Modelling and analysis for a pilot relief valve using CFD method and deformation theory of thin plates

The current work is concerned with modelling and analysis for a pilot relief valve, thus successfully bringing a systematic method for designing and analyzing similar valves. The essence of the work is to solve two important problems, one for positions of the pilot valve influenced by flow force and the other is for the opening of the relief valve governed by a thin annular plate. The computational fluid dynamics(CFD) method is used to present the flow force. Using a series of experiments, the flow rate versus pressure drop shows the rationality of the CFD results. In order to obtain the opening of relief valve with higher accuracy, the large deflection theory of thin plates is adopted. An equivalent method for replacing the concentrated force is innovatively proposed so that all of the loads of the plates can be given by a unified expression, which reduces the number of the governing equations and intermediate boundary conditions. For presenting a very simple and reliable method for solving the governing equation, an unconstrained nonlinear optimization is innovatively introduced to solve the deflection of the thin annular plate. Being verified by finite-element method(FEM) of the relief valve, the equivalent method and optimization can solve deflection of thin plates rapidly and accurately. Reflected through a complete model for the pilot relief valve, the theoretical flow rate of the pilot relief valve is consistent with experimental conclusion. Once again, the comparisons bring us insight into the accuracy of the method adopted in the current work.

Kalman Filter-Based Fusion Estimation Method of Steering Feedback Torque for Steer-by-Wire Systems

Universal challenge lies in torque feedback accuracy for steer-by-wire systems,especially on uneven and low-friction road.Therefore,this paper proposes a fusion method based on Kalman filter that combines a dynamics-reconstruction method and disturbance observer-based method.The dynamics-reconstruction method is designed according to the vehicle dynamics and used as the prediction model of the Kalman filter.While the disturbance observer-based method is performed as an observer model of the Kalman filter.The performance of all three methods is comprehensively evaluated in a hardware-in-the-loop system.Experimental results show that the proposed fusion method outperforms dynamics reconstruction method and disturbance observer-based method.Specifically,compared with the dynamics-reconstruction method,the root mean square error is reduced by 36.58%at the maximum on the flat road.Compared with the disturbance observer-based method,the root mean square error is reduced by 39.11%at the maximum on different-friction and uneven road.