Reliability Allocation and Prediction of Motor Controller Based on DEMATEL‐TOPSIS and Monte‐Carlo Simulation

ABSTRACT The reliability of motor controllers has a significant impact on the overall performance and driving safety of electric vehicles (EVs), but there is little research on the reliability of it. Therefore, a reliability optimization allocation method for motor controllers is proposed by combining cloud models, DEMATEL, and TOPSIS methods. Firstly, the DEMATEL method is used to calculate the degree of mutual influence between the various modules. In order to eliminate the influence of randomness and uncertainty in the expert decision‐making process, a cloud model is introduced to quantify the decision information of decision experts (DEs). During analysis, the TOPSIS method is applied to standardize the calculation of the cloud model matrix. Secondly, using the influence and influenced degree of each module, the reliability allocation coefficient of each module is calculated and the reliability allocation of the motor controller is achieved. Finally, the reliability of the motor controller is predicted by using the Monte‐Carlo simulation method.