Suspension Control-based Vehicle Ride Comfort Simulation

Ride comfort is the important performance of vehicle, it keeps passenger's comfort and goods's safety, also it influences other performances of vehicle. Active and semi-active suspension have eased the conflicts between ride comfort and operation stability in traditional passive suspension, enabling to suppress the over-large acceleration value of automobile body, improve ride comfort of the vehicles and make vehicles adapt to changes of road excitation and driving conditions. So Semi-active Suspension will be the development direction for designing modern suspension. Compared with active suspension, semi-active suspension is featured in low energy consumption and simple structure with wide application prospect, but similar to active suspension in control performance.First, pavement surface evenness and time domain model of road excitation are analysed in the paper. On basis of introducing the essential characteristics of electro-rheological fluid, this paper presents semi-active control for suspension based on ER damper and establishes a quarter car dynamic model. Its state space equation is derived. According as linear quadratic gaussian stochastic optimal control theory, weighted quadratic performance index related to the body acceleration, the suspension working space and the tyre dynamic displacement is used to design the LQG controller; According as fuzzy control theory as well, a fuzzy logic controller with two inputs and one output is designed. The fuzzy rules are established by experiences and theory analysis.Then use MATLAB/SIMULINK software to set up the model including passive and semi-active control and simulate.For compound control's advantages, designing a sliding model controller, the parameters of the switching surface are determined by the method of pole assignment. A proportion switching method and an equal near rate is used to amend the dynamic quality of sliding model motion in the proposed controller. Meanwhile, the RBF neural network arithmetic is introduced to optimize the sliding model control result. Then use MATLAB/SIMULINK software to set up the model including passive and semi-active control and simulate. The results show that the semi-active control is more effective than the passive control, the body acceleration has declined by 20% and ride quality has improved observably. Aiming at suspension parameter and velocity uncertainties, the semi-active control is more effective than the passive control, and sliding mode control of suspension is adaptive and robust. For non-linear suspension, sliding mode control based on RBF nerve networks is also effective and adaptive. At last, non-linear model of ER damper is proposeded, and which is useful for future research, meanwhile composing and control elements of suspension bench test are introduced, bench test as an improtant study aspect is pionted out in the paper.