基于模糊PI控制的蓄电池智能充电控制系统研究

Study on intelligent charging system of battery based on Fuzzy PI Control

蓄电池充电过程中存在复杂的、时变的化学反应和电化学反应,加之蓄电池参数的非线性、离散性和不确定性,采用常规PI控制在对其实现控制时往往效果不佳。模糊控制不过分依赖被控对象的数学模型,针对传统模糊控制的不足,提出基于遗传算法的模糊PI控制规则优化方法,并利用大时滞对象作为充电系统的被控对象做仿真分析,得出基于遗传算法的模糊PI控制优于常规模糊PI控制。

The battery charging process is complex and time-varying, and the parameters of battery are non-linear, discrete and uncertain. Therefore the battery system can’t be effectively controlled by using the conventional PI control algorithm. As the fuzzy control don’t rely much on the model, aiming at the shortcomings of the traditional fuzzy control, this paper put forward an optimization method of fuzzy PI controlling rules based on genetic algorithm. By using the large delay object as the charging system, it is concluded that the optimization method is better than general fuzzy PI control after some simulation and analysis.