Powertrain mounting system (PMS) often operates with some degrees of uncertainty. These uncertainties may result from poorly known or variable parameters such as mount stiffness, or from uncertain inputs. For realistic predictions of the system behavior, the PMS models have to account for these uncertainties. To this end, the Chebyshev interval method is applied to study the uncertain characteristics of PMS.In the PMS, the location and orientation of each mount are off-design variables due to the space limitation of the powertrain. The stiffness coefficients of the mounts are considered as interval variables. The lower bounds and upper bounds of natural frequencies and the mode kinetic energy distributions of PMS are obtained using the Chebyshev interval analysis method. As a comparison, the scanning method is used to validate the interval method. The overall conclusion is that the Chebyshev interval method is a powerful approach for the simulation of PMS with interval parameters.

High-dimensional high-frequency continuous-vibration control problems often have very complex dynamic behaviors. It is difficult for the conventional control methods to obtain appropriate control laws from such complex systems to suppress the vibration. This paper proposes a new vibration controller by using reinforcement learning (RL) and a finite-impulse-response (FIR) filter. First, a simulator with enough physical fidelity was built for the vibration system. Then, the deep deterministic policy gradient (DDPG) algorithm interacted with the simulator to find a near-optimal control policy to meet the specified goals. Finally, the control policy, represented as a neural network, was run directly on a controller in real-world experiments with high-dimensional and high-frequency dynamics. The simulation results show that the maximum peak values of the power-spectrum-density (PSD) curves at specific frequencies can be reduced by over 63%. The experimental results show that the peak values of the PSD curves at specific frequencies were reduced by more than 47% (maximum over 52%). The numerical and experimental results indicate that the proposed controller can significantly attenuate various vibrations within the range from 50 Hz to 60 Hz.