White Noise Method for Road Roughness Simulation

Application of White Noise Method in Road Roughness Simulation

In vehicle dynamics research, accurately simulating the impact of road roughness on vehicle vibration response is crucial. The white noise method serves as a widely-used time-domain simulation approach for road unevenness characterization.

Fundamental Principle: This technique leverages the power spectral density (PSD) function of road roughness, generating random sequences that conform to specific statistical properties to emulate real-road conditions. The implementation typically involves creating Gaussian white noise through random number generators (e.g., MATLAB's randn function), followed by spectral shaping using digital filters designed to match target PSD characteristics across specified spatial frequency ranges.

Implementation Workflow: 1. Parameter Configuration: Define target road parameters including ISO road classification (A-E grades) and spatial frequency range (typically 0.011-2.83 cycles/meter) 2. Spectral Shaping: Process white noise through a shaping filter (often a first-order low-pass filter) with transfer function H(ω) = √(Gq(n0)*v/ω) where Gq(n0) is road PSD, v is vehicle velocity 3. Time-Domain Conversion: Apply inverse Fast Fourier Transform (IFFT) to generate the final road profile using MATLAB's ifft function with proper amplitude scaling Example code structure: noise = randn(1,N); shaped_signal = filter(b,a,noise); road_profile = real(ifft(shaped_signal));

Technical Features: - Accurately reproduces statistical characteristics of various road grades through PSD matching - High computational efficiency enables real-time simulation scenarios - Flexible parameter adjustment facilitates simulation of diverse road conditions via modified filter coefficients

Application Value: This method provides critical input excitation for vehicle ride comfort analysis, suspension system design, and driving simulator development, serving as a fundamental tool in vehicle dynamics research with direct implementation potential in Simulink environments.