活性上利用基于模型的数据。

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