Variable universe fuzzy control strategy optimized by sparrow search algorithm for continuous damping controllable semi-active suspension system

A continuous damping controllable semi-active suspension system adjusts damping force by regulating the CDC valve, whose effectiveness significantly depends on the precise modeling of the current and damping force, as well as the advanced optimization of the control strategy. To further enhance its comprehensive performance, this study constructs a nonlinear mapping relationship between the control current, damping coefficient, and damping force of the CDC damper based on experimental data. Utilizing this foundation, a dynamic model of the continuous damping controllable semi-active suspension system is established, and the vibration characteristics under varying road excitation amplitudes and control currents are analyzed. Subsequently, a variable universe fuzzy control strategy optimized by the sparrow search algorithm is proposed to adaptively adjust the required control current, with simulations conducted to evaluate vibration suppression performance under Grade B and C random road excitations. Results demonstrate that the proposed variable universe fuzzy control strategy optimized by sparrow search algorithm enables a rapid adjustment frequency and a broad control range of 0.23–2.00 A for the control current, markedly improving the ride comfort and handling stability of the vehicle. The comprehensive performance of the continuous damping controllable semi-active suspension system is improved by approximately 26.47% compared to passive suspension systems. This study can provide a novel design approach for intelligent control of vehicle semi-active suspension systems.