On-line Model Recursive Identification for Variable Parameters of Driveline Vibration

Paper #:
  • 2017-01-2428

  • 2017-10-08
Abstract: The vehicle driveline suffers low frequency torsional vibration because of the abrupt change of torque and torque fluctuation of variable frequency. This problem can be solved by model-based predictive control, so building a control oriented driveline model is extremely important. The traditional off-line identified model which does not consider driveline parameter variation such as damping of tire and suspension during vehicle operation cannot accurately reflect the true characteristics of the driveline vibrations. And usually the fixed stiffness is considered, this will cause modeling errors and worse result of vibration control, in this paper, an on-line recursive identification method is proposed and verified based on an electric car. First of all, as for the low frequency vibration, the control oriented model is simplified into a six-parameter model with double inertia. Then based on stability analysis, motor torque and motor speed were determined as input signal for on-line identification. The recursive identification algorithm was designed and implemented by using Matlab/Simulink, meanwhile a detail model of the vehicle which considered driveline parameter variation was built using ADAMS. At last on-line identification is conducted with the co-simulation of ADAMS and Simulink for verification. Simulation results show that the identification is convergent and the identified dynamic stiffness has two significant minimum points, the minimum value appears different when changing the tire damping in ADAMS and it matches well with resonance frequency in ADAMS. Compared with theoretical dynamic stiffness calculated from real vehicle parameters, the identified dynamic stiffness matches well below 400rad/s and has certain offset in minimum value due to the simplification of damping. So compared with traditional off-line identification, the on-line recursive identification algorithm can be used to solve the problem of variable parameters during the entire vehicle operation period, modeling error can be reduced and better vibration control results can be achieved. Key words : driveline torsional vibration, on-line recursive identification, dynamic stiffness
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