Abstract
Lithium-bismuth liquid metal batteries have much potential for stationary energy storage applications, with characteristics such as a large capacity, high energy density, low cost, long life-span and an ability for high current charge and discharge. However, there are no publications on battery management systems or state-of-charge (SoC) estimation methods, designed specifically for these devices. In this paper, we introduce the properties of lithium-bismuth liquid metal batteries. In analyzing the difficulties of traditional SoC estimation techniques for these devices, we establish an equivalent circuit network model of a battery and evaluate three SoC estimation algorithms (the extended Kalman filter, the unscented Kalman filter and the particle filter), using constant current discharge, pulse discharge and hybrid pulse (containing charging and discharging processes) profiles. The results of experiments performed using the equivalent circuit battery model show that the unscented Kalman filter gives the most robust and accurate performance, with the least convergence time and an acceptable computation time, especially in hybrid pulse current tests. The time spent on one estimation with the three algorithms are 0.26 ms, 0.5 ms and 1.5 ms.
Highlights
The use of energy storage systems could significantly improve the reliability and efficiency of power grids, with respect to the integration of intermittent renewable energy sources [1]
To verify the applicability of the proposed algorithms to Liquid metal batteries (LMBs) management, we evaluated the results of estimation using qualitative analyses of the derived parameters and quantitative analyses of the error between the predicted and reference values of SoC and CCV
We 0.75 are able to0.0871 observe clear distinctions in the behavior of the three algorithms. They all converge to the reference value initially, with the extended Kalman filter (EKF) algorithm, the estimation error began to grow after 4 h, eventually reaching a maximum of 0.3
Summary
The use of energy storage systems could significantly improve the reliability and efficiency of power grids, with respect to the integration of intermittent renewable energy sources [1]. The measured capacity loss after operation for more than 450 charge–discharge cycles at 100 percent depth of discharge with the current densities as 1000 milliamperes per square centimeter, projects retention of over 85 percent of initial capacity after ten years of daily cycling [2]. As well as their increased energy density, these characteristics are advantageous in reducing the cost of adoption of LMBs, for large-scale applications.
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