| dc.description.abstract | A combined structure for autoupdating rotating component characteristic maps is proposed for an individual aeroengine model. The designed combined structure, known as the Newton–Raphson (NR)-particle swarm optimization (PSO) method, mainly composed of three parts, namely the equilibrium equations design, stability improved strategy, and reduced optimization logics. The equilibrium equations are designed to ensure the accuracy of the modified model. However, in some scenarios, the optimization process has poor stability. Therefore, a stability improved strategy is designed through limiting the range of values of the optimal parameters. In addition, reduced optimization logic is designed to reduce the computing time of the optimization algorithm. The NR-PSO method uses the Newton–Raphson method to increase the accuracy of model outputs. Meanwhile, the time consumed for optimization and the number of equilibrium equations are decreased by particle swarm optimization. The suggested method for automatic model correction has higher model output accuracy, quicker optimization speed, and stronger algorithm stability than particle swarm optimization. The simulation results showed the proposed method can transform the average performance model into the individual model matching the actual rig test data of an individual engine, and the maximum error of outputs of individual model are less than 1.5%. | |
