基于改进粒子群算法的蓄电池状态估计方法

Battery State Estimation Method Based on Improved Particle Swarm Optimization

为了保障直流系统的稳定运行,需要精确评估主要组成元件蓄电池的状态,以便于制定合理的运行维护方案,提高直流系统的安全保护性能。状态估计需要对蓄电池进行建模和评估,本文提出一种动态调整惯性权重系数的改进粒子群算法对状态做出估计,并通过仿真验算其有效性。

In order to ensure the stable operation of the DC system,it is necessary to accurately evaluate the state of the main components of the battery,so as to formulate a reasonable operation and maintenance scheme and improve the safety protection performance of the DC system.State estimation needs to model and evaluate the battery.In this paper,an improved particle swarm optimization algorithm is proposed to dynamically adjust the inertia weight coefficient to estimate the state,and make use of simulation to verify its effectiveness.