Mode transition path optimization for turbine-based combined-cycle ramjet stage under uncertainty propagation of integrated airframe-propulsion system

Chengkun Lv, Qian Huang, Juntao Chang, Ziao Wang, Jialin Zheng and Daren Yu

Energy, 2023, vol. 268, issue C

Abstract: This study was conducted in two parts: a characteristic analysis considering the uncertainty propagation in the mode transition of a turbine-based combined cycle (TBCC) engine, and an optimization of the control law for the mode transition. First, the characteristic analysis of the uncertainty propagation was used to determine the main influencing factor s of the input parameters on the output thrust and stability margin. The uncertainty propagations were in the inlet system, including the forebody, inlet splitter, and cowl. The uncertainty perturbation was introduced using a Markov chain Monte Carlo method based on the Metropolis–Hastings algorithm. Then, the optimization of the control law of the TBCC mode transition was studied using a sequential quadratic programming method. It mainly analyzes the optimization in three cases: univariate and single-objective optimization, multi-variable and single-objective optimization, multi-variable, and multi-objective optimization. The results for three settings satisfy the objective of keeping the output thrust relatively constant during the mode transition. In addition, the results without considering perturbation exceed the safety constraint boundary under an actual flight situation. Finally, the optimization process with or without uncertainty propagation is further studied, and it is found that the optimization considering the perturbation can avoid inlet unstart hazard.

Keywords: Turbine-based combined cycle engine; Mode transition; Uncertainty perturbation; Sequence quadratic programming; Control law (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:268:y:2023:i:c:s0360544223001123

DOI: 10.1016/j.energy.2023.126718

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