Abstract: Accurate identification and estimation of tractor running state is an important basis for its safe driving and smooth control. Aiming at the problems of complex estimation and low accuracy of state parameters of large tractors, a three-degree-of-freedom simulation model of large tractors was established, including Dugoff tire model. The state parameter estimation algorithm of large tractor based on volume Kalman filter theory was proposed. Then, the driving parameters of large tractors were estimated, including longitudinal speed, lateral speed, sideslip angle of center of mass and yaw rate. Finally, the Matlab software was used to simulate and verify, and the simulated state parameters were compared with the values estimated by the algorithm under the condition that the adhesion coefficient of the double-shift line surface was 0.8 and 0.6. The results showed that the errors between the simulated values of yaw rate, sideslip angle of center of mass and longitudinal speed of tractor and the real values were 0.1, 0.2 and 0.4, respectively, which verified the feasibility and accuracy of estimating the state parameters of large tractors based on the volumetric Kalman filter algorithm, and provided reference for the stability control of large tractors.

Key words: large tractor, nonlinear dynamics, volumetric kalman filtering, state parameter, Dugoff tire model

摘要： 拖拉机运行状态的准确识别与估计是其安全行驶和平稳控制的重要依据。针对大型拖拉机状态参数的估计复杂、精确度不高等问题，建立大型拖拉机整车三自由度仿真模型，其中包含Dugoff轮胎模型，提出基于容积卡尔曼滤波理论的大型拖拉机状态参数估计算法，并对大型拖拉机的行驶参数进行估计，包含纵向速度、侧向速度、质心侧偏角、横摆角速度。利用Matlab软件仿真验证，在双移线路面附着系数为0.8和0.6的工况下，对比仿真的状态参数和算法估计的数值。结果表明，拖拉机横摆角速度、质心侧偏角和纵向速度仿真值与真实值的误差分别为0.1、0.2、0.4，验证基于容积卡尔曼滤波算法对大型拖拉机状态参数估计的可行性和准确性，为大型拖拉机的稳定性控制等提供借鉴和参考。

关键词: 大型拖拉机, 非线性动力学, 容积卡尔曼滤波, 状态参数, Dugoff轮胎模型