Abstract

This paper deals with the problem of sampled-data observer design to estimate the state of health (SoH), the state of charge (SoC), and the internal temperature for batteries. The observation is based on the estimation of the battery internal resistance, which is supposed to be unknown and varying with temperature. The difficulty is that the system state equation contains an unknown parameter (which represents the internal resistance) and an output-dependent term only accessible to measurement at sampling time. The proposed approach consists of several levels of estimation and calculation using non-linear observers and fitting functions exploiting experimental data. It has been shown, using theoretical analysis, simulations, and experimental results, that the proposed method gives a novel approach to estimate the quantities (SoH, SoC, and temperature) useful for the battery management system (BMS). The point is that this approach only involves the estimation of the internal resistance of the battery.

摘要

本文讨论了采样数据观测器设计的问题，以估计电池的健康状态 (SoH)、充电状态 (SoC) 和内部温度。该观察基于对电池内阻的估计，该内阻应该是未知的并且随温度而变化。困难在于系统状态方程包含一个未知参数（代表内阻）和一个只能在采样时测量的与输出相关的项。所提出的方法包括使用非线性观测器和利用实验数据的拟合函数的多个级别的估计和计算。使用理论分析、模拟和实验结果表明，所提出的方法提供了一种估计数量（SoH、SoC、和温度）对电池管理系统 (BMS) 有用。关键是这种方法只涉及电池内阻的估计。