Multi-Objective Optimization and Test of a Tractor Drive Motor

Author:

Liu Mengnan,Li Yanying,Zhao SixiaORCID,Han Bing,Lei Shenghui,Xu Liyou

Abstract

The design objectives of the structural parameters of the tractor drive motor are diverse, and the constraints are complex. It is difficult to optimize the overall performance of the unit by using the empirical method and single-objective optimization method. This paper proposes a multi-objective optimization method for tractor drive motors based on an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II). Constraints are formulated according to the inherent characteristics of the motor itself and the characteristics of the tractor’s working conditions. The objective function was established with the heat loss of the drive motor and the total efficiency of the drive system. Based on the designed solution process of NSGA-II algorithm, an example optimization was carried out, and the tractor electromechanical drive system was carried out with the single-objective optimization results of the optimal energy use efficiency of the drive motor and the optimal mechanical transmission efficiency of the transmission system as the control group. The test results show that compared with the control group, the proposed multi-objective optimization method can make the overall tractor system efficiency the highest, and the maximum and rated values of the total efficiency ηq of the drive system of the multi-objective optimization design scheme. Compared with the optimal design scheme with ηme as a single objective, it was increased by 2% and 1.4%, respectively, and compared with the optimal design scheme with ηtr as a single objective, it is improved by 26.5% and 73.6%, respectively. It can provide an effective calculation method for the motor design problem in the subsequent development of the tractor electromechanical drive system.

Funder

The project is supported by National Key Research and Development Program of China “Development of intelligent electric tractor

Publisher

MDPI AG

Subject

Automotive Engineering

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