主办：陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊：1976年
汽车实用技术

汽车实用技术 ›› 2025, Vol. 50 ›› Issue (6): 16-21.DOI: 10.16638/j.cnki.1671-7988.2025.006.003

• 新能源汽车 • 上一篇    

基于 AVL-Cruise 的增程式电动拖拉机传动 系统匹配与优化

陈梦醒，姚艳萍*，杨召淞，邢哲浩，周利东   

  1. 太原科技大学 机械工程学院
  • 发布日期:2025-03-26
  • 通讯作者: 姚艳萍
  • 作者简介:陈梦醒（1998－），男，硕士研究生，研究方向为新能源农机传动控制 通信作者：姚艳萍（1976－），女，博士，教授，研究方向为连续输送技术，E-mail:919405128@qq.com
  • 基金资助:
    山西省基础研究计划项目（202203021211202）；山西省研究生教育改革研究课题（2023JG142）；山西省高 等学校科技成果转化培育项目（2020CG043）

Matching and Optimization of the Transmission System of an Extended Range Electric Tractor Based on AVL-Cruise

CHEN Mengxing, YAO Yanping* , YANG Zhaosong, XING Zhehao, ZHOU Lidong   

  1. School of Mechanical Engineering, Taiyuan University of Science and Technology
  • Published:2025-03-26
  • Contact: YAO Yanping

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摘要： 为了解决拖拉机传动系统的匹配与优化问题，首先根据拖拉机的整车设计要求，对拖 拉机的电机、电池、增程器、变速箱等参数进行了匹配；然后基于 AVL-Cruise 建立了整车模 型，并建立了循环工况、续航里程、最大爬坡度等仿真任务；最后在保证满足拖拉机动力性 的情况下，利用遗传算法优化变速箱传动比，提高其经济性。结果表明，拖拉机在犁耕和运 输作业工况下能耗均有所下降，经济性分别提高了 2.6%和 8.4%，犁耕和运输作业工况下的纯 电续航时间均有所上升，经济性分别提高了 4.2%和 4.6%，且优化后犁耕作业工况下电机 MAP 图中的工作点相较于优化前工作在更高的效率区间。

关键词: 增程式电动拖拉机；传动系统；遗传算法

Abstract: In order to solve the matching and optimization problem of the tractor transmission system, firstly the tractor motor, battery, range extender, gearbox and other parameters are matched according to the vehicle design requirements of the tractor. Then the vehicle model is established based on AVL-Cruise, and simulation tasks such as cycle working condition, driving range and maximum gradient are established. Finally, under the condition of satisfying the power performance of the tractor, the genetic algorithm is used to optimize the transmission ratio and improve its economy. The results show that the energy consumption of the tractor decreases and the economy increases by 2.6% and 8.4%, respectively, and the pure electric endurance increases by 4.2% and 4.6%, respectively, under the ploughing and transporting operating conditions. Moreover, the working points in the motor MAP graph under optimized ploughing working conditions are in a higher efficiency range than those before optimization.

Key words: extended range electric tractor; transmission system; genetic algorithm