摘要
新能源汽车电机驱动过程中由于电机系统本身噪声、传感器运行特性和各个部件接触不良等因素影响下,永磁电机传感器易处于异常工作状态和故障状态。电动汽车电机运行环境的复杂性导致故障诊断难度也相对较大。于是提出新能源汽车永磁电机传感器故障诊断方法。通过分析永磁电机机械运动方式构建新能源汽车永磁电机数学模型,将上述模型与滑模观测器结合,捕捉任意时刻永磁电机传感器故障状态。基于此,提取传感器故障状态下的特征量,并输入支持向量机中,根据支持向量机输出的分类结果实现新能源汽车永磁电机传感器故障诊断。实验结果表明,针对新能源汽车恒速形式和新能源汽车变速形式,研究方法的诊断结构均与实际情况相符。
Due to the influence of motor system noise,sensor operating characteristics and loose contact problems,the permanent magnet motor sensor is easy to be in an abnormal state and fault state,leading to the difficulty of fault diagnosis.Therefore,a method of fault diagnosis for permanent magnet motor sensors of new-energy vehicles was proposed.After analyzing the mechanical movement mode of permanent magnet motors,a mathematical model for new energy vehicles was constructed.Then,the model was combined with a sliding mode observer to capture the fault state of the permanent magnet motor sensor at any time.On this basis,the features of the sensor fault state were extracted and input into the support vector machine.Based on the classification results output by the support vector machine,the fault diagnosis of the permanent magnet motor sensor of the new-energy vehicle was realized.Experimental results show that the diagnosis structure of the proposed method is consistent with the actual situation in the form of constant speed and variable speed.
作者
王良成
汪源
张永辉
WANG Liang-cheng;WANG Yuan;ZHANG Yong-hui(Science and Technology Department,Sanya University,Sanya Hainan 572022,China;School of Information and Communication Engineering Hainan University,Hainan Haikou 570228,China)
出处
《计算机仿真》
2024年第4期136-140,共5页
Computer Simulation
关键词
新能源汽车
永磁电机传感器
滑模观测器
故障特征量
支持向量机
New-energy vehicle
Permanent magnet motor sensor
Sliding mode observer
Fault feature
Support vector machine
