[1]程帅铭,钟勇,王镛.智能农机动力系统作业工况匹配与换挡优化[J].福建工程学院学报,2023,21(01):55-62.[doi:10.3969/j.issn.1672-4348.2023.01.009]
　CHENG Shuaiming,ZHONG Yong,WANG Yong.Working condition matching and gear shift optimization of intelligent agricultural machinery power system[J].Journal of FuJian University of Technology,2023,21(01):55-62.[doi:10.3969/j.issn.1672-4348.2023.01.009]
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智能农机动力系统作业工况匹配与换挡优化()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第21卷
期数:
2023年01期
页码:
55-62
栏目:
出版日期:
2023-02-25

文章信息/Info

Title:
Working condition matching and gear shift optimization of intelligent agricultural machinery power system
作者:
程帅铭; 钟勇; 王镛
福建省汽车电子与电驱动重点实验室
Author(s):
CHENG Shuaiming;  ZHONG Yong;  WANG Yong
Fujian Key Laboratory of Automotive Electronics and Electric Drive
关键词:
拖拉机动力匹配; 作业工况; 换挡优化; 遗传算法
Keywords:
tractor power matching;  working condition;  gear shift optimization;  genetic algorithm
分类号:
S232.3
DOI:
10.3969/j.issn.1672-4348.2023.01.009
文献标志码:
A
摘要:
利用车辆经济性与动力性软件CRUISE，根据FJ1004 智能无人驾驶拖拉机的动力传动系统搭建了整车模型，通过柴油机的特性曲线分析匹配动力特性，依据工况特征加载拖挂特性，模拟机具消耗。通过工况仿真分析了拖拉机整车的动力性与经济性，与实验数据对比分析，最高车速误差为-0.76%；犁耕油耗和旋耕油耗误差分别为-1.2%和-1.3%。最后通过分析柴油AMT 拖拉机工作特性，结合MIGA 算法对换挡策略进行优化，确定最优功率和燃油经济性的换挡规律，在田间转移工况下油耗优化9.21%；在保证需求动力性的轻负载作业工况下油耗优化1.28%。为后续自适应工况换挡策略提供参考与优化方向。
Abstract:
The vehicle economy and power software CRUISE was used to build a vehicle model according to the power transmission system of FJ1004 intelligent unmanned tractor. The dynamic characteristics were analyzed and matched by the characteristic curve of the diesel engine, and the trailer characteristics were loaded according to the working condition characteristics to simulate the tool consumption. The dynamics and economy of the tractor were analyzed through the simulation of working conditions, and the maximum speed error was -0.76% compared with the experimental data. The fuel consumption errors of ploughing and rotary tillage were -1.2% and -1.3%, respectively. Finally, by analyzing the working characteristics of diesel AMT tractor, combined with MIGA algorithm, the shifting strategy was optimized, and the shifting law of optimal power and fuel economy was determined, and the fuel consumption was optimized by 9.21% under field transfer conditions. The fuel consumption is optimized by 1.28% under light load working conditions that ensure demand dynamics. This research provides model reference and optimization direction for subsequent adaptive working condition shifting strategies.

参考文献/References:

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更新日期/Last Update: 2023-02-25