基于滑模观测器的汽车轮胎力级联估计方法

提出了一种新型的基于滑模观测器理论的汽车轮胎力级联估计方法．首先基于单轮滚动动力学模型，以车轮转动角速度及驱动力矩作为输入，针对每个车轮的纵向轮胎力设计了纵向轮胎力滑模观测器．又采用了简化的车辆2自由度模型，以纵向轮胎力估计值、 前轮转角、 侧向加速度及横摆角速度作为输入，分别设计了前、 后轴侧向轮胎力滑模观测器．最后，为验证所设计的观测器的有效性，应用高保真车辆动力学软件veDYNA进行了仿真研究，并与扩展卡尔曼滤波（extendedKalman filter，EKF）方法进行了对比分析．实验结果表明，基于滑模观测器的车辆轮胎力级联估计方法具有更高的准确性．

Cascade Tire-force Estimation Method Based on Sliding-mode Observer

We present a novel cascade tire-force estimation framework based on the sliding-mode observer method. We estimate each longitudinal tire force on the basis of the single-wheel vehicle model, which uses the angular velocity and driving torque of the wheel as inputs. Then, we apply a simplified 2-degrees-of-freedom (2-DOF) vehicle dynamic model to design the front and rear lateral-tire-force sliding-mode observer, and use the estimated longitudinal tire forces, the front-wheel angle, the lateral acceleration, and the yaw rate as the observer inputs. We experimentally evaulate the proposed tire-force estimation method on the high-precision vehicle dynamic software, veDYNA, and compare the estimation results with those of the extended Kalman filter (EKF) method. The results demonstrate that the sliding-mode observer has relatively higher accuracy in estimating tire forces.