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Design of a Load Torque Based Control Strategy for Improving Electric Tractor Motor Energy Conversion Efficiency

机译:基于负载转矩的控制策略设计,以提高电动拖拉机的能量转换效率

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摘要

In order to improve the electrical conversion efficiency of an electric tractor motor, a load torque based control strategy (LTCS) is designed in this paper by using a particle swarm optimization algorithm (PSO). By mathematically modeling electric-mechanical performance and theoretical energy waste of the electric motor, as well as the transmission characteristics of the drivetrain, the objective function, control relationship, and analytical platform are established. Torque and rotation speed of the motor's output shaft are defined as manipulated variables. LTCS searches the working points corresponding to the best energy conversion efficiency via PSO to control the running status of the electric motor and uses logic and fuzzy rules to fit the search initialization for load torque fluctuation. After using different plowing forces to imitate all the common tillage forces, the simulation of traction experiment is conducted, which proves that LTCS can make the tractor use electrical power efficiently and maintain agricultural applicability on farmland conditions. It provides a novel method of fabricating a more efficient electric motor used in the traction of an off-road vehicle.
机译:为了提高电动拖拉机电机的电转换效率,本文采用粒子群优化算法(PSO)设计了基于负载转矩的控制策略(LTCS)。通过对电动机的机电性能和理论上的能源浪费以及传动系统的传动特性进行数学建模,从而建立了目标函数,控制关系和分析平台。电机输出轴的转矩和转速定义为操纵变量。 LTCS通过PSO搜索与最佳能量转换效率相对应的工作点,以控制电动机的运行状态,并使用逻辑和模糊规则来拟合针对负载转矩波动的搜索初始化。在采用不同的耕作力模拟所有常用耕作力后,进行了牵引试验仿真,证明了LTCS可以使拖拉机有效地利用电力,并在农田条件下保持农业适用性。它提供了一种新颖的方法来制造用于越野车辆牵引的更高效的电动机。

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  • 来源
    《Mathematical Problems in Engineering》 |2016年第4期|2548967.1-2548967.14|共14页
  • 作者单位

    Xian Univ Technol, Sch Mech & Precis Instrument Engn, 5 Jinhua South Rd, Xian 710048, Peoples R China;

    Henan Univ Sci & Technol, Vehicle & Transportat Engn Inst, 48 Xiyuan Rd, Luoyang 471003, Peoples R China;

    Henan Univ Sci & Technol, Vehicle & Transportat Engn Inst, 48 Xiyuan Rd, Luoyang 471003, Peoples R China;

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