基于模糊PID算法的车身稳定控制策略与多工况联合仿真
CSTR:
作者:
作者单位:

重庆大学 机械与运载工程学院,机械传动国家重点实验室,重庆 400044

作者简介:

E-mail: yongjun.pan@cqu.edu.cnE-mail: yongjun.pan@cqu.edu.cn

通讯作者:

E-mail: yongjun.pan@cqu.edu.cn

基金项目:

国家自然科学基金资助项目(11702039)


MULTI-CONDITION CO-SIMULATIONS OF VEHICLE STABILITY CONTROL VIA FUZZY PID ALGORITHM
Author:
Affiliation:

School of Automotive Engineering/State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044,China

Fund Project:

The project supported by the National Natural Science Foundation of China (11702039)

  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [16]
  • |
  • 相似文献
  • |
  • 引证文献
  • | |
  • 文章评论
    摘要:

    汽车电子稳定系统(ESP)是一项关键的主动安全配置,它能够在车辆高速过弯时防止出现侧滑和失控,维持汽车的稳定行驶.为了评估并提高不同工况下整车行驶的稳定性,就需要对目前的车身稳定控制算法进行比较并改进.本文基于Carsim软件建立了某乘用车的整车动力学模型,联合Simulink软件进行车身稳定控制的联合仿真.把整车行驶的侧向位移、质心侧偏角、横摆角速度和侧向加速度等动力学参数作为评价量,基于双移线、正弦和角阶跃工况,采用传统的PID控制算法和目前较新的模糊PID控制算法对整车的行驶稳定性进行控制.仿真结果表明,模糊PID控制策略的实时性和自适应性更好,能够提升整车的行驶稳定性和成员的驾乘舒适性.

    Abstract:

    The vehicle electronic stability program (ESP) is a critical active safety configuration. It can work correspondingly to ensure the driving stability when the vehicle corners with high speeds. It is necessary to compare and improve the stability control algorithm to evaluate and enhance the vehicle stability in different conditions. In this paper, traditional and fuzzy PID algorithms are presented to simulate the vehicle high speed cornering. A vehicle dynamic model built up Carsim is used for the vehicle stability control. The lateral displacement, vehicle side slip angle, yaw rate and lateral acceleration are selected as parameters for stability evaluations. Afterwards, the co-simulation of vehicle stability control in double shifting, sine and angle step conditions are performed. The simulation results show that the fuzzy PID algorithm based vehicle controller employing the fuzzy PID algorithm meets the stability requirements in different conditions.

    参考文献
    [1] Choi S. Antilock brake system with a continuous wheel slip control to maximize the braking performance and the ride quality. IEEE Transactions on Control Systems Technology, 2008, 16(5):996~1003
    [2] 陈炯, 王会义, 宋健. 基于滑移率和减速度的ABS模糊控制仿真研究. 汽车工程, 2006, 28 (2): 148~151
    [3] 王姝, 蹇小平, 张凯, 等. 纯电动汽车牵引力控制系统(TCS)的研发与开发. 汽车安全与节能学报, 2015, 10(2): 346~353
    [4] Han K, Choi M , Lee B,et al. Development of a traction control system using a special type of sliding mode controller for hybrid 4WD vehicles. IEEE Transactions on Vehicular Technology, 2018, 67(1): 264~274
    [5] 卢少波, 李以农, 郑玲. 基于制动与悬架系统的车辆主动侧翻控制的研究. 汽车工程, 2011, 33(8): 670~675
    [6] 张云清, 高斯, 李凌阳, 等. 基于多体动力学的车辆动力学控制系统仿真及优化. 动力学与控制学报, 2007, 5 (1): 68~74
    [7] 赵树恩, 刘秋杨. 基于分数阶PID理论的汽车线控转向的主动控制. 汽车安全与节能学报, 2019, 10 (2): 161~168
    [8] 张志勇, 唐磊, 郝威,等. 轮毂驱动电动汽车差动助力转向变论域模糊PID控制. 汽车安全与节能学报, 2019, 10(2): 169~177
    [9] 唐传茵, 马岩, 赵广耀, 等. 基于模糊控制策略的车辆主动悬架研究. 动力学与控制学报, 2015,13 (3):210~214
    [10] 孙大许, 兰凤崇, 何幸福,等. 双电机四轮驱动电动汽车自适应驱动防滑控制的研究. 汽车工程, 2016, 38 (5):600~608
    [11] Jalali K, Uchida T, Mcphee J, et al. Development of an advanced fuzzy active steering controller and a novel method to tune the fuzzy controller. SAE International Journal of Passenger Cars-Electronic and Electrical Systems, 2013, 6(1): 241~254
    [12] Manhtuan D, Man Z H, Zhang C S, et al. Robust sliding mode learning control for uncertain discrete-time multi-input multi-output systems. IET Control Theory and Applications, 2014, 8(12): 1045~1053
    [13] 李果, 杨建民. 基于L2干扰抑制理论的电动汽车车身稳定系统控制. 北京信息科技大学学报, 2019, 34(1):1~6
    [14] 陈无畏, 刘翔宇, 黄鹤, 等. 考虑路面影响的车辆稳定性控制质心侧偏角动态边界控制. 机械工程学报, 2012,48(14):112~118
    [15] 高振海, 王竣, 郭健.汽车稳定性多控制工况设计及其切换机制研究. 机械工程学报, 2014, 50 (4):107~112
    [16] 王其东, 王金波, 陈无畏,等.基于汽车行驶安全边界的EPS与ESP协调控制策略. 机械工程学报, 2016, 52 (6):99~107
    相似文献
    引证文献
引用本文

聂小博,熊玥,潘勇军.基于模糊PID算法的车身稳定控制策略与多工况联合仿真[J].动力学与控制学报,2021,19(3):46~52; Nie Xiaobo, Xiong Yue, Pan Yongjun. MULTI-CONDITION CO-SIMULATIONS OF VEHICLE STABILITY CONTROL VIA FUZZY PID ALGORITHM[J]. Journal of Dynamics and Control,2021,19(3):46-52.

复制
分享
文章指标
  • 点击次数:1096
  • 下载次数: 1514
  • HTML阅读次数: 71
  • 引用次数: 0
历史
  • 收稿日期:2019-12-31
  • 最后修改日期:2020-08-29
  • 在线发布日期: 2021-07-06
文章二维码

微信公众号二维码

手机版网站二维码