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.