非高斯随机路面下八轮重型车辆悬架的减振控制方法研究

韩祎; 董龙雷; 唐攀涛

doi:10.13433/j.cnki.1003-8728.20220136

非高斯随机路面下八轮重型车辆悬架的减振控制方法研究

doi: 10.13433/j.cnki.1003-8728.20220136

西安交通大学航天航空学院机械结构及强度国家重点实验室, 西安 710049

基金项目:

山东省重大创新工程项目 2019JZZY020215HZ

详细信息

作者简介:
韩祎(1991-), 博士研究生, 研究方向为复杂结构建模及减振控制, hanyijy@stu.xjtu.edu.cn

通讯作者:
董龙雷, 教授, 博士生导师, dongll@xjtu.edu.cn

中图分类号: TG156
计量
- 文章访问数: 173
- HTML全文浏览量: 180
- PDF下载量: 84
- 被引次数: 0
出版历程
- 收稿日期: 2021-11-25
- 刊出日期: 2023-10-25

Study on Damping Control Method of Eight-wheel Heavy Vehicle Suspension Under Non-Gaussian Random Road

State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi'an Jiaotong University, Xi'an 710049, China

摘要

摘要: 针对非高斯随机路面条件开展了八轮重型装甲车辆悬架的减振控制策略研究。当前随机路面通常采用基于功率谱密度法的高斯信号进行表征, 难以准确描述装甲车辆行驶的复杂路面工况。建立了八轮重型装甲车的整车悬架模型, 实现了对起伏路面非高斯性能的准确表征, 提出了针对非高斯随机路面的模糊自适应悬架振动控制策略。仿真结果表明: 所提出的控制策略可在装甲车所行驶的实际路面工况下对整车起到良好的减振效果, 为八轮装甲车辆的减振控制奠定了理论基础。
- 八轮重型装甲车 /
- 整车悬架模型 /
- 非高斯随机路面 /
- 模糊自适应
Abstract: In this paper, the damping control strategy of eight-wheel heavy armored vehicle suspension was studied under non-Gaussian random road conditions. At present, the random road is usually characterized by Gaussian signal based on power spectral density method, which is difficult to exactly describe the complex road conditions of armored vehicles. First, the suspension model of the eight-wheel heavy armored vehicle was established; Second, the accurate characterization of non-Gaussian performance of undulating road was realized; Finally, a fuzzy adaptive suspension vibration control strategy on non-Gaussian random roads was proposed. The simulation results show that the proposed control strategy has a good damping effect on the armored vehicle under the actual road conditions, and lays a theoretical foundation for the damping control of the armored vehicle.
- eight-wheeled heavy armored vehicle /
- vehicle suspension model /
- non-Gaussian random road /
- fuzzy adaptive control method

HTML全文

图 1 车辆运动坐标系

Figure 1. Vehicle motion coordinate system

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图 2 八轮重型车辆整车悬架模型

Figure 2. Whole vehicle suspension model of eight wheeled heavy armored vehicle

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图 3 非高斯载荷信号

Figure 3. Non-Gaussian load signal

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图 4 高斯载荷信号

Figure 4. Gaussian load signal

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图 5 功率谱密度

Figure 5. Power spectral density

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图 6 振幅概率密度分布

Figure 6. Amplitude probability density distribution

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图 7 非高斯随机路面信号

Figure 7. Non-Gaussian random road signal

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图 8 磁流变半主动悬架控制系统框图

Figure 8. Block diagram of magnetorheological semi-active suspension control system

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图 9 天棚控制策略理想模型

Figure 9. Ideal model of sky-hook control

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图 10 高斯随机路面激励下车辆质心处振动速度

Figure 10. Vibration velocity at the center of mass of the vehicle under Gaussian random road excitation

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图 11 高斯随机路面激励下车辆质心处振动位移

Figure 11. Vibration displacement at the center of mass of the vehicle under Gaussian random road excitation

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图 12 非高斯随机路面激励下车辆质心处振动速度

Figure 12. Vibration velocity at the center of mass of a vehicle under non-Gaussian random road excitation

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图 13 非高斯随机路面激励下车辆质心处振动位移

Figure 13. Vibration displacement at the center of mass of the vehicle under non-Gaussian random road excitation

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图 14 改进后非高斯随机路面激励下车辆质心处振动速度

Figure 14. Vibration velocity at the centroid of the vehicle under improved non-Gaussian random road excitation

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图 15 改进后非高斯随机路面激励下车辆质心处振动位移

Figure 15. Vibration displacement at the center of mass of the vehicle under improved non-Gaussian random road excitation

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表 1 高斯随机路面不同控制策略效果比较

Table 1. Comparison of effects of different control strategies on Gaussian random road surface

高斯随机信号	速度	位移
被动控制	0.225 9 m/s	0.037 2 m
天棚控制	0.209 9 m/s	0.0335 m
天棚控制改善比例	-7.08%	-9.95%
模糊控制	0.189 6 m/s	0.0318 m
模糊控制改善比例	-16.06%	-14.52%

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表 2 非高斯随机路面不同控制策略效果比较

Table 2. Comparison of the effects of different control strategies on non Gaussian random road surfaces

非高斯随机信号	速度	位移
被动控制	0.266 7 m/s	0.022 7 m
天棚控制	0.247 2 m/s	0.021 0 m
天棚控制改善比例	-7.31%	-7.49%
模糊控制	0.251 2 m/s	0.021 4 m
模糊控制改善比例	-5.81%	-5.72%
模糊自适应	0.230 2 m/s	0.020 1 m
模糊自适应改善比例	-13.69%	-11.45%

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