基于IMPSO-BP镍氢电池智能充电技术  

NI-MH batteries intelligence charging based on IWPSO-BP

作　　者：程方晓[1] 王源[1] 王旭[1] CHENG Fangxiao WANG Yuan WANG Xu(School of Electrical Electronic Engineering, Changchun University of Technology, Changchun 130012, China)

机构地区：[1]长春工业大学电气与电子工程学院,吉林长春130012

出　　处：《长春工业大学学报》2016年第5期461-464,共4页Journal of Changchun University of Technology

基　　金：吉林省科技发展计划基金资助项目(20120362)

摘　　要：以充电电压与额定电压之差ΔV和临近两个电压采样点的变化率Δu/Δt作为输入变量,建立人工神经网络模型,研究了基于自适应动态调整惯性权重粒子群算法的BP算法(IMPSO-BP)。利用Matlab仿真得到了理想的快速充电电流。The difference between charging voltage and rated voltageΔV and the change rate between the two near voltage sampling pointΔu/Δt are taken as the inputs to build an Artificial Neural Network Model.A BP algorithmbased on adaptive dynamic adjustment inertia weightparticle swarmoptimization（IWPSO-BP）is studied,and the fast changing current is obtained with Matlab simulation.

关 键 词：电动汽车 充电 镍氢电池 粒子群算法 人工神经网络 

分 类 号：TM910.06[电气工程—电力电子与电力传动]