Factorial analysis of Kalman filtering for semi-active vehicle suspension control

Best, Matthew C. and Gordon, Timothyn J. (1994) Factorial analysis of Kalman filtering for semi-active vehicle suspension control. In: 2nd Biennial European Joint Conference on Engineering Systems Design and Analysis., 4 - 7 July 1994, London.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


This paper considers the design of Kalman filter observers for the on-line estimation of dynamic states of a vehicle suspension, with a view to applying semi-active suspension control. A data based identification method is presented, and two sources of data are considered; from vehicle tests on a four poster hydraulic shake rig, and also from quarter vehicle simulations. Both are subjected to a `full factorial' statistical study, and detailed conclusions are drawn concerning the relative importance of various operational parameters, in particular the type and location of feedback sensors. Finally, a `minimal' Kalman filter is designed which uses wheel hub and vehicle body mounted accelerometers alone; the resulting accuracy of state estimation is considered to be acceptable for semi-active suspension control.

Additional Information:Conference Code:21113
Keywords:Computer simulation, Control nonlinearities, Control system analysis, Degrees of freedom (mechanics), Dynamics, Kalman filtering, Mathematical models, Numerical analysis, Random processes, State estimation, Statistical methods, Vehicle suspensions, Data based identification method, Full factorial statistical analysis, Semi active suspension control, Automobile springs
Subjects:H Engineering > H331 Road Vehicle Engineering
Divisions:College of Science > School of Engineering
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ID Code:11695
Deposited On:13 Feb 2014 10:19

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