基于改进细菌觅食优化算法的电动转向系统功率优化  

Power optimization of EPS system based onimproved BFO algorithm

作　　者：吴立群 李媛媛[1] 陈少棠 WU Liqun;LI Yuanyuan;CHEN Shaotang(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620

出　　处：《传感器与微系统》2021年第8期61-64,共4页Transducer and Microsystem Technologies

基　　金：上海市科学技术委员会地方高校能力建设项目(15590501300)。

摘　　要：为了降低新能源纯电动汽车中电动助力转向系统的电能消耗,提出一种基于改进细菌觅食优化(IBFO)算法的功率优化控制策略。建立电动助力转向系统动态模型和车辆模型,通过改进细菌觅食算法的趋化操作和迁徙操作,提高了算法的收敛速度和精度。采用时间误差绝对积分函数评价细菌觅食算法的收敛性。分别进行MATLAB/SIMULINK仿真和硬件在环试验,测试结果表明:改进后的细菌觅食算法控制器能够更加有效地降低助力电机的功率,减少了转向过程中助力电机功耗。In order to reduce power consumption of electric power steering system in new energy pure electric vehicles,a power optimization control strategy based on an improved bacterial foraging optimization(IBFO)algorithm is proposed.The dynamic model and vehicle model of the electric power steering system are established,and the convergence speed and precision of the algorithm are improved by improving the trending and migration operation of the BFO algorithm.The integral function of time multiplied absolute value of error is used to evaluate the convergence of the BFO algorithm.The MATLAB/SIMULINK simulation and hardware-in-the-loop test are performed separately.The test results show that the IBFO algorithm controller can reduce power of booster motor more effectively and reduce power consumption of the booster motor during steering.

关 键 词：电动助力转向(EPS)系统 改进细菌觅食优化(IBFO)算法 功率优化 

分 类 号：U463.4[机械工程—车辆工程] TP212[交通运输工程—载运工具运用工程]