摘要
针对传感器在实际应用中存在的温度漂移、非线性误差和环境干扰等问题,研究了基于最小二乘法和卡尔曼滤波的自适应补偿算法。通过建立温度-误差模型和多源数据融合技术,实现传感器信号的实时校正。该补偿方法在电机转速加速度变化较大的工况下依然保持稳定,显著提升了传感器测量精度。通过建立分程计量方法和多源数据融合技术,实现传感器信号的实时校正。该补偿方法能有效应对电机转速加速度变化较大等复杂工况,显著提升了传感器测量精度,尤其改善了电流传感器在低电量状态下的测量准确性。
To address issues such as temperature drift,nonlinear errors,and environmental interference in practical sensor applications,an adaptive compensation algorithm based on least squares method and Kalman filtering is studied.Through establishing a temperature-error model and multi-source data fusion technology,real-time calibration of sensor signals is achieved.The compensation method maintained stability even under conditions with large variations in motor speed and acceleration,significantly improving sensor measurement accuracy.Through the establishment of a segmented measurement method and multi-source data fusion technology,real-time correction of sensor signals is achieved.This compensation method effectively handled complex operating conditions such as large variations in motor speed and acceleration,significantly improving sensor measurement accuracy,particularly enhancing the measurement precision of current sensors under low-power conditions.
作者
辛欣
马天舒
叶熠琳
XIN Xin;MA Tianshu;YE Yilin(Tianjin Center for Patent Examination Cooperation of the Patent Office of the State Intellectual Property Office,Tianjin 300304,China;China Automotive Information Technology(Tianjin)Co.,Ltd.,Tianjin 300399,China;Zhejiang Kuaishou Information Technology Co.,Ltd.,Hangzhou 311100,China)
出处
《电子工业专用设备》
2025年第1期68-72,共5页
Equipment for Electronic Products Manufacturing
关键词
汽车电子系统
传感器误差
补偿算法
数据融合
精度提升
Automotive electronic systems
Sensor error
Compensation algorithm
Data fusion
Accuracy improvement
