摘要
针对电动助力转向系统中的转矩传感器进行改进设计,实现了转矩和转角信号的一体化测量,节约了空间。建立了传感器齿轮组的数学模型,根据其使用特点,设定了数学模型的边界条件,并利用遗传算法与粒子群算法相结合的混合算法对齿轮系统的参数进行了优化设计,使传感器的质量和体积均有所下降,通过与传统设计方法及惩罚函数优化法相比较,混合算法优化的效果更佳。
The design of torque sensor in the EPAS was improved, the integration of torque and angle signal measuring was re- alized and the space was saved.The mathematical model of the sensor gear set was established and according to the characteristics of its use ,the boundary conditions for the mathematical model were set.The hybrid algorithm combining the genetic algorithm and the particle swarm optimization was used to optimize the parameters of the gear system, which declined the quality and volume of the sensor.Compared with the traditional design methods and the penalty function optimization , the optimization effect of this hybrid algorithm is better.
出处
《仪表技术与传感器》
CSCD
北大核心
2015年第4期93-95,103,共4页
Instrument Technique and Sensor
基金
北京高等学校"青年英才计划"资助项目(YETP1798)
科研基地-汽车技能大师工作室建设(国家改革试点项目2012)(PXM2012-014306-000177)
关键词
电动助力转向系统
转矩转角传感器
齿轮优化
遗传算法
粒子群算法
electric power steering system
torque and angle integration sensor
gear optimization design
genetic algorithm
particleswarm optimization
