文章提出一种基于电机转速（Rotational Speed,REV）的低压直流电机温度估算方法。该方法以电机参数模型库为基础,结合电机产热散热动态特性及驱动电流与转速的非线性映射关系,构建温度预测算法框架。通过搭建实验台架采集实测数据,采用误差反向修正策略迭代优化算法,最终使估算值与实际温度最大偏差≤3℃。该方法可避免传统模型对复杂传感器的依赖,节省整车传感器成本,在电机热保护及故障预警领域具有工程应用价值。

This paper proposes a temperature estimation method for low-voltage DC motors based on Rotational Speed (REV). This method is based on the motor parameter model library and combines the dynamic characteristics of motor heat generation and dissipation as well as the nonlinear mapping relationship between driving current and rotational speed to construct a temperature prediction algorithm framework. By setting up an experimental bench to collect the measured data and adopting the error reverse correction strategy to iteratively optimize the algorithm, the maximum deviation between the estimated value and the actual temperature was ultimately made ≤3℃. This method can avoid the reliance of traditional models on complex sensors, save the cost of vehicle sensors, and has engineering application value in the field of motor thermal protection and fault early warning.