Apery intelligent control method for harmonizing auto magnetorheological half-initiative suspension according to posture

Abstract

The invention provides the method of vehicle magnetic flow changing to semi-active suspension damped control, comprising the following steps: using the acceleration transducer and dip angle transducer to obtain the vehicle motion state signal, dividing the motion state into eight sorts, adopting controlling modality to control, defining the control number according to the minimum amplitude versus frequency character from the transfer characteristic in resonance frequency. The vehicle has good control stability. The method integrates the ceiling damped control with proportional plus derivative control to form the multi-modality and multi-controller intelligence control. The algorithm is simple, and the method is conveniently used in vehicle semi-active suspension.

Description

technical field [0001] The invention belongs to the technical field of automobile damping control, and in particular relates to a humanoid intelligent control method for automobile magneto-rheological semi-active suspension damping. Background technique [0002] Since D.A.Crosby and D.C.Karnopp of the United States proposed the concept of semi-active in 1973, scholars from various countries have been committed to the research of semi-active controllable devices and control algorithms. Since semi-active systems are usually strongly nonlinear, their applications are limited. From simple ceiling damping control to complex intelligent control such as fuzzy control and neural network control, it has been continuously applied in simulation and road test research, while the ceiling damping control is used in actual vehicles. The ceiling damping control algorithm is simple, and reasonable selection of parameters can well suppress the vertical vibration of t...

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Problems solved by technology

However, the improvement of this smooth performance is at the cost of the reduction of handling stability, which is unacceptable in some working conditions

[0003] Optimal control and robust control that depend on the model, due to the need to measure more states, increase the complexity of software and hardware, and the application is also limited

The intelligent control methods of fuzzy control and neural network control are also applied to the semi-active vibration reduction control of automobiles, but these methods are often based on various assumptions, and the control rules are heavily dependent on the experience of experts. There are large differences in working conditions, and due to the complexity of the algorithm, it is still mainly in the simulation experiment stage

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