Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer
Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer
复制标题
DOI：
10.1109/tie.2009.2013737
复制
发表时间：
2009-05-01
影响因子：
7.7
通讯作者：
Hori, Yoichi
中科院分区：
文献类型：
--
作者：
Geng, Cong;Mostefai, Lotfi;Hori, Yoichi
提出了一种基于稳定力矩器的轮式电动车辆控制算法，该算法产生直接横摆力矩来补偿状态偏差。该控制方案是基于模糊规则为基础的机构侧偏角（β）观测器。在模糊观测器的设计策略中，车辆动力学由Takagi-Sugeno类模糊模型表示。首先，本地等效车辆模型建立使用线性近似的车辆动力学低和高横向加速度运行制度，分别。然后，最优β观测器设计的每个局部模型，使用卡尔曼滤波理论。最后，局部观测器结合起来，形成整体控制系统，通过使用模糊规则。这些模糊规则表示与车辆动力学的非线性和不确定性，如轮胎力饱和和道路附着的影响的变量之间的定性关系。一个自适应机制的模糊隶属函数已被纳入，以提高系统的精度和性能。这种设计方法的有效性已被证明在模拟和实时实验设置。
A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting.