摘要
针对当前国内外铅酸蓄电池容量测试及活化设备智能化程度低、容量快速预测误差大和功能简单等问题,提出一种基于遗传退火优化BP神经网络的蓄电池剩余容量快速预测算法和劣化蓄电池活化诊治方法。研制了基于ARM9和μC/OS-Ⅱ嵌入式操作系统平台的蓄电池容量预测与活化诊治系统。系统由总控、充电和放电三个单元组成,各单元通过RS-485总线构成分布式测控系统,具有蓄电池充电、放电、剩余容量快速预测和劣化电池活化等功能。
Aiming at the problem of weak intelligence,big error of fast capability prediction;and simple function of VRLA battery capability prediction and activation equipment,a method of fast capability prediction and activation based on BP neural networks optimized by genetic-annealing algorithm is presented.And a system of battery capability prediction and activation equipment based on ARM9 and μC/OS-Ⅱ is developed which consists of three parts of general control,charge and discharge.The parts make up a distributed system with RS-485 bus and have the functions of charge,discharge and battery capability prediction and bad battery activation.
出处
《工业控制计算机》
2009年第10期1-3,共3页
Industrial Control Computer
基金
科技部国际科技合作项目(2007DFR10420)
重庆市重点科技攻关项目(CSTC2007AA2015)
(CSTC2008AC2107)资助项目
