In the present study, a novel approach to estimating the efficiency of roller chain power transmission systems is proposed based on sliding friction losses and damping force. The dynamics model is taken into account between chain links with lateral offset owing to the derailleur system. Frictional losses were calculated according to Coulomb’s law of friction, and the damping force was dependent on the damping coefficient. The effects of rotational speed, load, derailleur system, and damping coefficient on transmission efficiency were analyzed. The test stand of the roller chain power transmission system was set up to verify the estimated efficiency, and the results showed a good correlation, demonstrating the validity of the chain power transmission efficiency estimation.

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Vibration-control techniques generally fall into two categories: passive methods that optimize the structure of the suspension to absorb any impact from the ground, and active methods that directly control the vertical force of the suspension by hydraulic or electric actuators when the vehicle traverses a bumpy road. In this study, a vibration-control method is described that employs both an optimal controller and suspension parameter optimization. Continuous speed bumps are implemented to simulate more complex and realistic driving conditions. First, a vehicle system is modeled using a semi-recursive multibody formulation, which allows for a more precise description of the longitudinal–vertical dynamics. Then, an optimal control method for vehicle vibration control is introduced. Second, the Latin hypercube design is utilized to analyze the response surface methodology (RSM) model. For suspension optimization, the RSM model and the non-linear programming with a quadratic Lagrangian (NLPQL) algorithm are employed. Thirdly, both passive suspension optimization and active motion control are employed for vibration control. The results indicate that the presented method can effectively control vehicle vibration, decreasing the average vibration by 30.8%. The results suggest that the novel approach can also enhance the ride comfort in autonomous vehicles traversing, e.g., a series of speed bumps.