The trade-off between handling stability and ride comfort is a disadvantage for the bus fitted with passive suspension due to its high center of gravity and heavy load. A novel suspension configuration with both hydraulically interconnected suspension and electronic controlled air spring is created to handle this conflicting requirement. The proposed whole vehicle system model has three subsystems: a 9-degree-of-freedom vehicle multi-body model, hydraulically interconnected suspension model, and electronic controlled air spring. The electronic controlled air spring comprises an air spring and an auxiliary air chamber, and its height can be adjusted by a fuzzy controller. Then, analytical work is performed to evaluate the handling stability and ride comfort of the vehicle with different suspension configurations under various maneuvers and suspension height modes. Finally, the vehicle on-road test is conducted to experimentally validate the proposed models. Both analytical and experimental results indicate that the vehicle fitted with hydraulically interconnected suspension and electronic controlled air spring can obtain high performance for both handling stability and ride comfort.

This paper is aimed at developing a computationally efficient approach to simulate the vertical dynamic behavior of vehicle–track coupled system. With the finite element method, the car body, bogies, and rail are modeled as Euler beams supported by springs and dashpots, which can investigate the influence of flexibility of the vehicle on structural dynamic response. By a variant of component-mode synthesis (CMS), the degrees-of-freedom (DOFs) within the substructures are condensed and the two substructures are coupled through nonlinear Hertzian theory. Although the system matrix is updated and factorized during the calculation, the total computational efficiency is significantly improved due to the much smaller size of the equations of motion and direct solution algorithm instead of iterative procedure. Compared with an existing model, the accuracy and efficiency of the method are investigated. Application of the model is shown by numerical example.

In order to improve the lateral and directional performance of vehicles, this paper proposes a novel rear-steering based decentralized control (RDC) algorithm for four-wheel-steering (4WS) vehicles. Based on a linearized single-track vehicle model, a prototype of the RDC algorithm for linear conditions is derived. Linear analysis in frequency domain shows that the RDC can significantly reduce the magnitude and increase the phase lag of sideslip response as well as enlarge the bandwidth of yaw response in a broad frequency range. Through the incorporation of a novel sliding mode controller, the RDC algorithm is further extended for nonlinear applications. Analysis based on nonlinear model shows that, the RDC can guarantee the performance of the closed-loop (CL) system in the presence of uncertainties in system parameters and state feedback values. Moreover, the RDC is robust to arbitrary lateral disturbances and can guarantee that the vehicle converges to reference yaw rate and zero sideslip. Simulation results show that the RDC can effectively improve the lateral and directional performance of the vehicle in comparison with previous control methods. Excellent robustness to external disturbance and road friction variation is reported as well.

Electric vehicles generally have a better noise, vibration, and harshness quality than traditional vehicles due to the relatively quiet electric motors. By contrast, the noise, vibration, and harshness issues of the driveline system become more outstanding and significant in the absence of the “masking effect” by the engine. The electrification of the powertrain has also brought many changes in the sources or transmission of vibration, which has led to some new noise, vibration, and harshness issues. Specifically, the intense vibration of the prototype bus appears when driving in third gear, which makes the passengers uncomfortable. This paper presents an efficient analytical strategy for identifying the resonance sources and vibration transmission for a pure electric bus. The strategy incorporates order analysis, operating deflection shape, and transfer path analysis. Order analysis shows that the resonance is primarily caused by the second-order excitation associated with the driveline, and the vibration sources are further identified using operating deflection shape analysis. Moreover, the vibration transfer paths from the driveline to the bus floor are quantitatively determined by the transfer path analysis method. The results show that the coupling vibration of the powertrain and the rear drive axle, which amplifies the resonance of the whole driveline, is transmitted to the bus floor primarily through powertrain mounts and V rods. Based on the results, the design and structure modifications of the driveline and transfer paths are recommended to handle this issue. The proposed identification strategy would be beneficial for accurate and efficient engineering troubleshooting on the vibration issues.

This study presents a technique that uses a model reduction method for the dynamic response analysis of a beam structure to a moving load, which can be modeled either as a moving point force or as a moving body. The nature of the dedicated condensation method tailored to address the moving load case is that the master degrees of freedom are reselected, and the coefficient matrices of the condensed model are recalculated as the load travels from one element to another. Although this process increases computational burden, the overall computational time is still greatly reduced because of the small scale of motion equations. To illustrate and validate the methodology, the technique is initially applied to a simply supported beam subjected to a single-point load moving along the beam. Subsequently, the technique is applied to a practical model for wheel-rail interaction dynamic analysis in railway engineering. Numerical examples show that the condensation model can solve the moving load problem faster than an analytical model or its full finite element model. The proposed model also exhibits high computational accuracy.