VEHICLE TRACTION FORCE CONTROL BASED ON THE ROAD ADHESION COEFFICIENT ESTIMATION BY FFUKF
-
摘要: 以后驱牵引车为研究对象, 设计了基于路面附着系数估计的牵引力控制系统(TCS). 在路面附着系数估计方面, 针对传统卡尔曼滤波难以跟踪时变非线性系统的问题, 本文将模糊控制理论和衰减记忆滤波思想引入无迹卡尔曼滤波, 设计一种基于模糊遗忘因子的无迹卡尔曼滤波路面附着系数估计方法, 提高了算法的跟踪性能. 牵引力控制包括扭矩控制和制动控制. 在TCS扭矩控制方面, 分别利用路面附着系数和驱动轮滑转率在目标滑转率附近时的车辆加速度计算目标基础扭矩, 根据车辆行驶状态和抖振度参量, 基于可拓控制理论划分经典域、可拓域和非域, 通过可拓集的关联函数得到动态权重系数, 将上述两种方法计算得到的目标基础扭矩进行可拓融合设计出基础扭矩. 之后, 以实际滑转率和目标滑转率之间的误差作为输入, 采用模糊自整定PI控制器得到目标反馈扭矩. 在制动控制方面, 针对两种典型路面分别设计了PI控制压力和附着差压力. 实车试验结果表明, 基于模糊遗忘因子的无迹卡尔曼滤波算法能够更加快速地跟踪路面附着系数的变化, 同时基于路面附着系数估计的TCS控制策略能够有效抑制驱动轮过度滑转, 将驱动轮滑转率控制在最佳范围内, 显著提高了车辆的动力性.Abstract: Traction control system (TCS) based on road adhesion coefficient estimation is designed for the rear drive tractor. Firstly , to track the time-varying nonlinear system in the classical Kalman filter, a fuzzy control theory and an attenuated memory filter are introduced into untraced Kalman filter, and the fuzzy forgetting factor unscented Kalman filter (FFUKF) is proposed to estimate road adhesion coefficient, so as to improve the tracking performance of the algorithm. Traction control includes torque control and braking control. Then, for the TCS torque control, the road adhesion coefficient and the vehicle acceleration when the slip rate of the driving wheel is near the target slip rate are used to calculate the target base torque, respectively. According to the vehicle state and chattering parameters, the extension set is divided into the classical domain, extension domain and non-domain with the extension control theory, and the dynamic weight coefficient is obtained by the correlation function of extension set. The base torque is designed by extension fusion of the target base torques calculated by the above methods. Next, the error between the actual slip rate and the target slip rate is used as the input, and the target feedback torque is obtained by using the fuzzy self-tuning PI controller. In terms of braking control, the PI pressure control and adhesion difference pressure are designed on two typical road surfaces, respectively. Finally, the test results show that the proposed FFUKF algorithm can track the tire-road friction coefficient more quickly, and the proposed TCS control strategy can effectively restrain the excessive slip of the driving wheels to control the slip rate of drive wheel in the best range, so that improving vehicle dynamic performance significantly.
-
图 11 均一低附路面实车试验结果
Figure 11. Real vehicle results on the uniform road with low road adhesion coefficient
表 1 模糊推理则表
Table 1. Fuzzy inference table
NB NM ZO PM PB NB LL LM BM BM M NM LM LM BM M M ZO LM M BB M LM PM M M BM LM LM PB M BM BM LM LL 
下载: 导出CSV
表 2 模糊自整定PI的模糊规则
Table 2. Fuzzy rules of fuzzy adaptive PI
$ |E| $ LL LM M BM BB $ {k_p} $ LL LM M BM BB $ {k_i} $ BB BM M LM LL
下载: 导出CSV
表 3 试验车辆参数配置
Table 3. Vehicle parameters
Parameter Value m/kg 6800 L/m 3.9 $ {L_f} $/m 1.49 $ {L_r} $/m 2.485 $ {h_g} $/m 1.123 $ {P_m} $/kW 370 $ {T_m} $/(N·m) 2300
下载: 导出CSV
-
[1] 李贵强. 基于自抗扰算法的电动汽车牵引力系统优化控制技术研究. [博士论文]. 北京: 中国科学院大学, 2020Li Guiqiang. Study on optimization of electric vehicle traction control system base on ADRC algorithm. [PhD Thesis]. Beijing: University of Chinese Academy of Sciences, 2020 (in Chinese) [2] 冉旭. 牵引力控制系统中压力与扭矩的协调控制. [硕士论文]. 秦皇岛: 燕山大学, 2013Ran Xu. Coordinated control based on brake pressure and engine torque in traction control system. [Master Thesis]. Qinhuangdao: Yanshan University, 2013 (in Chinese) [3] 林棻, 王少博, 赵又群等. 基于改进Keras模型的路面附着系数估计. 机械工程学报, 2021, 57(12): 74-86 (Lin Fen, Wang Shaobo, Zhao Youqun, et al. Road friction coefficient estimation based on improved Keras model. Journal of Mechanical Engineering, 2021, 57(12): 74-86 (in Chinese)Lin Fen, Wang Shaobo, Zhao Youqun et al. Road friction coefficient estimation based on improved Keras model. Journal of Mechanical Engineering, 2021, 57(12): 74-86 (in Chinese) [4] 李韶华, 王桂洋, 杨泽坤等. 基于DRBF-EKF算法的车辆质心侧偏角与路面附着系数动态联合估计. 力学学报, 2022, 54(7): 1-13 (Li Shaohua, Wang Guiyang, Yang Zekun, et al. Dynamic joint estimation of vehicle sideslip angle and road adhesion coefficient based on drbf-ekf algorithm. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1-13 (in Chinese)Li Shaohua, Wang Guiyang, Yang Zekun et al. Dynamic joint estimation of vehicle sideslip angle and road adhesion coefficient based on drbf-ekf algorithm. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1-13 (in Chinese)). [5] 胡敬宇, 汪, 严永俊等. 基于限定记忆随机加权扩展卡尔曼滤波的车辆状态估计. 东南大学学报, 2022, 52(2): 387-393 (Hu Jingyu, Wang Yan, Yan Yongjun, et al. Vehicle state estimation based on limited memory random weighted extended Kalman filter. Journal of Southeast University, 2022, 52(2): 387-393 (in Chinese)Hu Jingyu, Wang Yan, Yan Yongjun et al. Vehicle state estimation based on limited memory random weighted extended Kalman filter. Journal of Southeast University, 2022, 52(2): 387-393 (in Chinese) [6] 王博, 卢萍萍, 管欣等. 路面附着系数识别方法发展现状综述. 汽车技术, 2014, 8: 1-7 (Wang Bo, Lu Pingping, Guan Xin, et al. A review on the development status of road adhesion coefficient identification approach. Automobile Technology, 2014, 8: 1-7 (in Chinese) doi: 10.3969/j.issn.1000-3703.2014.08.001(Wang Bo, Lu Pingping, Guan Xin et al. A review on the development status of road adhesion coefficient identification approach. Automobile Technology, 2014 (8): 1-7 (in Chinese)). doi: 10.3969/j.issn.1000-3703.2014.08.001 [7] Sato Y, Kobayashi D, Watanabe K, et al. Study on recognition method for road friction condition. Transactions of the Society of Automotive Engineers of Japan, 2007, 38(2): 51-56 [8] Koskinen S. Sensor data fusion based estimation of tyre-road friction to enhance collision avoidance. [PhD Thesis]. Tampere University of Technology, 2010 [9] Cho W, Choi J, Kim C, et al. Unified chassis control for the improvement of agility, maneuverability, and lateral stability. IEEE Transactions on vehicular Technology, 2012, 61(3): 1008-1020 doi: 10.1109/TVT.2012.2183152 [10] Sharifzadeh M, Akbari A, Timpone F, et al. Vehicle tyre/road interaction modeling and identification of its parameters using real-time trust-region methods. IFAC-Papers On Line, 2016, 49(3): 111-116 [11] 顾凯峰. 驾驶员行为特性及路面附着系数的车辆纵向主动安全控制研究. [硕士论文]. 重庆: 重庆交通大学, 2021Gu Kaifeng. Research on vehicle longitudinal active safety control considering driver behavior characteristics and road adhesion coefficient. [Master Thesis]. Chongqing: Chongqing Jiaotong University, 2021 (in Chinese) [12] Wang Y, Yin G, Dong H. A novel approach for tire-road friction coefficient estimation using adaptive cubature kalman filter//2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI). Hangzhou, 18-20 Dec. 2020 [13] Liu YH, Li T, Yang YY, et al. Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm. Mechanical Systems and Signal Processing, 2017, 88: 25-35 doi: 10.1016/j.ymssp.2016.07.024 [14] Pei X, Hu X, Liu W et al. State estimation of vehicle’s dynamic stability based on the nonlinear kalman filter. Automot. Innov., 2018, 1: 281-289 doi: 10.1007/s42154-018-0028-6 [15] Chen L, Bian M, Luo Y, et al. Estimation of road-tire friction with unscented Kalman filter and MSE-weighted fusion based on a modified Dugoff tire model//SAE Technical Paper, 2015-01-1601, 2015 [16] 钱华明, 葛磊, 彭宇. 多渐消因子卡尔曼滤波及其在 SINS 初始对准中的应用. 中国惯性技术学报, 2012, 20(3): 287-291 (Qian Huaming, Ge Lei, Peng Yu. Multiple fading factors Kalman filter and its application in SINS initial alignment. Journal of Chinese Inertial Technology, 2012, 20(3): 287-291 (in Chinese) doi: 10.3969/j.issn.1005-6734.2012.03.008Qian Huaming, Ge Lei, Peng Yu. Multiple fading factors Kalman filter and its application in SINS initial alignment. Journal of Chinese Inertial Technology, 2012, 20(3): 287-291(in Chinese)). doi: 10.3969/j.issn.1005-6734.2012.03.008 [17] 张浩. 基于强跟踪无迹卡尔曼滤波的结构时变参数识别. [硕士论文]. 兰州: 兰州理工大学, 2016Zhang Hao. Structural time-varying parameter identification based on strong tracking unscented Kalman filter. [Master Thesis], Lanzhou: Lanzhou University of Technology, 2016 (in Chinese) [18] 李兴佳, 李建芬, 朱敏等. 基于无迹卡尔曼滤波的定位融合与校验算法研究. 汽车工程, 2021, 43(6): 825-832 (Li Xingjia, Li Jianfen, Zhu Min, et al. Research on positioning fusion and verification algorithm based on UKF. Automotive Engineering, 2021, 43(6): 825-832 (in Chinese)Li Xingjia, Li Jianfen, Zhu Min, et al. Research on positioning fusion and verification algorithm based on UKF. Automotive Engineering, 2021, 43(6): 825-832 (in Chinese) [19] 张成宝, 吴光强, 丁玉兰等. 汽车驱动防滑的控制方法研究. 汽车工程, 2000, 22(5): 324-328 (Zhang Chengbao, Wu Guangqiang, Ding Yulan, et al. A research on the control method of vehicle anti-slip regulation. Automotive Engineering, 2000, 22(5): 324-328 (in Chinese)(Zhang Chengbao, Wu Guangqiang, Ding Yulan et al. A research on the control method of vehicle anti-slip regulation. Automotive Engineering, 2000, 22(05): 324-328 (in Chinese)). [20] 田浩. 轮毂电机汽车驱动防滑控制研究. [硕士论文]. 吉林: 吉林大学, 2022(Tian Hao. Research on acceleration slip regulation system for electric vehicles with in-wheel motors. [Master Thesis]. Jilin: Jilin University, 2022 (in Chinese) [21] Ding X, Zhang L, Wang Z, et al. Acceleration slip regulation for four-wheel-independently-actuated electric vehicles based on road identification through the fuzzy logic. IFAC-Papers On Line, 2018, 51(31): 943-948 doi: 10.1016/j.ifacol.2018.10.059 [22] Dugoff H, Fancher PS, Segel L. An analysis of tire traction properties and their influence on vehicle dynamic performance. SAE transactions, 1970, 79: 1219-1243 [23] 王震坡, 薛雪, 王亚超. 基于自适应无迹卡尔曼滤波的分布式驱动电动汽车车辆状态参数估计. 北京理工大学学报, 2018, 38(7): 698-702 (Wang Zhenbo, Xue Xue, Wang Yachao. State parameter estimation of distributed drive electric vehicle based on adaptive unscented Kalman filter. Transactions of Beijing Institute of Technology, 2018, 38(7): 698-702 (in Chinese)(Wang Zhenbo, Xue Xue, Wang Yachao. State parameter estimation of distributed drive electric vehicle based on adaptive unscented Kalman filter. Transactions of Beijing Institute of Technology, 2018, 38(7): 698-702 (in Chinese)). [24] 谢文超, 赵延明, 方紫微等. 带可变遗忘因子递推最小二乘法的超级电容模组等效模型参数辨识方法. 电工技术学报, 2021, 36(5): 996-1005 (Xie Wenchao, Zhao Yanming, Fang Ziwei, et al. Variable forgetting factor recursive least squales based parameter identification method for the equivalent circuit model of the supercapacitor cell module. Transactions of China Electrotechnical Society, 2021, 36(5): 996-1005 (in Chinese)Xie Wenchao, Zhao Yanming, Fang Ziwei et al. Variable forgetting factor recursive least squales based parameter identification method for the equivalent circuit model of the supercapacitor cell module. Transactions of China Electrotechnical Society, 2021, 36(5): 996-1005 (in Chinese)). [25] 韩伟, 王大志, 刘震. 基于可变遗忘因子RLS算法的谐波电流检测方法. 电工技术学报, 2013, 28(12): 70-74 (Han Wei, Wang Dazhi, Liu Zhen. A harmonic current detection method based on variable forgetting factor RLS algorithm. Transactions of China Electrotechnical Society, 2013, 28(12): 70-74 (in Chinese)Han Wei, Wang Dazhi, Liu Zhen. A harmonic current detection method based on variable forgetting factor RLS algorithm. Transactions of China Electrotechnical Society, 2013, 28(12): 70-74 (in Chinese [26] 潘冬, 郭林, 李玉善. 高速公路隧道智能照明控制系统研究. 山东交通科技, 2021, 3: 89-92 (Pan Dong, Guo Lin, Li Yushan. Study on intelligent lighting control system of expressway tunnel. Shandong Communications Technology, 2021, 3: 89-92 (in Chinese)Pan Dong, Guo Lin, Li Yushan, Study on intelligent lighting control system of expressway tunnel. Shandong Communications Technology, 2021(3): 89-92 (in Chinese) [27] 刘佳佳, 左兴权. 交叉口交通信号灯的模糊控制及优化研究. 系统仿真学报, 2020, 32(12): 2401-2408 (Liu Jiajia, Zuo Xingquan. Research on fuzzy control and optimization for traffic lights at single intersection. Journal of System Simulation, 2020, 32(12): 2401-2408 (in Chinese)Liu Jiajia, Zuo Xingquan. Research on fuzzy control and optimization for traffic lights at single intersection. Journal of System Simulation, 2020, 32(12): 2401-2408 (in Chinese) [28] 苑绍志, 李静, 李幼德. 考虑路面不平的牵引力控制系统. 吉林大学学报(工学版), 2007, 37(5): 990-993 (Yuan Shaozhi, Li Jing, Li Youde. Traction control system with consideration of road surf ace roughness. Journal of Jilin University (Engineering and Technology Edition) , 2007, 37(5): 990-993 (in Chinese)(Yuan Shaozhi, Li Jing, Li Youde. Traction control system with consideration of road surf ace roughness. Journal of Jilin University (Engineering and Technology Edition), 2007, 37(5): 990-993 (in Chinese)). [29] 孔磊, 宋健, 严忆泉等. 用于防抱制动系统的路面不平特征识别算法. 机械工程学报, 2007, 43(11): 229-234 (Kong Lei, Song Jian, Yan Yiquan, et al. Recognition algorithm of road roughness for anti-lock braking system. Chinese Journal of Mechanical Engineering, 2007, 43(11): 229-234 (in Chinese) doi: 10.3321/j.issn:0577-6686.2007.11.037(Kong Lei, Song Jian, Yan Yiquan et al. Recognition algorithm of road roughness for anti-lock braking system. Chinese Journal of Mechanical Engineering, 2007, 43(11): 229-234 (in Chinese)). doi: 10.3321/j.issn:0577-6686.2007.11.037 [30] 王焕清, 陈明, 刘晓平. 一类非线性系统模糊自适应固定时间量化反馈控制. 自动化学报, 2021, 47(12): 2823-2830 (Wang Huanqing, Chen Ming, Liu Xiaoping. Fuzzy adaptive fixed-time quantized feedback control for a class of nonlinear systems. ACTA Automatica Sinica, 2021, 47(12): 2823-2830 (in Chinese)(Wang Huanqing, Chen Ming, Liu Xiaoping. Fuzzy adaptive fixed-time quantized feedback control for a class of nonlinear systems. ACTA Automatica Sinica, 2021, 47(12): 2823-2830 (in Chinese)). [31] 邱灿文. 无人赛车纵向控制系统设计与研究. [硕士论文]. 广州: 广东工业大学, 2019Qiu Canwen. Design and research of longitudinal control system of unmanned racing car. [Master Thesis]. Guangzhou: Guangzhou University of Technology, 2019 (in Chinese) -
下载:
点击查看大图
图(13) / 表(3)
计量
- 文章访问数: 317
- HTML全文浏览量: 160
- PDF下载量: 55
- 被引次数: 0
