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Active engine mounts (AEMs) notably contribute to ensuring superior performance of vehicle’s noise, vibration, and harshness. This paper incorporates a filtered-x-least-mean-squares (FxLMS) controller into the active control engine mount system to attenuate the transmitted force to the body. To avoid the error caused by substituting the load cell for acceleration transducer, the FIR model of the secondary path was obtained by experiment. Finally, a hardware-in-the-loop testing system is built to verify the performance of the active engine mount. It can be observed from the test results that the vibration is reduced notably after control, which demonstrates the effectiveness of the active engine mount and the controller in vibration attenuation.

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.