无人驾驶电动拖拉机底盘配置优化——基于NSGA-Ⅲ算法  

Optimization of Driverless Electric Tractor Chassis Configuration——Based on NSGA-III Algorithm

作　　者：吴正开 王家忠[1,2] 郉雅周 李珊珊 弋景刚[1,2] 赵春明 Wu Zhengkai;Wang Jiazhong;Xing Yazhou;Li Shanshan;Yi Jinggang;Zhao Chunming(College of Mechanical and Electrical Engineering,Agricultural University of Hebei,Baoding 071001,China;Hebei Intelligent Agricultural Equipment Technology Innovation Center,Baoding 071001,China;Tianjin Yidingfeng Power Technology Co.Ltd.,Tianjin 300380,China)

机构地区：[1]河北农业大学机电工程学院,河北保定071001 [2]河北省智慧农业装备技术创新中心,河北保定071001 [3]天津易鼎丰动力科技有限公司,天津300380

出　　处：《农机化研究》2024年第12期228-233,共6页Journal of Agricultural Mechanization Research

基　　金：河北省重点研发项目(21327203D,22327202D)。

摘　　要：针对由传统燃油拖拉机电动改装后的无人驾驶电动拖拉机播种机组附着性能不佳、工作不稳定和耗能大等问题,提出了一种基于NSGA-Ⅲ算法优化底盘配置布局的方案,解决了现有无人驾驶电动拖拉机仅根据经验法加装配重的难题。首先,进行了对无人驾驶电动拖拉机播种机组动力学分析;其次,在动力学分析基础上建立了整机优化的目标函数,以及前后轮动载荷、使用重力和质心位置等约束条件;再次,采用NSGA-Ⅱ和NSGA-Ⅲ算法分别对无人驾驶拖拉机播种机组进行多目标优化。优化结果表明:采用NSGA-Ⅲ算法优化后的配重质量为93.7kg,减少为经验法配重的46.85%、NSGA-Ⅱ算法的86.8%。最后,将北斗的定位信号发送给车载组合导航接收机,获得整机的精准定位信息,利用工控机控制器规划出合理的作业路径,进行田间试验。结果表明:采用NSGA-Ⅲ算法优化后的无人驾驶电动拖拉机组在播种工况下的滑移率符合要求,且经1530s作业后耗电量为0.29kW·h,减少为优化前的85.3%,优化效果良好。Aiming at the problems such as poor adhesion performance,unstable work and high energy consumption of the seeding unit of the unmanned electric tractor after electric modification from the traditional oil-powered tractor,a scheme based on NSGA-III algorithm was proposed to optimize the chassis configuration layout,which solved the problem of the existing unmanned electric tractor loading counterweight only according to the empirical method.Firstly,the dynamics analysis of the seeding unit of the unmanned electric tractor is carried out.Secondly,on the basis of dynamic analysis,the objective function of the machine optimization was established,and the constraint conditions such as front and rear wheel dynamic load,gravity and center of mass position were established.Then,NSGA-II and NSGA-III algorithms were used to optimize the seeding units of unmanned tractors.The optimization results show that the weight weight of the optimized NSGA-III algorithm is 93.7kg,which is reduced to 46.85%of the weight of the empirical method and 86.8%of the NSGA-II algorithm.Finally,the positioning signal of Beidou was sent to the vehicle-mounted integrated navigation receiver to obtain the precise positioning information of the whole machine,and the industrial computer controller was used to plan a reasonable working path for field experiment.Field experiments show that the slip rate of the unmanned electric tractor optimized by NSGA-III algorithm meets the requirements under sowing conditions,and the power consumption is 0.29kW·h after 1530s operation,which is reduced to 85.3%before optimization,and the optimization effect is good.

关 键 词：无人驾驶电动拖拉机 底盘配置 多目标优化 NSGA-Ⅲ 

分 类 号：S219.4[农业科学—农业机械化工程]