基于神经网络左逆的电动汽车质心侧偏角观测  

Sideslip angle estimated based on NNLI for electric vehicles

作　　者：缪鹏虎 刘国海[1] 张多[1] 

机构地区：[1]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《信息技术》2016年第4期117-120,共4页Information Technology

摘　　要：有效的估计车辆状态参数(如横摆角速度和质心侧偏角)对于车辆稳定性控制而言有至关重要的作用。但是能够直接测量质心侧偏角的传感器成本很高,不适合用于量产汽车。所以需要对质心侧偏角进行估计。文中提出了一种新型的基于"内含传感器"神经网络左逆(NNLI)的质心侧偏角观测器。通过利用车辆现有的传感器测量的车身状态量,如横摆角速度、纵向加速度、侧向加速度以及电动汽车的驱动电机力矩来估计质心侧偏角。最后文中给出了基于MATLAB/Simulink和Carsim的联合仿真结果。Effective estimation of vehicle states（ e. g.,yaw rate and sideslip angle） is important for vehicle stability control. A novel estimation of sideslip angle using neural network left inversion（ NNLI）is presented for the in-wheel motor drive electric vehicles. Unfortunately the devices are very expensive for measuring sideslip angle directly and are not suitable for ordinary vehicle. And thus it must be estimated. The innovation of the presented algorithm is not only little concerned with reference model parameters identification,but also uses the characteristic of the in-wheel motor drive electric vehicles.Longitudinal acceleration,lateral acceleration,yaw rate,speed,steering angle,the torque of in-wheel motor and angular acceleration can be acquired by ordinary sensors are used as inputs. The co-simulation with MATLAB / Simulink and Car Sim and some simulations are carried out to demonstrate the effectiveness of the proposed estimator.

关 键 词：质心侧偏角 神经网络左逆 内含传感器 电动汽车 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP212.14[自动化与计算机技术—控制科学与工程]