Research On Modeling And Simulation Of Semi-active Suspension ADD-SH Control Strategy Based On Vi-grad CarRealTime

Control strategy is key point insemi-active suspension system design. But the most theory research is not proved in experiment. Less of them is brought to market. Considering this problem, this paper analyzes the reason why most of control strategy is difficult to apply in engineering. Based on actual project, control strategy of ADD-SH and the Design of Experiment(DOE) of control parameters are chosen as the subject of study.Not only for classical semi-active suspension control, but also fuzzy control, neural network control, sprung mass vertical velocity is necessary. But body vertical velocity cannot be measured by the sensor directly. So state observer is necessary part of control strategy. High performance reference model is fundamental of state observer. In classic suspension model, Road roughness is treated as system input that is not measured by sensor. This paper design a new reference model that use tire load as input, which making the open loop performance of state observer improved greatly. Besides low feedback gain can reduce potential system instability. To get accuracy reference model, system identification method is used to fit experiment curve and get optimal reference model parameters.Then this paper chooses 7 degrees of freedom vehicle model to simulate ADD-SH control strategy under different experiment conditions. Verify the effectiveness of the ADD-SH control strategy. After control strategy verification, Vi-grad Car RealTime model is built depending on ADAMS model and SWIFT tire model, meanwhile arrangement and dynamic response performance of CDC damper and tire enveloping properties is considered in the model. At the end of chapter 4, This paper compares the riding performance with passive damper and CDC damper.Because original ADD-SH control take parameter adjust under consideration, this paper uses Experimental Design to optimize ADD-SH control parameters to reduce the vertical body acceleration root mean square value response. Response Surface Metrology(RSM) is chosen as method of DOE. And use this way to get optimal parameters for the control strategy under different vehicle speed and road level. And the optimal parameters are treated as 2D lookup table to adjust ADD-SH algorithm parameter, and compared the passive damper performance and performance improvement of ADD-SH control upgrade. Finally, This paper outlook the research direction of semi-active suspension.