双电机耦合驱动电动拖拉机转矩分配策略设计  

Design of Torque Distribution Strategy for Dual-motor Variable-speed Drive Electric Tractor

作　　者：陈安焱 陈树人[1] 施爱平[1] 徐立友 张厚忠[1] Chen Anyan;Chen Shuren;Shi Aiping;Xu Liyou;Zhang Houzhong(Key Laboratory of Modern Agricultural Equipment and Technology,Ministry of Education and Jiangsu Province,Jiangsu University,Zhenjiang 212013,China;College of Vehicle and Traffic Engineering,Henan University of Science and Technology,Luoyang 471003,China)

机构地区：[1]江苏大学现代农业装备与技术教育部重点试验室,江苏镇江212013 [2]河南科技大学车辆与交通工程学院,河南洛阳471003

出　　处：《农机化研究》2021年第11期1-6,共6页Journal of Agricultural Mechanization Research

基　　金：“十三五”国家重点研发计划项目(2016YFD0701002);河南省高校科技创新人才支持计划项目(18HASTIT026);江苏省研究生科研创新计划项目(KYCX182265)。

摘　　要：根据双电机耦合驱动电动拖拉机的动力传递特点,为了提高双电机运行效率,从而提高电池能量的利用率,提出了一种基于线性递减权重粒子群算法的双电机耦合驱动电动拖拉机转矩分配策略。结合粒子群算法的全局搜索特点与电机效率曲线,制定了适应度函数与惯性因子。仿真与标准粒子群算法对比表明:基于线性递减权重的粒子群算法收敛速度快,搜索结果更优。Simulink仿真与硬件在环对比表明:仿真结果在运输工况与犁耕工况下需求转矩相对误差分别为1.24%、4.45%,比标准粒子群算法的SOC变化量分别提升4.26%与5.81%。According to the power transmission characteristics of the dual-motor coupled driving electric tractor, in order to improve the operating efficiency of the dual-motor and thus improve the utilization of battery energy,a torque distribution strategy of the dual-motor coupled driving electric tractor based on a linear decreasing weight particle swarm optimization algorithm is proposed.Combining the global search characteristics of the particle swarm optimization algorithm and the motor efficiency curve, a fitness function and an inertia factor are formulated.By comparing simulation with standard particle swarm optimization,the particle swarm algorithm based on linearly decreasing weights converges faster and the search results are better.The comparison between Simulink simulation and hardware-in-the-loop simulation results shows that the relative errors of demand torque under transport conditions and ploughing conditions are 1.24% and 4.45%,respectively, which are 4.26% and 5.81% higher than the SOC changes of standard particle swarm algorithm.

关 键 词：双电机耦合驱动 电动拖拉机 转矩分配 粒子群算法 

分 类 号：S219.032.1[农业科学—农业机械化工程]