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Ride Comfort’ Co-simulation Of The Changfeng Road-off Vehicle&Research Of Active Suspension’s Intelligent Control Strategies

Posted on:2011-02-26Degree:MasterType:Thesis
Country:ChinaCandidate:C X DingFull Text:PDF
GTID:2252330395985292Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
With the development of automobile industry, the ride comfort and handling performance of vehicle is becoming very important. As structure parameters of traditional passive suspension can not adaptively change with external road and real-time conditions, it limits the improvement of vehicle’s dynamic performance. The active suspension could adjust the control force actively and timely to reduce the vibration according to the working condition. It enables the vehicle to get optimal ride comfort and handling safety.So, targeting to study a Changfeng off-road vehicle’s ride comfort&handling stability performance, the full vehicle’s ride comfort was analysed&active suspension intelligent control strategies was discussed in this dissertation. Below is the main job and achievement of the dissertation:(1)The ride comfort’s test data of the full vehicle was analysed, some factors to improve ride comfort was found. The multi-rigid body system dynamical model was produced. The simulation for ride comfort performances was studied, and good results were obtained.(2) The road model and suspension performance indexes was chosen and built. Combining the advantages of fuzzy control and PID control strategy, a fuzzy-PID controller was designed for active suspension. The genetic algorithm was used to design the quantified factors of the fuzzy controller and the three correction factors of the PID. Compared with the active suspension with PID or Fuzzy-PID control strategy and passive suspension, the results showed the active suspension with fuzzy-PID controller via genetic algorithm could improve the ride comfort and handling performances much better.
Keywords/Search Tags:Vehicle ride comfort, Active Suspension, Fuzzy-PID Control strategy, Genetic algorithm, Co-simulation
PDF Full Text Request
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