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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.

Object detection is an important visual content of the autonomous vehicle, the traditional detecting methods usually cost a lot of computational memory and elapsed time. This paper proposes to use lightweight deep convolutional neural network (MobilenetV3-SSDLite) to carry out the object detection task of autonomous vehicles. Simulation analysis based on this method is implemented, the feature layer obtained after h-swish activation function in the first Conv of the 13th bottleneck module in MobilenetV3 is taken as the first effective feature layer, and the feature layer before pooling and convolution of the antepenultimate layer in MobilenetV3 is taken as the second effective feature layer, and these two feature layers are extracted from the MobilenetV3 network.

The turbocharger air intake noise during transient conditions like wide open throttle and tip-in/out affects the passenger ride comfort. This paper aims to study an optimized design of multi-chamber perforated resonators to attenuate this noise. The noise produced by a turbocharger in a test vehicle has been measured to find out the noise spectral characteristics which can be used to design the acoustic targets including the amplitude and frequency range of transmission loss (TL). The structural parameters of the resonators are optimized based on genetic algorithm (GA) and two-dimensional prediction theory of the resonator TL. The optimized resonators are installed on the test vehicle to verify the actual noise reduction effect. The results suggest that the broadband noise has been eliminated, and subjective feelings are greatly improved.

The noise and vibration of electric vacuum pump (EVP) become a major problem for electric vehicles when the vehicle is stationary. This paper aims at the EVP’s abnormal noise of an electric vehicle when stationary. Driver’s right ear (DRE) noise was tested and spectrogram analysis was carried out to identify the noise sources. In order to attenuate this kind of abnormal noise, a new EVP rubber mount with a segmented structure was introduced, which optimized the transfer path of vibration. Then dynamic stiffness and fatigue life of the EVP mount with different rubber hardness were calculated through finite element analysis (FEA) approach. Bench tests of fatigue life and DRE noise were performed to validate the FEA results. Test data of the sample mount shows that sound pressure level of DRE was dramatically attenuated and thus passengers’ ride comfort was enhanced.

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.

Tire cavity noise of pure electric vehicles is particularly prominent due to the absence of engine noise, which are usually eliminated by adding Helmholtz resonators with arbitrary transversal section to the wheel rims. This paper provides theoretical basis for accurately predicting and effectively improving acoustic performance of wheel resonators. A hybrid finite element method is developed to extract the transversal wavenumbers and eigenvectors, and the mode-matching scheme is employed to determine the transmission loss of the Helmholtz resonator. Based on the accuracy validation of this method, the matching design of the wheel resonators and the optimization method of tire cavity noise are studied. The identification method of the tire cavity resonance frequency is developed through the acoustic modal test. A scientific transmission loss target curve and fitness function are defined according to the noise characteristics.

The active engine mount (AEM) is developed in automotive industry to improve overall NVH performance. The AEM is designed to reduce major-order signals of engine vibration over a broad frequency range, therefore it is of vital importance to extract major-order signals from vibration before the actuator of the AEM works. This work focuses on a method of real-time extraction of the major-order acceleration signals at the passive side of the AEM. Firstly, the transient engine speed is tracked and calculated, from which the FFT method with a constant sampling rate is used to identify the time-related frequencies as the fundamental frequencies. Then the major-order signals in frequency domain are computed according to the certain multiple relation of the fundamental frequencies. After that, the major-order signals can be reconstructed in time domain, which are proved accurate through offline simulation, compared with the given signals.

Faced on transient vibration of EV, considering the characteristics of the electric drive system, active and passive integrated transient vibration control method of power train mounting system was proposed. Models of power train system and mounting system were established, modal characteristics were grasped by simulation and experiment. A feed-forward controller was constructed from the facet of active control, mounting system transient vibration and power train torsion vibration were reduced. Based on this, further optimization of mounting system was conducted from a passive control perspective. Results show that the active and passive integrated control method can effectively reduce the dynamic reaction force of mounting points, improve the vibration conditions of power train and vehicle body as well.

In course of the electrification of vehicle's powertrain, one of the vital problems we've been faced with is the limitation of the vehicle's driving range due to the capacity of currently available batteries. Therefore, range-extended electric vehicle (ReEV) concept has become one of the most promising transitory technologies to compensate this defect. Electric vehicle is supposed to be quiet and comfortable for the customers. However, some annoying sound derived from powertrain and accessories must be reduced or eliminated to meet this requirement. Accessory NVH has an important contribution to ReEV's NVH performance. If it is not well handled, poor vibration and noise may appear. This paper focuses on accessories' NVH performance in ReEV including the NVH problems from steering pump, vacuum pump and AC compressor.

In recent years, electric vehicle and hybrid vehicle are either on the market or under intensive research and development (R&D). Since the concept of auxiliary power unit (APU) was brought into the automotive industry, the range-extended electric vehicle (ReEV) has become the favor of the worldwide manufacturers. Normally, the APU starts and stops more frequently in response to the control strategy compared with traditional vehicles, which will affect the ride comfort of passengers. Thus, APU start-stop NVH refinement is an important aspect of ReEV R&D. In this paper, a subjective evaluation on a ReEV was performed to quickly diagnose NVH issues firstly. Based on subjective results, the NVH experiment in a semi-anechoic room was carried out to troubleshoot these issues. The accelerations of the APU mounts, the seat track and the steering wheel as well as interior noise level were acquired and analyzed.