High-speed turbocharger rotors are often supported on double film floating ring bearings. In recent times, foil bearings are increasingly used as an alternative to floating ring bearings for supporting such lightweight rotors. Present work aims at the dynamic modeling and stability studies of the automotive turbocharger rotor system supported on the airfoil bearings under varying operating conditions. The effects of different parameters including rotor spin speed, bearing clearance, bump foil thickness, and foil pitch on the dynamic response of the rotor system are illustrated. The nonlinear relationship between the bearing parameters and vibration response data is modeled using supervised neural network scheme. With the use of counter propagation neural network model, inverse identification methodology of the bearing parameters is performed. Further, an optimal design of foil bearing parameters using a surrogate model is proposed with a modified particle swarm optimization scheme. The resultant design parameters are employed, and the percentage reductions in vibration amplitudes of dynamic response are reported.

高速涡轮增压器转子通常支撑在双膜浮环轴承上。近年来，箔轴承越来越多地用作浮动环轴承的替代品，以支撑这种轻质转子。目前的工作旨在对在不同工况下支撑在翼型轴承上的汽车涡轮增压器转子系统进行动力学建模和稳定性研究。说明了包括转子旋转速度，轴承间隙，凸点箔厚度和箔间距在内的不同参数对转子系统动态响应的影响。轴承参数和振动响应数据之间的非线性关系是使用监督神经网络方案建模的。利用反向传播神经网络模型，进行了轴承参数的逆辨识方法。此外，提出了一种使用替代模型的箔轴承参数优化设计，并采用了改进的粒子群优化方案。使用所得的设计参数，并报告了动态响应的振动幅度减小的百分比。