基于状态估计的轮毂电机驱动控制策略研究

Drive Control Strategy of In-wheel Motor Based on State Estimation

摘要:

为克服轮毂电机响应慢，控制精度和抗干扰性差的难题，本文在滑模控制（Sliding mode control, SMC）的基础上，开发基于转速和角度在线状态估计的超螺旋滑模（Super-twisting sliding mode control, STSMC）轮毂电机转速转矩联合控制策略。采用单移线工况，轮毂电机汽车匀速换变道时分别对各轮毂电机进行转速控制，满足阿克曼转向要求，变道后采用正弦过渡方法对各轮毂电机进行转矩控制，电机快速平滑输出期望转矩，车辆直线加速。为防止转速和角度传感器误差或者损坏，轮毂电机控制中采用最大相关熵平方根广义高阶容积卡尔曼算法（Maximum correlation entropy square root generalized high-order cubature Kalman filter, MCSRGHCKF）对转速和转子角度进行无传感器估计，实验测试得到转子角度估计误差为－0.05 rad，转速误差为0.3 r/min，满足电机控制要求。从电机启动到匀速运行阶段采用STSMC算法控制，转速超调量为6.33%，最大输出转矩为0.35 N·m，响应时间为0.22 s，稳态转速脉动为±0.5 r/min，转矩脉动为±0.01 N·m，相比PID和SMC算法，控制效果更佳。在转速切换转矩控制，转矩可按照正弦函数平滑过渡，最大超调仅为2.86%，电机运行平稳。

Abstract:

To overcome the challenges of slow response, poor control accuracy, and poor anti-interference performance of in-wheel motor, a super-twisting sliding mode control (STSMC) in-wheel motor speed and torque joint control strategy was developed based on online state estimation of speed and angle, which was based on the sliding mode control (SMC). Under the single-lane change condition, the speed of each in-wheel motor was controlled when the vehicle changed lanes at a constant speed, meeting the Ackermann steering requirements. After lane changing, the torque of each in-wheel motor was controlled by using a sinusoidal transition method, allowing the motor to quickly and smoothly output the desired torque and accelerate the vehicle in a straight line. To prevent errors or damage of the speed and angle sensors, the maximum correlation entropy square root generalized high-order cubature Kalman filter (MCSRGHCKF) was used for sensorless estimation of the speed and rotor angle. Based on experimental testing, the rotor angle estimation error was -0.05 rad, and speed error was 0.3 r/min, both of which met the motor control requirements. From the start of the motor to the uniform speed operation stage, the STSMC algorithm was used for control, with speed overshoot of 6.33%, maximum output torque of 0.35 N·m, response time of 0.22 s, steady-state speed ripple of ±0.5 r/min, and torque ripple of ±0.01 N·m. Compared with PID and SMC algorithms, the control effect was better. In the speed switching torque control, the torque can smoothly transition according to the sine function, with maximum overshoot of only 2.86%, and the motor ran smoothly.