| 基于自适应神经网络模糊推理系统的蓄电池SOH预测 |
| |
| 引用本文： | 李刚,谢永成,李光升,朱祺. 基于自适应神经网络模糊推理系统的蓄电池SOH预测[J]. 微型机与应用, 2011, 30(22): 82-84,87 |
| |
| 作者姓名： | 李刚 谢永成 李光升 朱祺 |
| |
| 作者单位： | 装甲兵工程学院控制工程系,北京,100072 |
| |
| 摘 要： | 针对装甲车辆铅酸蓄电池健康状况影响因素复杂、难以准确预测的特点,提出了基于自适应神经网络模糊推理系统的蓄电池SOH预测模型。在确定模型的输入变量后,对其进行了MATLAB仿真和实测数据验证分析。结果表明,该模型具有很高的预测精度,在装甲车辆铅酸蓄电池SOH预测上具有很高的实用价值。
|
| 关 键 词： | 蓄电池SOH 自适应神经网络模糊推理系统 预测模型 MATLAB |
Prediction of battery SOH based on adaptive neural fuzzy inference system |
| |
| Li Gang,Xie Yongcheng,Li Guangsheng,Zhu Qi. Prediction of battery SOH based on adaptive neural fuzzy inference system[J]. Microcomputer & its Applications, 2011, 30(22): 82-84,87 |
| |
| Authors: | Li Gang Xie Yongcheng Li Guangsheng Zhu Qi |
| |
| Affiliation: | (Department of Control Engineering,Academy of Armored Forces Engineering,Beijing 100072,China) |
| |
| Abstract: | There are many factors influence armored vehicles lead-acid battery SOH, so it＇s hard to predict it accurately. Aiming at this characteristic, the paper puts forward a battery SOH prediction model using the adaptive neural fuzzy inference system. After confirming the input variables, then do the MATLAB simulation and real-time data validation. The result shows the model has a high precision, and it has a high practical value when using in the armored vehicles lead-acid battery SOH prediction. |
| |
| Keywords: | battery SOH ANFIS prediction model MATLAB |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
