基于改进鲸鱼优化算法的主动悬架控制策略
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天津理工大学创新创业计划性项目(202210060090)

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    摘要:

    汽车主动悬架一直是汽车悬架控制领域的研究热点,而主动悬架中控制器的选取以及相关参数的设定决定了主动悬架的优劣.针对控制器相关参数如何快速、准确地对真实路面情况进行自适应调整问题,本文对鲸鱼优化算法进行改进作为Smith-PID控制器参数调整算法,设计了一款基于改进鲸鱼优化算法参数自整定PID控制器.该悬架结合悬架动挠度、车身垂向加速度和车轮动位移等指标建立综合评价指标反馈给改进鲸鱼算法对控制器的参数进行实时整定.为了验证该控制器的有效性,本文建立了主动悬架系统仿真模型和被动悬架、两类典型的主动悬架进行了对比.仿真结果表明,本文提出的控制器能明显改善车辆平顺性,提高车辆的平稳性和乘坐舒适性.

    Abstract:

    The parameter adaptive adjustment of automobile active suspension controller has always been a research hotspot in the field of automobile suspension control. In this paper, the whale optimization algorithm is selected as the parameter adjustment algorithm of the controller, and the improvement strategy of the algorithm is proposed. Based on this, a parameter self-tuning PID controller based on the improved whale optimization algorithm is designed. Based on the suspension dynamic deflection, body vertical acceleration and wheel dynamic displacement, the dimensionless evaluation index is built to feed back to the improved whale algorithm to adjust the controller parameters in real time. In order to verify the effectiveness of the controller, the simulation model of active suspension system is established and compared with different active suspension systems in transverse and longitudinal aspects. The simulation results show that the controller proposed in this paper can obviously improve the ride comfort, ride stability and ride comfort of the vehicle.

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李登科,冯晶晶,王忠玉,孙睿翎.基于改进鲸鱼优化算法的主动悬架控制策略[J].动力学与控制学报,2024,22(11):20~27; Li Dengke, Feng Jingjing, Wang Zhongyu, Sun Ruiling. Active Suspension Control Strategy Based on Improved Whale Optimization Algorithm[J]. Journal of Dynamics and Control,2024,22(11):20-27.

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  • 收稿日期:2024-03-22
  • 最后修改日期:2024-04-17
  • 在线发布日期: 2024-11-29
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