# Research on Ride Comfort Control of Air Suspension Based on Genetic Algorithm Optimized Fuzzy PID
## 1 Introduction  
The air suspension system boasts superior attributes such as variable stiffness, low vibration frequency, and resistance to road impacts. When integrated into vehicle suspension systems, it significantly improves both ride comfort and handling stability while also minimizing damage to road surfaces [1]. Particularly, the electronic control air suspension system can adjust control forces based on input parameters, enabling adjustments to vehicle posture (especially vehicle height). According to various driving conditions, the suspension system achieves optimal matching and coordinated control of stiffness and damping to adapt to various vehicle usage scenarios, thereby improving the overall performance of vehicles. [PERSON] conducted control research on the suspension system of electric vehicles by establishing PID control semi-active suspension models and skyhook damping control semi-active suspension models. The results indicated that the PID control semi-active suspension increased the peak value and root mean square (RMS) of suspension dynamic deflection, while the skyhook damping control semi-active suspension increased the peak value and RMS of tire dynamic deformation. This verified the mutual influenceamong suspension smoothness evaluation indicators, demonstrating that improving one performance aspect might reduce another [2]. [PERSON] studied vehicle ride comfort by investigating the height adjustment of air springs during the inflation and deflation process of electronically controlled active air suspension. By applying fuzzy PID controllers and BP-PID controllers to analyze the vehicle ride comfort during height changes of free diaphragm air springs, it was found that the fuzzy PID controller effectively suppressed the vertical acceleration of the car body, particularly when the vertical acceleration exceeded 1.0 m/s\({}^{2}\). The BP-PID controller effectively suppressed vertical acceleration above 0.8 m/s\({}^{2}\), thereby improving ride comfort [3]. [PERSON] presented an adaptive sliding-mode control method, which is used to stabilize the displacement of electronically controlled air suspension in the presence of parameter uncertainties. Simulation research showed that the proposed control method can obtain satisfactory control performance for electronically controlled air suspension [4]. A hybrid fuzzy and proportional-integral-derivative (PID) controller is proposed for roll angle handling of a three-axle truck with an active air suspension system, the pitch angle is controlled by the active suspension system. Roll reduction of a heavy vehicle can improve the ride comfort and rollover tendency of the truck [5]. A fuzzy controller is proposed for the insufficient roll resistance of D23. The results show that the designed controller can further effectively improve the handling stability of vehicles [6]. An optimal fuzzy control with control rules optimized by the genetic algorithm is proposed to evaluate the performance of the control damping and the control air spring of the vehicle air suspension system on ride comfort and road friendliness [7]. An innovative design of an adaptive air suspension system with an LQR control strategy is proposed, and a dynamic model of an air suspension system used in passenger vehicles was designed and simulated for both passive and adaptive systems in MATLAB [8]. A height control strategy for the sprayer body was formulated, and sliding mode control and the on-off control were used to design the suspension height stability controller. The simulation experiment results showed that sliding mode control and on-off control could track and stabilize the height of the sprayer body when it changed under no excitation and D-grade road random excitation. Compared with the on-off control method, the sliding mode control approach had good control ability and precision due to its robustness to change in model parameters [9]. Domestic and international scholars conducted control research on suspension systems based on PID control theory [10; 11; 12; 13; 14].