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Active engine mount (AEM) is an effective approach which can optimize the noise, vibration and harshness (NVH) performance of vehicles. The filtered-x-least-mean-squares (FxLMS) algorithm is widely applicated for vibration attenuation in AEMs. However, the performance of FxLMS algorithm can be deteriorated without an accurate secondary path estimation. First, this paper models the secondary path using finite impulse response (FIR) model, infinite impulse response (IIR) model and back propagation (BP) neural network model and the model errors of which are compared to determine the most accurate and robust modeling method. After that, the influence of operation frequency on accuracy of the secondary path model is analyzed through simulation approach. Then, the impact of reference signal mismatch on the control effect is demonstrated to study the robustness of FxLMS algorithm.

Attributable to its comprehensive advantages of good vibration isolation performance and low cost, air engine mount is gradually being applied in vehicle powertrain vibration reduction. In the present paper, a full vehicle nonlinear model considering air engine mount was established to describe the characteristics of engine shake better. A Jacobian-free Newton-Krylov (JFNK) method for solving nonlinear equations was proposed to simulate the model more efficiently. The result demonstrated that air engine mount has great influence on engine shake characteristics under the front wheel excitation. Then the influence of air engine mount parameters on engine shake characteristics was discussed. Finally, the engine shake characteristics considering air engine mount and hydraulic engine mount were compared and the result showed the former resonance frequency was higher.