考虑参数自适应的电液馈能悬架LQR控制研究

邹俊逸1, 2, 程 进1, 2, 左鑫凯1, 2, 郭思婧3

振动与冲击 ›› 2025, Vol. 44 ›› Issue (9) : 109-118.

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振动与冲击 ›› 2025, Vol. 44 ›› Issue (9) : 109-118.
振动理论与交叉研究

考虑参数自适应的电液馈能悬架LQR控制研究

  • 邹俊逸1,2, 程 进1,2, 左鑫凯1,2,郭思婧*3
作者信息 +

LQR control of electro-hydraulic energy-regenerative suspension considering parametric adaptation

  • ZOU Junyi1,2, CHENG Jin1,2, ZUO Xinkai1,2, GUO Sijing*3
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文章历史 +

摘要

电液馈能悬架具有阻尼调节和能量回收的功能,兼顾了减振和能耗两方面,合理的控制系统设计可有效改善车辆的平顺性和能耗水平,因此,本文针对电液馈能悬架提出了一种考虑参数自适应的线性二次型调节器(Linear quadratic regulator,LQR)控制策略,旨在实现控制系统的快速收敛和性能最优化。首先,由于传统LQR控制器在参数选择上对于经验存在较高的依赖性,本文利用改进鲸鱼算法实现了加权系数的自适应寻优,可有效提高控制系统的计算效率;其次,将传统鲸鱼算法中的线性收敛因子改为非线性收敛因子,实现全局寻优和局部寻优的平衡,可较好地降低寻优的时间;此外,为解决现有算法容易陷入局部最优的问题,还提出了一种结合自适应权重系数和随机差分变异的策略来代替鲸鱼算法中的个体更新策略。最后,基于AMESim建立了电液馈能减振器的仿真模型,并搭建了实验台架,展开了阻尼特性等实验,仿真结果与实验数据吻合,验证了电液馈能减振器模型的精确性;在此基础上,基于MATLAB/Simulink分别搭建了LQR、传统鲸鱼算法优化LQR和改进鲸鱼算法优化LQR三种控制器,构建了MATLAB/AMESim的联合仿真模型,在随机路面上进行对比分析,仿真结果表明,基于改进鲸鱼算法优化的LQR控制器可以使车身加速度、悬架动位移均方根值分别降低38.17%、74.71%,悬架的馈能功率、车轮动位移分别提高了22.50%、8.55%,验证了所提方法的可行性和有效性。

Abstract

Electro-hydraulic energy-regenerative suspension(EHERS) has the functions of damping adjustment and energy recovery, which takes into account both vibration damping and energy consumption. And the reasonable control system design can effectively improve the ride comfort of the vehicle and the level of energy consumption, therefore, this paper proposes a LQR control strategy considering parameter adaptation for electro-hydraulic energy-regenerative suspension, aiming at realizing rapid convergence of the control system and optimization of the performance. Firstly, since the traditional LQR controller has a high dependence on experience in parameter selection, this paper utilizes the improved whale algorithm to realize the adaptive optimization of weighting coefficients, which can effectively improve the computational efficiency of the control system; Secondly, the linear convergence factor in the traditional whale algorithm is changed to a nonlinear convergence factor to realize the balance between global and local optimization, which can better reduce the time of optimization; In addition, in order to solve the problem that the existing algorithms are easy to fall into the local optimum, a strategy combining adaptive weight coefficients and stochastic difference variants is proposed to replace the individual update strategy in the whale algorithm. Finally, the simulation model of electro-hydraulic energy-regenerative damper is established based on AMESim, and the experimental bench is built to carry out the experiments of damping characteristics. The simulation results match the experimental data, which verifies the accuracy of theelectro-hydraulic energy-regenerative damper model; On this basis, three kinds of controllers, LQR, traditional whale algorithm optimized LQR and improved whale algorithm optimized LQR, are built based on MATLAB/Simulink respectively, and the co-simulation model of MATLAB/AMESim is constructed for comparative analysis on random road surface. Simulation results show that the improved whale algorithm optimized LQR controller can reduce the root mean square value of body acceleration and suspension dynamic displacement by 38.17% and 74.71%, respectively, and improve the regenerative power of suspension and wheel dynamic displacement by 22.50% and 8.55%, respectively, which verifies the feasibility and effectiveness of the proposed method.

关键词

电液馈能悬架 / LQR控制器 / 参数自适应 / 改进鲸鱼算法

Key words

electro-hydraulic regenerative suspension / LQR controller / parameter adaptation / improved whale algorithm

引用本文

导出引用
邹俊逸1, 2, 程 进1, 2, 左鑫凯1, 2, 郭思婧3. 考虑参数自适应的电液馈能悬架LQR控制研究[J]. 振动与冲击, 2025, 44(9): 109-118
ZOU Junyi1, 2, CHENG Jin1, 2, ZUO Xinkai1, 2, GUO Sijing3. LQR control of electro-hydraulic energy-regenerative suspension considering parametric adaptation[J]. Journal of Vibration and Shock, 2025, 44(9): 109-118

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