Abstract
As the emergency power supply for a simulation substation, lead-acid batteries have a work pattern featuring non-continuous operation, which leads to capacity regeneration. However, the accurate estimation of battery state of charge (SOC), a measurement of the amount of energy available in a battery, remains a hard nut to crack because of the non-stationarity and randomness of battery capacity change. This paper has proposed a comprehensive method for lead-acid battery SOC estimation, which may aid in maintaining a reasonable charging schedule in a simulation substation and improving battery’s durability. Based on the battery work pattern, an improved Ampere-hour method is used to calculate the SOC during constant current and constant voltage (CC/CV) charging and discharging. In addition, the combined Particle Swarm Optimization (PSO) and Least Squares Support Vector Machine (LSSVM) model is used to estimate the SOC during non-CC discharging. Experimental results show that this method is workable in online SOC estimation of working batteries in a simulation substaion, with the maximum relative error standing at only 2.1% during the non-training period, indicating a high precision and wide applicability.
Highlights
As the hub of the power grid, substations are responsible for power supply for different regions, which makes training on substation operation and maintenance crucial
He et al [9,10] proposed an electromotive force (EMF) method combined with recursive least-squares (RLS) for online estimation of open circuit voltage (OCV) and state of charge (SOC) of Li-ion batteries
In order to achieve a better effect on battery SOC estimation, this paper proposes a comprehensive method to estimate the battery SOC under the CC and non-CC models
Summary
As the hub of the power grid, substations are responsible for power supply for different regions, which makes training on substation operation and maintenance crucial. Since the French physicist Gaston Plante invented the world’s first rechargeable battery based on leadacid chemistry in 1859, the lead-acid battery has been gaining momentum and applied in more and more scenarios due to its high safety, low cost, stable operation and long service life [2,3]. When it is woven into the fabric of our daily life, the research on the lead-acid battery SOC comes under the spotlight. The relative error is less than 3%, but the electrochemical model entails a lot of mathematical formula calculations and modeling, which brings down the applicability He et al [9,10] proposed an electromotive force (EMF) method combined with recursive least-squares (RLS) for online estimation of OCV and SOC of Li-ion batteries. Due to the limitation of the Ampere-hour method [14], this paper will correct the influence of temperature and the charge and discharge current on the Ampere-hour method in the process of battery charging and discharging
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