陈特,陈龙,蔡英凤,徐兴,江浩斌.基于多模型迭代的车辆状态融合估计方法[J].农业机械学报,2018,49(6):385-392.
CHEN Te,CHEN Long,CAI Yingfeng,XU Xing,JIANG Haobi.Vehicle State Fusion Estimation Method Based on Multi-model Iteration[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(6):385-392.
摘要点击次数: 1728
全文下载次数: 927
基于多模型迭代的车辆状态融合估计方法   [下载全文]
Vehicle State Fusion Estimation Method Based on Multi-model Iteration   [Download Pdf][in English]
投稿时间:2017-12-18  
DOI:10.6041/j.issn.1000-1298.2018.06.046
中文关键词:  车辆  状态估计  质心侧偏角  误差补偿  岭估计
基金项目:国家自然科学基金重点项目(U1564201、U1664258)、江苏省“六大人才高峰”项目(2014-JXQC-004)、江苏省“333”工程项目(BRA2016445)、江苏省重点研发计划项目(产业前瞻与共性关键技术)(BE2016149)和江苏省高校自然科学基金项目(16KJB580012)
作者单位
陈特 江苏大学 
陈龙 江苏大学 
蔡英凤 江苏大学 
徐兴 江苏大学 
江浩斌 江苏大学 
中文摘要:为了提高车辆行驶状态估计的可靠性,提出一种基于多模型观测器误差补偿与迭代的车辆状态融合估计方法。基于三自由度车辆动力学模型设计了车辆状态强跟踪滤波估计算法;同时,根据四轮轮速耦合关系,考虑到数据扰动和病态矩阵的影响,设计了车辆状态的岭估计算法。为进一步提高估计系统的可靠性,提出了动力学模型观测器与运动学模型观测器补偿与迭代的估计方式,设计了模糊控制器,根据实时的质心侧偏角和滑移率的伪量测值,判断强跟踪滤波器和岭估计器估计结果所占权重,利用闭环估计系统的迭代与融合提高估计性能。仿真和道路实验结果表明,所提出的车辆状态融合估计方法能够兼顾强跟踪滤波算法与岭估计算法的优势,根据车辆纵向滑移和质心侧偏角动态调节强跟踪估计与岭估计结果的权重系数,从而在保证估计精度的同时提高了估计系统的多工况适应能力。
CHEN Te  CHEN Long  CAI Yingfeng  XU Xing  JIANG Haobi
Jiangsu University,Jiangsu University,Jiangsu University,Jiangsu University and Jiangsu University
Key Words:vehicle  state estimation  sideslip angle  error compensation  ridge estimation
Abstract:In order to improve the reliability of vehicle running state estimation, a vehicle state fusion estimation method based on multi-model observer error compensation and iteration was proposed. A strong-tracking filter estimation algorithm was presented for vehicle state estimation based on three-degree-of-freedom vehicle dynamics model, meanwhile, using the coupling relationship of four wheel speed, a ridge estimation algorithm for vehicle state estimation was designed considering the influence of data disturbance and ill-conditioned matrix. To further improve the reliability of estimation system, an estimation strategy with the error compensation and iteration between the dynamic-model-based observer and the kinematic-model-based observer was developed, a fuzzy controller was designed which was used to judge the weight of strong tracking filter and ridge estimator according to the real-time pseudo measurement value of sideslip angle and longitudinal slip rate, and then estimation performance was improved by iteration and fusion of the closed-loop estimation system. The results of the simulation and road test showed that the proposed vehicle state fusion estimation method can integrate the advantages of strong tracking filter algorithm and ridge estimation algorithm, dynamically adjust the weight coefficients of strong tracking filter and ridge estimation results according to the vehicle longitudinal slip ratio and sideslip angle, guarantee the estimation accuracy and synchronously improve the adaptability of the estimation system under multiple conditions.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

   下载PDF阅读器