Abstract
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.
Highlights
Electric vehicles use a motor as the core power source [1,2] and electric energy as the driving energy [3]
In order to solve the above problems, combined with the bench test data of tractor motors, this paper aims to put forward a model to correctly describe the efficiency characteristics of motors by comparing four different modeling methods and by exploring the influence of other data transformation forms of physical quantities on the efficiency characteristics of motors
According to the problems above, this paper proposes a modeling method of motor efficiency, combining the correlation coefficient and polynomial regression (PR)
Summary
Electric vehicles use a motor as the core power source [1,2] and electric energy as the driving energy [3]. This is convenient for recycling energy, but it can achieve low emissions or even zero emissions [4–6]. Compared with internal combustion engine vehicles, electric vehicles have the advantages of low noise and low maintenance costs [7] These characteristics provide great help for the sustainability of the environment and its ecology. In the research field of agricultural machinery, agricultural machinery faces complicated working conditions Agricultural machinery such as tractors generally needs to meet the requirements of operation, including ploughing, rotary tillage, transportation, and normal road driving [16,17]. The research and application of electric tractors can help to overcome the problems of the traditional tractor, such as complicated variable transmission structures, frequent operation of the driver, limited energy utilization efficiency, etc. [18–20]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
