A Frequency Compensation Algorithm of Four-Wheel Coherence Random Road

The road surface roughness is the main source of kinematic excitation of a moving vehicle, which has an important influence on vehicle performance. In recent decades, random road models have been widely studied, and a four-wheel random road time domain model is usually generated based on the correlation of the four-wheel input, in which a coherence function is used to describe the coherence of the road input between the left and right wheels usually. However, during our research, there are some conditions that show that the road PSD (power spectral density) of one wheel is smaller than the other one on the same axle. Actually, it is caused by the uncorrelation between the left- and right-wheel road surface roughness. Hence, a frequency compensation algorithm is proposed to correct the deviation of the PSD of the road input between two wheels on the same axle, and it is installed in a 7-DOF vehicle dynamic study. The simulation result demonstrates the applicability of the proposed algorithm such that two-wheel road input deviation compensation has an important influence on vehicle performances, and it can be used for a control system installed in the vehicle to compensate road roughness for damper tuning in the future.

[1]  Igor Rychlik,et al.  Models for road surface roughness , 2012 .

[2]  D. Cebon,et al.  Artificial Generation of Road Surface Topography by the Inverse F.F.T. Method , 1983 .

[3]  A N Heath EVALUATION OF THE ISOTROPIC ROAD ROUGHNESS ASSUMPTION , 1988 .

[4]  J. D. Robson,et al.  The application of isotropy in road surface modelling , 1978 .

[5]  David Cebon,et al.  Interaction Between Heavy Vehicles and Roads , 1993 .

[6]  J. D. Robson ROAD SURFACE DESCRIPTION AND VEHICLE RESPONSE , 1979 .

[7]  K. Bogsjö Coherence of road roughness in left and right wheel-path , 2008 .

[8]  Samy Aly Hassan,et al.  Identification of road surface qualities for linear and non-linear vehicle modeling , 2002 .

[9]  A. N. Heath Application of the isotropic road roughness assumption , 1987 .

[10]  D. Whitehouse,et al.  The properties of random surfaces of significance in their contact , 1970, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[11]  Klas Bogsjö Evaluation of stochastic models of parallel road tracks , 2007 .

[12]  David Cebon,et al.  THE ARTIFICIAL GENERATION OF ROAD SURFACE TOPOGRAPHY BY THE INVERSE FFT METHOD , 1984 .

[13]  Kjell Ahlin,et al.  Comparing road profiles with vehicle perceived roughness , 2004 .

[14]  M. Shinozuka,et al.  Digital simulation of random processes and its applications , 1972 .

[15]  C. J. Dodds The Laboratory Simulation of Vehicle Service Stress , 1974 .

[16]  Toshio Yoshimura A SEMI-ACTIVE SUSPENSION OF PASSENGER CARS USING FUZZY REASONING AND THE FIELD TESTING , 2014 .

[17]  G. Carter Coherence and time delay estimation , 1987, Proceedings of the IEEE.

[18]  J. D. Robson,et al.  The description of road surface roughness , 1973 .

[19]  Robert Evans,et al.  Road roughness characteristics in car and truck wheel tracks , 2013 .

[20]  Jiunn-Jong Wu Simulation of rough surfaces with FFT , 2000 .

[21]  D. Ammon PROBLEMS IN ROAD SURFACE MODELLING , 1992 .

[22]  Peter Múčka,et al.  ROAD WAVINESS AND THE DYNAMIC TYRE FORCE , 2004 .

[23]  Ivan Prebil,et al.  Creating models of road sections and their use in driving dynamics simulations , 2007 .

[24]  J. D. Robson,et al.  Implications of isotropy in random surfaces , 1977 .

[25]  Dongpu Cao,et al.  Modeling and validation of off-road vehicle ride dynamics , 2012 .

[26]  Chen Sizhong,et al.  Model of excitation of random road profile in time domain for a vehicle with four wheels , 2011, 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC).

[27]  Mircea Grigoriu,et al.  On the spectral representation method in simulation , 1993 .

[28]  Zhang Yonglin,et al.  Numerical simulation of stochastic road process using white noise filtration , 2006 .