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To build a more accurate motor efficiency model with a strong generalization ability in order to evaluate and improve the efficiency characteristics of electric vehicles, this paper researches motor efficiency modeling based on the bench tests of two motor efficiencies with differently rated powers. This paper compares and analyzes three motor efficiency modeling methods and finds that, when the measured values in motor efficiency tests are insufficient, the bilinear interpolation method and radial basis kernel function neural networks have poor generalization abilities in full working conditions, and the precision of polynomial regression is limited. On this basis, this paper proposes a new modeling method combining correlation analysis, polynomial regression, and an improved simulated annealing (I-SA) algorithm. Using the mean and the standard deviation of the mean absolute percentage error of the 5-fold Cross Validation (CV) of 100 random tests as the evaluation indices of the precision of the motor efficiency model, and based on the motor efficiency models with verified precision, this paper makes a comparative analysis on the full vehicle efficiency of electric tractors of three types of drive in five working conditions. Research results show that the proposed novel method has a high modeling precision of motor efficiency; tractors with a dual motor coupling drive system have optimal economic performance.

agriculture

A Novel 10-Parameter Motor Efficiency Model Based on I-SA and Its Comparative Application of Energy Utilization Efficiency in Different Driving Modes for Electric Tractor