车辆半主动悬架变论域模糊PID控制研究

Research on variable universe fuzzy PID control for vehicle
semi-active suspensions

摘要

为了改善车辆的平顺性,提出了一种融合灰狼优化机制的变论域模糊PID控制策略(GWO-VUFPID),分别建立了二自由度悬架模型、模糊PID、变论域模糊PID控制器(VUFPID)及GA-VUFPID,并针对基于VUFPID控制的半主动悬架系统,使用灰狼算法(GWO)优化模糊PID控制器的比例因子,在C级路面下运行仿真,与VUFPID控制、模糊PID控制半主动悬架及被动悬架进行对比分析。仿真结果显示:在车身加速度方面,GWO-VUFPID控制得到的车身加速度均方根值比被动悬架、模糊PID、VUFPID及GA-VUFPID控制分别降低了24.84%、13.75%、6.58%、2.38%;在悬架动挠度方面,GWO-VUFPID控制的悬架动挠度均方根值比被动悬架、模糊PID、VUFPID及GA-VUFPID控制分别降低了34.69%、20.00%、6.90%、2.33%;在轮胎动载荷方面,4种控制策略与被动悬架无明显差距,表明GWO-VUFPID在车身加速度和悬架动挠度方面表现出更优性能,验证了其在非线性车辆悬架控制领域的可行性和有效性。

Abstract

To improve vehicle ride comfort, this study proposed a variable universe fuzzy PID control strategy integrating the gray wolf optimizer mechanism (GWO-VUFPID). A 2-degree-of-freedom suspension model, a fuzzy PID controller, a variable universe fuzzy PID controller (VUFPID) and a GA-VUFPID (genetic algorithm optimized variable universe fuzzy PID) controller were established, respectively. For the semi-active suspension system based on VUFPID control, the gray wolf algorithm (GWO) was used to optimize the scale factor of the fuzzy PID controller. Simulations were carried out under the C-level road surface, and the results were compared with those of VUFPID-controlled, fuzzy PID-controlled semi-active suspensions and passive suspension. The simulation results show that, in terms of vehicle body acceleration, the root mean square value of body acceleration obtained with GWO-VUFPID control is reduced by 24.84%, 13.75%, 6.58% and 2.38% , respectively, compared with those of the passive suspension, fuzzy PID control, VUFPID control and GA-VUFPID control. In terms of suspension dynamic deflection, the RMS value of suspension dynamic deflection obtained with GWO-VUFPID control is reduced by 34.69%, 20.00%, 6.90%, and 2.33%, respectively, compared with those of the passive suspension, fuzzy PID control, VUFPID control, and GA-VUFPID control. Regarding tire dynamic load, there is no significant difference between the four control strategies and the passive suspension. The results demonstrate that GWO-VUFPID achieves better performance in both body acceleration and suspension dynamic deflection, verifying its feasibility and effectiveness in the field of nonlinear vehicle suspension control

关键词

半主动悬架 / 变论域 / 模糊PID控制 / 灰狼算法 / 行驶平顺性

Key words

semi-active suspension / variable universe / fuzzy PID control / grey wolf algorithm / ride comfort

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基金资助

山东省自然科学基金创新发展联合基金项目(ZR2024LZN012),国家自然科学基金项目(52202508)