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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.

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.

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.

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.

The backlash between engaging components in a driveline is unavoidable, especially when the gear runs freely and collides with the backlash, the impact torque generated increases the vibration amplitude. The power-split hybrid electric vehicle generates output torque only from the traction motor during the launching process. The nonlinear backlash can greatly influence the driveability of the driveline due to the rapid response of the traction motor and the lack of the traditional clutches and torsional shock absorbers in the powertrain. This paper focuses on the launch vibration of the power-split hybrid electric vehicle, establishes a nonlinear driveline model considering gear backlash, including an engine, two motors, a Ravigneaux planetary gear set, a reducer, a differential, a backlash assembly, half shafts, and wheels.