Article(id=1312000043926782864, tenantId=1146029695717560320, journalId=1311385739772133495, issueId=1311999647825101743, articleNumber=null, orderNo=null, doi=10.6041/j.issn.1000-1298.2025.12.006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741190400000, receivedDateStr=2025-03-06, revisedDate=1742745600000, revisedDateStr=2025-03-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1790734786254, onlineDateStr=2026-09-30, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790734786254, onlineIssueDateStr=2026-09-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790734786254, creator=13701087609, updateTime=1790734786254, updator=13701087609, issue=Issue{id=1311999647825101743, tenantId=1146029695717560320, journalId=1311385739772133495, year='2025', volume='56', issue='12', pageStart='1', pageEnd='818', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790734691815, creator='13701087609', updateTime=1790738411040, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1312015247465083866, tenantId=1146029695717560320, journalId=1311385739772133495, issueId=1311999647825101743, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1312015247465083867, tenantId=1146029695717560320, journalId=1311385739772133495, issueId=1311999647825101743, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=78, endPage=86, ext={EN=ArticleExt(id=1312000044241355666, articleId=1312000043926782864, tenantId=1146029695717560320, journalId=1311385739772133495, language=EN, title=Design and Experiment of Light and Simple Rice-Wheat Harvesters' Electric Intelligent Chassis, columnId=1311999648647185329, journalTitle=Transactions of the Chinese Society for Agricultural Machinery, columnName=Special Column of Key Technologies for Intelligent Agricultural Power Equipment, runingTitle=null, highlight=null, articleAbstract=

Hilly and mountainous areas are important grain production bases in China. The farmlands in these regions are characterized by small plot sizes, steep slopes, and narrow roads. Traditional fuel-driven chassis have disadvantages such as slow power response, inflexible steering, and low levels of intelligence. To address these issues, an electric intelligent chassis suitable for light and simple rice and wheat harvesters was designed. This machine adopted a distributed design to achieve flexible steering and a wide track design to adapt to rice harvesting operations in hilly and mountainous areas. Motion condition analysis was conducted, and the parameter design of the electric drive system and battery system was completed, solving the problem of slow power response of fuel-powered chassis. The software and hardware design of the motion control system was carried out, enabling remote control operation or autonomous navigation of the chassis. Performance tests and operation parameter optimization tests were conducted. Taking the harvesting speed, threshing drum speed, and cleaning fan speed as test factors, and the breakage rate, impurity rate, and loss rate as evaluation indicators, a Box-Behnken test was designed. The results of the Box-Behnken test were analyzed by variance, and a regression model between the evaluation indicators and the test factors was established. With the goal of minimizing the breakage rate, impurity rate, and loss rate, the optimal solution for the harvesting speed, threshing drum speed, and cleaning fan speed was obtained: the harvester's harvesting speed was 0.8 m/s, the threshing drum speed was 1 000 r/min, and the cleaning fan speed was 2 786.15 r/min. Field tests showed that under this condition, the breakage rate was 0.42%, the impurity rate was 4.05%, and the loss rate was 0.87%. The machine operated smoothly during the operation period, and the operation indicators met the standards for mechanized rice and wheat harvesting. The test results indicated that the designed electric intelligent chassis could meet the operational requirements of the harvester.

, authors=Haolu LIU1, Cheng SHEN1, Guangqiao CAO1, Lianglong HU1, Shangkun LI1, Xiaobing DING2, Lijun ZHAO3, Delong HU4, authorsList=Haolu LIU, Cheng SHEN, Guangqiao CAO, Lianglong HU, Shangkun LI, Xiaobing DING, Lijun ZHAO, Delong HU, authorCompany=null, correspAuthors=Cheng SHEN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1312000052978090996, articleId=1312000043926782864, tenantId=1146029695717560320, journalId=1311385739772133495, language=CN, title=轻简型稻麦收获机电动智能底盘设计与试验, columnId=1311999648798180275, journalTitle=农业机械学报, columnName=智能农业动力装备关键技术专栏, runingTitle=null, highlight=null, articleAbstract=

丘陵山区是我国重要的粮食生产基地,针对该地区农田地块面积小、坡度大和道路窄等特点,本文设计了一种适用于轻简型稻麦收获机作业的电动智能底盘,采用分布式电驱动设计实现灵活转向,采用宽履带设计适应丘陵山区水稻机收作业,开展了运动工况分析,完成了电驱系统与电池系统参数设计,解决了燃油动力底盘响应慢的问题;开展了运动控制系统软硬件设计,实现了底盘遥控操作和自主导航。开展了性能测试试验和作业参数优化试验,以收获速度、脱粒滚筒转速、清选风机转速为试验因素,破碎率、含杂率、损失率为评价指标,设计Box-Behnken试验并进行方差分析,建立了评价指标与试验因素的回归模型,以破碎率、含杂率、损失率最小为寻优目标,对试验因素进行寻优求解,获得最优工作参数组合:收获机收获速度为0.8 m/s、脱粒滚筒转速为1000 r/min、清选风机转速为2 786.15 r/min。田间试验结果表明,最优参数组合下破碎率为0.42%、含杂率为4.05%、损失率为0.87%,作业期间整机运行平稳,作业指标基本符合稻麦机械化收获标准,设计的电动智能底盘能满足收获机作业需求。

, authors=刘浩鲁1, 沈成1, 曹光乔1, 胡良龙1, 李尚昆1, 丁小兵2, 赵立军3, 胡德龙4, authorsList=刘浩鲁, 沈成, 曹光乔, 胡良龙, 李尚昆, 丁小兵, 赵立军, 胡德龙, authorCompany=null, correspAuthors=沈成, authorNote=

刘浩鲁(1993—),男,助理研究员,博士生,主要从事农机装备电动化与智能化研究,E-mail:

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沈成(1989—),男,副研究员,博士,主要从事农机装备电动化与智能化研究,E-mail:
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刘浩鲁(1993—),男,助理研究员,博士生,主要从事农机装备电动化与智能化研究,E-mail:

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刘浩鲁(1993—),男,助理研究员,博士生,主要从事农机装备电动化与智能化研究,E-mail:

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Computers and Electronics in Agriculture, 2025, 230: 109846., articleTitle=A novel robust model predictive controller for improving the steering stability of electric drive mobile platform considering the effect of both yaw motion and rototiller lifting, refAbstract=null), Reference(id=1312000063254134915, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, doi=null, pmid=null, pmcid=null, year=2021, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[31], rfOrder=50, authorNames=唐忠, journalName=履带式水稻联合收割机(理论、模型、设计), refType=null, unstructuredReference=唐忠. 履带式水稻联合收割机(理论、模型、设计)[M]. 北京: 清华大学出版社, 2021., articleTitle=null, refAbstract=null)], funds=[Fund(id=1312000058216775759, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, awardId=52272438, language=CN, fundingSource=国家自然科学基金面上项目(52272438), fundOrder=null, country=null), Fund(id=1312000058275496016, 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figureFileBig=uvXKQqpjYleFADxxgLC2yg==, tableContent=null), ArticleFig(id=1312000056128012339, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=图1, caption=轻简型电动稻麦收获机系统架构示意图, figureFileSmall=5GEuIA2bDp3zXrdQrQS5dg==, figureFileBig=uvXKQqpjYleFADxxgLC2yg==, tableContent=null), ArticleFig(id=1312000056299978804, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=EN, label=Fig. 2, caption=Light and simple electric rice and wheat harvester physical picture, figureFileSmall=QvQ7StM2OcFy6Bn3SCB7kQ==, figureFileBig=XqGMOEcEvFv+Fbl5c7vHmA==, tableContent=null), ArticleFig(id=1312000056362893365, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=图2, caption=轻简型电动稻麦收获机实物图, figureFileSmall=QvQ7StM2OcFy6Bn3SCB7kQ==, figureFileBig=XqGMOEcEvFv+Fbl5c7vHmA==, tableContent=null), ArticleFig(id=1312000056421613622, 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caption=底盘结构示意图

1. 驱动轮 2. 支撑架 3. 张紧轮 4. 导向轮 5. 履带 6. 负重轮

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Main technical indicators of chassis

, figureFileSmall=null, figureFileBig=null, tableContent=
参数履带节距/mm履带节数履带宽度/mm轨距/mm最大爬坡角度/(°)跨沟宽度/mm越障高度/mm
数值794136069025450215
), ArticleFig(id=1312000057315000387, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=表1, caption=

底盘主要技术指标

, figureFileSmall=null, figureFileBig=null, tableContent=
参数履带节距/mm履带节数履带宽度/mm轨距/mm最大爬坡角度/(°)跨沟宽度/mm越障高度/mm
数值794136069025450215
), ArticleFig(id=1312000057386303556, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=EN, label=Tab. 2, caption=

Hardware selection and parameters of motion control system

, figureFileSmall=null, figureFileBig=null, tableContent=
部件名称选型及参数
运动控制器stm32F405
电机驱动器Flipsky FSESC 75100 With Aluminum PCB
工控机研华嵌入式工控机ARK 8500U
自主导航系统上海华测CGI-430型导航系统:IMU-RTK-BDS组合导航
遥控系统云卓-H12:通道数12,频段2.400~2.483 GHz
), ArticleFig(id=1312000057453412421, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=表2, caption=

运动控制系统硬件选型及参数

, figureFileSmall=null, figureFileBig=null, tableContent=
部件名称选型及参数
运动控制器stm32F405
电机驱动器Flipsky FSESC 75100 With Aluminum PCB
工控机研华嵌入式工控机ARK 8500U
自主导航系统上海华测CGI-430型导航系统:IMU-RTK-BDS组合导航
遥控系统云卓-H12:通道数12,频段2.400~2.483 GHz
), ArticleFig(id=1312000057537298502, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=EN, label=Tab. 3, caption=

Field trial information

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序号试验信息
1试验地点:江苏省句容市边城镇大华村
试验时间:2023年12月7日
试验品种:沪软1818水稻
试验面积:0.33 hm2
2试验地点:江苏省扬州市张洪程院士创新试验基地
试验时间:2024年6月1日
试验品种:扬麦33小麦
试验面积:0.14 hm2
3试验地点:重庆市江津区四屏镇旺龙村
试验时间:2024年9月1日
试验品种:神农128水稻
试验面积:0.19 hm2
), ArticleFig(id=1312000057608601672, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=表3, caption=

田间试验信息

, figureFileSmall=null, figureFileBig=null, tableContent=
序号试验信息
1试验地点:江苏省句容市边城镇大华村
试验时间:2023年12月7日
试验品种:沪软1818水稻
试验面积:0.33 hm2
2试验地点:江苏省扬州市张洪程院士创新试验基地
试验时间:2024年6月1日
试验品种:扬麦33小麦
试验面积:0.14 hm2
3试验地点:重庆市江津区四屏镇旺龙村
试验时间:2024年9月1日
试验品种:神农128水稻
试验面积:0.19 hm2
), ArticleFig(id=1312000057675710537, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=EN, label=Tab. 4, caption=

Coding of test factors

, figureFileSmall=null, figureFileBig=null, tableContent=
编码因素
收获速度/(m·s-1)脱粒滚筒转速/(r·min-1)清选风机转速/(r·min-1)
-10.81 0002 500
00.91 2002 800
11.01 4003 100
), ArticleFig(id=1312000057742819402, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=表4, caption=

试验因素编码

, figureFileSmall=null, figureFileBig=null, tableContent=
编码因素
收获速度/(m·s-1)脱粒滚筒转速/(r·min-1)清选风机转速/(r·min-1)
-10.81 0002 500
00.91 2002 800
11.01 4003 100
), ArticleFig(id=1312000057805733963, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=EN, label=Tab. 5, caption=

Experimental design and results

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试验号因素Y1/%Y2/%Y3/%
X1X2X3
10000.424.60.88
21100.484.10.93
30000.434.50.89
410-10.424.90.84
5-1-100.353.90.84
60-110.353.70.96
7-10-10.414.70.83
80000.444.50.89
9-1010.403.70.95
10-1100.473.80.93
110110.493.60.97
121010.413.90.96
130000.434.50.88
140-1-10.364.90.82
1501-10.474.80.92
160000.444.40.87
171-100.374.20.92
), ArticleFig(id=1312000057881231436, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=表5, caption=

试验设计与结果

, figureFileSmall=null, figureFileBig=null, tableContent=
试验号因素Y1/%Y2/%Y3/%
X1X2X3
10000.424.60.88
21100.484.10.93
30000.434.50.89
410-10.424.90.84
5-1-100.353.90.84
60-110.353.70.96
7-10-10.414.70.83
80000.444.50.89
9-1010.403.70.95
10-1100.473.80.93
110110.493.60.97
121010.413.90.96
130000.434.50.88
140-1-10.364.90.82
1501-10.474.80.92
160000.444.40.87
171-100.374.20.92
), ArticleFig(id=1312000057973506125, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=EN, label=Tab. 6, caption=

Regression equation analysis of variance

, figureFileSmall=null, figureFileBig=null, tableContent=
试验指标变异来源平方和自由度均方FP
破碎率模型0.030 590.003 452.21<0.000 1**
X10.000 310.000 34.810.064 4
X20.028 810.028 8443.08<0.000 1**
X30.000 010.000 00.192 30.674 2
X1X20.000 010.000 00.384 60.554 8
X1X30.000 010.000 00.000 01.000 0
X2X30.000 210.000 23.460.105 1
0.000 510.000 57.840.026 5*
0.000 110.000 10.793 50.402 6
0.000 510.000 57.840.026 5*
残差0.000 570.000 1
失拟0.000 230.000 10.833 30.541 3
误差0.000 340.000 1
总和0.031 016
含杂率模型3.1390.347 354.02<0.000 1**
X10.12510.12519.440.003 1**
X20.0210.023.110.121 1
X32.4212.42376.44<0.000 1**
X1X201001.000 0
X1X301001.000 0
X2X301001.000 0
0.213 210.213 233.160.000 7**
0.318 410.318 449.530.000 2**
0.002 610.002 60.409 40.542 7
残差0.04570.006 4
失拟0.02530.008 31.670.309 9
误差0.0240.005
总和3.1716
损失率模型0.036 590.004 126.920.000 1**
X10.001 310.001 38.290.023 7*
X20.005 510.005 536.580.000 5**
X30.023 110.023 1153.35<0.000 1**
X1X20.001 610.001 610.620.013 9*
X1X301001.000 0
X2X30.00210.00213.440.008 0**
2.63×10-712.63×10-70.001 70.967 8
0.002 210.002 214.460.006 7**
0.000 710.000 74.540.070 6
残差0.001 170.000 2
失拟0.000 830.000 33.690.119 7
误差0.000 340.000 1
总和0.037 616
), ArticleFig(id=1312000058099335246, tenantId=1146029695717560320, journalId=1311385739772133495, articleId=1312000043926782864, language=CN, label=表6, caption=

回归方程方差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
试验指标变异来源平方和自由度均方FP
破碎率模型0.030 590.003 452.21<0.000 1**
X10.000 310.000 34.810.064 4
X20.028 810.028 8443.08<0.000 1**
X30.000 010.000 00.192 30.674 2
X1X20.000 010.000 00.384 60.554 8
X1X30.000 010.000 00.000 01.000 0
X2X30.000 210.000 23.460.105 1
0.000 510.000 57.840.026 5*
0.000 110.000 10.793 50.402 6
0.000 510.000 57.840.026 5*
残差0.000 570.000 1
失拟0.000 230.000 10.833 30.541 3
误差0.000 340.000 1
总和0.031 016
含杂率模型3.1390.347 354.02<0.000 1**
X10.12510.12519.440.003 1**
X20.0210.023.110.121 1
X32.4212.42376.44<0.000 1**
X1X201001.000 0
X1X301001.000 0
X2X301001.000 0
0.213 210.213 233.160.000 7**
0.318 410.318 449.530.000 2**
0.002 610.002 60.409 40.542 7
残差0.04570.006 4
失拟0.02530.008 31.670.309 9
误差0.0240.005
总和3.1716
损失率模型0.036 590.004 126.920.000 1**
X10.001 310.001 38.290.023 7*
X20.005 510.005 536.580.000 5**
X30.023 110.023 1153.35<0.000 1**
X1X20.001 610.001 610.620.013 9*
X1X301001.000 0
X2X30.00210.00213.440.008 0**
2.63×10-712.63×10-70.001 70.967 8
0.002 210.002 214.460.006 7**
0.000 710.000 74.540.070 6
残差0.001 170.000 2
失拟0.000 830.000 33.690.119 7
误差0.000 340.000 1
总和0.037 616
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轻简型稻麦收获机电动智能底盘设计与试验
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刘浩鲁 1 , 沈成 1 , 曹光乔 1 , 胡良龙 1 , 李尚昆 1 , 丁小兵 2 , 赵立军 3 , 胡德龙 4
农业机械学报 | 智能农业动力装备关键技术专栏 2025,56(12): 78-86
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农业机械学报 |智能农业动力装备关键技术专栏 2025 , 56 (12) : 78 -86
轻简型稻麦收获机电动智能底盘设计与试验
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刘浩鲁(1993—),男,助理研究员,博士生,主要从事农机装备电动化与智能化研究,E-mail:

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刘浩鲁1 , 沈成1 , 曹光乔1, 胡良龙1, 李尚昆1, 丁小兵2, 赵立军3, 胡德龙4
作者信息
  • 1.农业农村部南京农业机械化研究所,南京 210014
  • 2.重庆鑫源农机股份有限公司,重庆 401329
  • 3.重庆文理学院智能制造工程学院,重庆 402160
  • 4.江苏农林职业技术学院农学园艺学院,句容 212400
通讯作者:
沈成(1989—),男,副研究员,博士,主要从事农机装备电动化与智能化研究,E-mail:
作者简介:

刘浩鲁(1993—),男,助理研究员,博士生,主要从事农机装备电动化与智能化研究,E-mail:

Design and Experiment of Light and Simple Rice-Wheat Harvesters' Electric Intelligent Chassis
Haolu LIU1 , Cheng SHEN1 , Guangqiao CAO1, Lianglong HU1, Shangkun LI1, Xiaobing DING2, Lijun ZHAO3, Delong HU4
Affiliations
  • 1.Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China
  • 2.Chongqing Shineray Agricultural Machinery Co., Ltd., Chongqing 401329, China
  • 3.College of Intelligent and Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China
  • 4.Department of Agronomy and Horticulture, Jiangsu Vocational College of Agriculture and Forestry, Jurong 212400, China
出版时间: 2025-12-25 doi: 10.6041/j.issn.1000-1298.2025.12.006
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丘陵山区是我国重要的粮食生产基地,针对该地区农田地块面积小、坡度大和道路窄等特点,本文设计了一种适用于轻简型稻麦收获机作业的电动智能底盘,采用分布式电驱动设计实现灵活转向,采用宽履带设计适应丘陵山区水稻机收作业,开展了运动工况分析,完成了电驱系统与电池系统参数设计,解决了燃油动力底盘响应慢的问题;开展了运动控制系统软硬件设计,实现了底盘遥控操作和自主导航。开展了性能测试试验和作业参数优化试验,以收获速度、脱粒滚筒转速、清选风机转速为试验因素,破碎率、含杂率、损失率为评价指标,设计Box-Behnken试验并进行方差分析,建立了评价指标与试验因素的回归模型,以破碎率、含杂率、损失率最小为寻优目标,对试验因素进行寻优求解,获得最优工作参数组合:收获机收获速度为0.8 m/s、脱粒滚筒转速为1000 r/min、清选风机转速为2 786.15 r/min。田间试验结果表明,最优参数组合下破碎率为0.42%、含杂率为4.05%、损失率为0.87%,作业期间整机运行平稳,作业指标基本符合稻麦机械化收获标准,设计的电动智能底盘能满足收获机作业需求。

稻麦收获机  /  电动智能底盘  /  分布式电驱动  /  油电混动  /  丘陵山区

Hilly and mountainous areas are important grain production bases in China. The farmlands in these regions are characterized by small plot sizes, steep slopes, and narrow roads. Traditional fuel-driven chassis have disadvantages such as slow power response, inflexible steering, and low levels of intelligence. To address these issues, an electric intelligent chassis suitable for light and simple rice and wheat harvesters was designed. This machine adopted a distributed design to achieve flexible steering and a wide track design to adapt to rice harvesting operations in hilly and mountainous areas. Motion condition analysis was conducted, and the parameter design of the electric drive system and battery system was completed, solving the problem of slow power response of fuel-powered chassis. The software and hardware design of the motion control system was carried out, enabling remote control operation or autonomous navigation of the chassis. Performance tests and operation parameter optimization tests were conducted. Taking the harvesting speed, threshing drum speed, and cleaning fan speed as test factors, and the breakage rate, impurity rate, and loss rate as evaluation indicators, a Box-Behnken test was designed. The results of the Box-Behnken test were analyzed by variance, and a regression model between the evaluation indicators and the test factors was established. With the goal of minimizing the breakage rate, impurity rate, and loss rate, the optimal solution for the harvesting speed, threshing drum speed, and cleaning fan speed was obtained: the harvester's harvesting speed was 0.8 m/s, the threshing drum speed was 1 000 r/min, and the cleaning fan speed was 2 786.15 r/min. Field tests showed that under this condition, the breakage rate was 0.42%, the impurity rate was 4.05%, and the loss rate was 0.87%. The machine operated smoothly during the operation period, and the operation indicators met the standards for mechanized rice and wheat harvesting. The test results indicated that the designed electric intelligent chassis could meet the operational requirements of the harvester.

rice-wheat harvester  /  electric intelligent chassis  /  distributed electric drive  /  hybrid oil-electric  /  hilly and mountainous areas
刘浩鲁, 沈成, 曹光乔, 胡良龙, 李尚昆, 丁小兵, 赵立军, 胡德龙. 轻简型稻麦收获机电动智能底盘设计与试验. 农业机械学报, 2025 , 56 (12) : 78 -86 . DOI: 10.6041/j.issn.1000-1298.2025.12.006
Haolu LIU, Cheng SHEN, Guangqiao CAO, Lianglong HU, Shangkun LI, Xiaobing DING, Lijun ZHAO, Delong HU. Design and Experiment of Light and Simple Rice-Wheat Harvesters' Electric Intelligent Chassis[J]. Transactions of the Chinese Society for Agricultural Machinery, 2025 , 56 (12) : 78 -86 . DOI: 10.6041/j.issn.1000-1298.2025.12.006
丘陵山区占中国国土面积的50%以上,是重要的粮食生产区域[1]。然而,丘陵山区受地理因素制约,农业生产条件较差,难以开展大规模种植和机械化作业[2-3]。中国丘陵山区农业机械化仍处于较低水平[4-5],严重制约了中国在城市化和人口老龄化背景下的农业发展和粮食安全[6-7]。因此,丘陵山区农业机械化刻不容缓[8]。
中国丘陵山区耕地面积普遍较小[9],较大耕地面积为0.20~0.33 hm2,较小耕地面积仅为十几平方米。土地破碎化给农作物机械化收获带来了许多困难。曹光乔等[10]的研究表明,山区零碎耕地主要影响收获机转向效率,因此有必要优化和提高收获机转向性能以适应山区零散的耕地。XIE等[11]设计了一种适用于狭窄地块的拱腰式底盘,具有较强地面适应性与良好转向机动性。HU等[12]开发了一种基于负载敏感原理和比例-积分-微分(PID)控制算法的多模式液压转向系统,以提高农业机械在丘陵山区的转向灵活性。吕小荣等[13]为解决土地破碎化带来的问题,设计了一种小型多功能底盘液压系统,实现无级变速和枢轴转向。针对小型谷物收获机在丘陵作业时倾斜角度大、通过性差等问题,雷小龙等[14]设计了一种谷物联合收获机底盘自动升降液压系统。上述研究所涉及的农机装备主要采用燃油动力驱动液压系统,缺少电动农机研究。电动农机具有动力响应速度快、传动简单、转向灵活的特点[15-16],十分适合在中小地块使用[17],也更易于实现智能控制[18-19]。陈凤等[20]设计了一种适用于设施园艺的四轮轮毂电机驱动移动平台,并提出了一种自适应防滑控制策略。崔志超等[21]设计了一种用于温室的电动作业平台,能够满足温室内果蔬管理、采摘及搬运需求。王宝超等[22]设计了一台适用于温室的增程式电动履带拖拉机。王元杰等[23]提出了一种电动机无级调速与变速箱调速相结合的调速方法,以实现良好的转速-转矩特性。赵立军等[24]设计了一种山地电动履带底盘,并开展了底盘爬坡、越障等性能仿真测试。王家博等[25]提出了改进抗差自适应扩展卡尔曼滤波法,用于履带式电动微耕机自主导航。LUO等[26]提出了一种基于学习的后轮独立驱动电动拖拉机翻耕过程偏航稳定性的双层控制方法。李贤哲等[27]提出了一种基于多岛遗传算法的分布式驱动系统参数优化设计与验证方法。针对温室电动拖拉机旋耕作业响应性差、耕深不稳定和功率突变等问题,杨杭旭等[28]提出了基于时间序列分析的角度预测方法,实现了前馈PID控制优化。LUO等[29]提出了一种基于地形参数识别的电动拖拉机驱动节能控制策略。CHEN等[30]设计了一种电驱移动平台,并提出了旋耕机横向耦合动力学模型,提高了旋耕机升降作业过程中的偏航稳定性。
综上,电动农机研究应用场景主要集中在设施园艺环境,机型主要为运载机械和动力机械,受电池续航等问题限制,缺少应用于丘陵山区主粮收获作业的相关研究。电动底盘动力响应速度快,特别适合丘陵山区等狭小地块作业,因此,本研究设计一种适用于丘陵山区稻麦收获机作业的电动智能底盘,将其搭载至4LZ-1.0LC型稻麦收获机。分析常见工况,对电动底盘动力电池、电驱动部件和电动底盘等关键部件进行参数设计,进行运动控制器软硬件设计,通过试验验证该收获机作业性能,并利用响应面法获得最佳运行参数。
采用油电混合动力形式,作业部件由内燃机提供动力,行走底盘采取分布式电驱动,系统架构如图1所示,主要包括作业部件、内燃机、动力电池、电控单元、电驱部件和履带底盘。
整机实物如图2所示,其中外形尺寸为3.1 m×1.5 m×1.7 m。割台是收获机主要作业部件,割幅为1.1 m,喂入量为1 kg/s。动力电池位于履带底盘与脱粒清选部件之间,处于整机中后部,防止转场过程中因碰撞引起安全事故。内燃机位于整机中部,保持配重平衡,防止重心偏移导致歪斜、倾覆等问题,增强机具通过性。动力电池是行走底盘的能量源,为履带两侧的驱动电机供电,驱动电机通过减速箱与底盘驱动轮连接,驱动底盘行驶;柴油发动机为作业机构提供动力,通过链传动、带传动驱动收获输送部件和脱粒清选部件工作,当动力电池电量较低时,作为增程器为动力电池补充电量;电控单元作为运动控制器,接入遥控信号或智能作业系统信号,控制驱动部件动作。
工况主要包括爬坡越障、收获作业和转场3种,爬坡越障速度为0.5 m/s,收获作业速度为0.9 m/s,转场速度为1.3 m/s,相应于驱动轮爬坡转速为54 r/min,收获作业转速为94 r/min,转场转速为125 r/min。参照文献[31],开展设计研究。
转场工况时,收获机主要受摩擦力影响,忽略空气阻力和加速阻力,驱动电机提供的功率应大于克服摩擦力所做的功率,故转场工况所需功率为
其中
式中
      P1——转场所需总功率,kW
      v1——转场时速度,m/s
      Ff1——转场过程所受摩擦力,N
      μh——摩擦因数,取0.3~0.5
      ηm——电机效率,取0.85
      ηh——整机效率,取0.9
      mh——整机质量,取800 kg
      g——重力加速度,m/s2
由式(1)、(2)可得转场时所需功率为4.08~6.8 kW。
转场工况启动时,驱动电机提供的功率应大于克服摩擦力和提供加速度所做的功率,启动所需功率为
式中
      ——转场时瞬时速度,m/s
      a——加速度,取1 m/s2
由式(3)可得转场启动时所需功率为5.13~7.85 kW。
爬坡工况时,主要进行行走作业,收获机速度较低,主要受地面摩擦力和重力沿斜坡方向分力影响,忽略空气阻力和加速阻力,驱动电机提供的功率应大于克服摩擦力所做的功率,故爬坡工况所需功率为
其中
式中
      P2——爬坡所需总功率,kW
      v2——爬坡时速度,m/s
      Ff2——爬坡过程中所受阻力,N
      θ——爬坡角度,取极端工况25°
由式(4)、(5)可得爬坡时所需功率为3.63~4.58 kW。
爬坡工况启动时,驱动电机提供的功率应大于克服摩擦力、重力沿斜坡方向分力和提供加速度所做的功率,启动所需功率为
式中
      ——爬坡时瞬时速度,m/s
由式(6)可得爬坡启动时所需功率为4.68~5.63 kW。
收获工况时,收获机主要受地面摩擦力影响,忽略空气阻力和加速阻力,驱动电机提供的功率应大于克服摩擦力所做的功率,故收获工况所需功率为
其中
式中
      P3——收获所需总功率,kW
      v3——收获时速度,m/s
      Ff3——收获过程中所受阻力,N
由式(7)、(8)可得收获时所需功率为2.83~4.71 kW。
收获工况启动时,驱动电机提供的功率应大于克服摩擦力和提供加速度所做的功率,启动所需功率为
式中
      ——收获时瞬时速度,m/s
由式(9)可得收获启动时所需功率为3.88~5.76 kW。
稻麦收获机作业工况复杂,底盘行驶时土壤粘重,地面平整度较差,负载多变,瞬时扭矩输出要求高。无刷直流电机具有过载能力强、起动转矩大、效率高和功率密度大的优点,适宜电动农机作业特点和环境,选择无刷直流电机作为主驱动电机。通过分析3种工况下受力,电机额定功率应满足最大功率工况所需功率的1.1~1.6倍,电机额定功率PN与峰值功率PNmax为
由式(10)、(11),驱动电机选用2台72 V、4 kW无刷直流电机。
为适应电动农机行走作业低速高扭矩的动力输出特点,需使用减速机实现降速增扭,电动机最大输出转矩为
式中
      Tmax——电机最大输出转矩,N·m
      n——电机转速,r/min
考虑机械结构设计,由式(12),匹配传动比为40的斜齿准双曲面齿轮减速器,电驱动部件如图3所示。
考虑田间复杂环境,为保障续航和安全性,选择三元锂电池作为动力电池。根据电机母线工作电压和作业最大功率确定动力电池容量,计算式为
式中
      Cb——动力电池容量,A·h
      Um——电机母线电压,V
      hk——锂电池放电深度,取0.8
      ηmC——电机控制器和电动机效率乘积,取0.8
由式(13),电池部分选用72 V、200 A·h规格三元锂电池。BMS电源管理系统能实现过流保护、过压保护、短路保护、平衡保护、过冲保护、过放保护、过热保护和充电保护。
丘陵山区地形复杂,坡高沟深,土壤黏重,地块破碎,对底盘通过性和转向灵活性要求较高,因此选择宽履带结构和分布式电驱动设计,底盘结构示意图如图4所示。整体结构由1对驱动轮、1对导向轮、1对张紧轮、5对负重轮、支撑架和橡胶履带构成,两侧驱动轮分别由两侧的驱动电机联结减速机驱动。
履带节距tp为
履带宽度b与履带接地长度L配合可提高底盘牵引附着性能。窄长履带滚动阻力小,牵引附着性能好,但转向阻力矩较大,为适应丘陵山区水稻机收作业的土壤质地条件,减少接地比压,提高转向灵活性,采取宽履带设计,b/L取0.3。底盘主要技术指标如表1所示。
履带动力底盘主要由履带、驱动轮、导向轮、托带轮和支重轮构成。整机行驶和转向由电机驱动履带底盘驱动轮实现,两侧驱动轮分别由两侧的电机独立驱动,通过控制两侧电机转速实现差速转向,运动控制系统硬件选型及参数如表2所示。
在底盘运动控制中,自主导航系统或人工遥控向运动控制器输入加速度信息a和转向角度信息δ,运动控制器调整两侧电机转速信号n并输出转矩信号T,实现整机运动控制,底盘运动控制结构框图如图5所示。
人工遥控操作时,通过2个遥控手杆分别控制速度和转角信号,速度解析函数为
式中
      vmax——整机最大行驶速度,m/s
      α——速度遥控手杆行程
      α0——速度遥控手杆最小行程
      αmax——速度遥控手杆最大行程
转向信号解析函数为
式中
      β——转向角度手杆行程
      β0——转向角度遥控手杆最小行程
      βmax——转向角度遥控手杆最大行程
构建阿克曼转向模型,实现收获机电子差速转向,如图6所示。
当收获机绕点O运动时,有
式中
      vL——左侧履带驱动轮线速度,m/s
      vR——右侧履带驱动轮线速度,m/s
      ω——转向角速度,rad/s
      vm——转向速度,m/s
      H——两侧履带间轨距,m
      Rm——中心运动半径,m
根据式(17),给出差速模型逆运动学数学推导,得到
式中
      C——曲率,用于大曲率路径的前馈补偿
当左右履带以大小相等、方向相反的速度运动时,可以实现收获机原地转向,轨迹如图7所示。
为验证轻简型电动稻麦收获机行走、作业各项性能,分别在江苏省句容市、江苏省扬州市和重庆市江津区开展了水稻/小麦收获试验共计3次,田间试验信息如表3所示。
按照GB/T 8097—2008《收割机械联合收获机试验方法》并参考GB/T 2828.1—2012《计数抽样检测程序》进行。每次试验划定5份×25 m×1 m等份试验区,试验时收获机以前进速度0.9 m/s、割幅1 m满幅作业。接取试验行程内出粮口排出物不少于1 000 g的小样,并按照五点取样法测定作业后试验区每平方米掉落稻麦籽粒,使用清洁样品袋装袋编号,并测定作业机破碎率、含杂率和损失率。多次作业完成后使用精度0.001 g电子秤测量,结果取平均值。
破碎率p、含杂率z和损失率s计算公式为
式中
      m——总质量
      mp——破碎质量
      mz——含杂质量
      ms——损失质量
根据前期预试验结果确定作业参数范围,以收获速度(v)、脱粒滚筒转速(n1)和清选风机转速(n2)为自变量,以破碎率(Y1)、含杂率(Y2)和损失率(Y3)为响应值,依照Box-Behnken试验设计原理,采用三因素三水平响应面分析方法,分别建立各因素与脱净率、总损失率和籽粒含杂率间的数学模型,并对各因素及其交互作用进行分析,各试验因素编码如表4所示。分别实施17组响应面分析试验,试验结果如表5所示,其中X1、X2、X3为试验因素编码值。应用Design-Expert 12.0软件进行数据处理分析。
根据表5试验结果,对破碎率(Y1)、含杂率(Y2)和损失率(Y3)进行回归模型方差分析,结果如表6所示,剔除不显著项后Y1、Y2和Y3二次回归模型为
由表6可知,破碎率、含杂率和损失率二次回归模型P<0.000 1,表明回归模型极显著,失拟项P>0.05,失拟不显著,说明模型所拟合的二次回归方程与实际相符合。交互因素对损失率的影响如图8所示。
根据二次回归模型结果与响应面分析,为进一步提升轻简型电动稻麦收获机作业性能,以破碎率(Y1)、含杂率(Y2)和损失率(Y3)最小为优化指标,在各试验因素水平约束条件下,建立性能指标全因子二次回归方程,确定目标优化值与最优工作参数模型。目标函数与约束条件为
最终得到优化试验指标破碎率为0.34%、含杂率为3.95%、损失率为0.84%;最优工作参数为收获速度0.8 m/s、脱粒滚筒转速1 000 r/min、清选风机转速2 786.15 r/min。
按照最优工作参数开展田间试验验证,作业期间整机运行平稳,破损率为0.42%,含杂率为4.05%,损失率为0.87%。
按照柴油7元/L、农业用电0.4元/度计算,传统燃油型稻麦收获机燃油消耗23.55 L/hm2,作业成本为165元/hm2,采用电动底盘后,燃油消耗为14.1 L/hm2,耗电量29.25 kW·h/hm2,作业成本110.4元/hm2,较燃油型收获机,稻麦收获机节约作业成本约1/3。
(1)面向丘陵山区地形环境下稻麦收获作业需求,基于4LZ-1.0LC型稻麦收获机,改进设计了一款分布式电动智能底盘,开展了典型工况条件下的动力学分析,完成电池和电驱系统选型设计。行走驱动系统采用了分布式电驱动履带底盘,采用无刷直流电机+减速机组合实现低速大扭矩动力输出。为提升收获机运动控制精度,满足多样化控制需求,提供了自主导航系统和人工遥控操作2种运动控制模式,完成运动控制系统软硬件设计。
(2)开展了作业性能优化试验,以收获速度、清选风机转速、脱粒滚筒转速为试验因素,破碎率、含杂率和损失率为评价指标,探究试验因素对作业质量的影响规律,结果表明当收获机收获速度为0.8 m/s、脱粒滚筒转速为1 000 r/min、清选风机转速为2786.15 r/min时,破碎率为0.42%、含杂率为4.05%、损失率为0.87%,基本符合稻麦机械化收获要求。
  • 国家自然科学基金面上项目(52272438)
  • 国家重点研发计划项目(2023YFD2000301; 2023YFD2000303)
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2025年第56卷第12期
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doi: 10.6041/j.issn.1000-1298.2025.12.006
  • 接收时间:2025-03-06
  • 首发时间:2026-09-30
  • 出版时间:2025-12-25
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  • 收稿日期:2025-03-06
  • 修回日期:2025-03-24
基金
国家自然科学基金面上项目(52272438)
国家重点研发计划项目(2023YFD2000301; 2023YFD2000303)
作者信息
    1.农业农村部南京农业机械化研究所,南京 210014
    2.重庆鑫源农机股份有限公司,重庆 401329
    3.重庆文理学院智能制造工程学院,重庆 402160
    4.江苏农林职业技术学院农学园艺学院,句容 212400

通讯作者:

沈成(1989—),男,副研究员,博士,主要从事农机装备电动化与智能化研究,E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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