非线性模型预测直接转矩和ASR/ABS控制的电动汽车纵向稳定性

为了解决电动汽车在加速和制动过程中容易发生滑移和抖动、不能满足稳定性和舒适性的要求,提出了一种基于主从式非线性模型预测(nonlinear model prediction,NMP)直接转矩控制(direct torque controt,DTC)的电动汽车鲁棒控制策略。采用双电机-单控制器主从式驱动模型,基于模糊逻辑控制器,在线确定权重因子的精确值,生成优化电动汽车驱动决策的最优切换状态,保证电机速度的精确跟踪。结合NMP-DTC电机控制方法,设计了一种模糊逻辑ASR/ABS控制器,以角加速度变化和滑移率变化为输入,以补偿转矩为输出变量,根据道路特性的变化提供补偿转矩,保证电动汽车行驶在最佳滑移率范围内,提高行驶的稳定性。基于MATLAB/Simulink进行变负载转矩电机跟踪和汽车纵向稳定性仿真,与参考速度进行对比分析。结果表明,所提出的主从式NMP-DTC的电动汽车ASR/ABS控制,在变负载下不仅电机跟踪轨迹误差降低,而且可保证在加速和制动过程中车辆的纵向稳定性控制。

Study on Longitudinal Stability of Electric Vehicle Based on Nonlinear Model Prediction of Direct Torque and ASR/ABS Control

At present, electric vehicles are prone to slip and jitter during acceleration and braking, which cannot meet the requirements of stability and comfort. In this paper, a robust control of electric vehicle based on master-slave non-linear model predictive control (NMP) direct torque control (DTC) is proposed. Fuzzy logic control technology is used to determine the exact value of weight factor on-line and generate the optimal switching state for optimizing the driving decision of electric vehicle to ensure the accurate tracking of motor. Combining with the motor control method of NMP-DTC, a fuzzy logic ASR/ABS controller is designed, which takes the change of angular acceleration and slip rate as input and the compensation torque as output variable. The compensation torque can be provided according to the change of road characteristics to ensure that the electric vehicle runs in the optimal slip rate range. The simulation of variable load torque motor tracking and vehicle longitudinal stability is carried out based on MATLAB/simulink, and the results are compared with the reference speed. The results show that the ASR/ABS control of the proposed master-slave NMP-DTC not only reduces the tracking error of the motor under variable load, but also ensures the vehicle longitudinal stability control during acceleration and braking.