Abstract
The usage of batteries in recent years has become widespread in many fields e.g. in electric vehicles, energy renewable and stand-alone systems which require a robust approach for estimation of the state of charge (SOC). The SOC represents an important factor to guaranty safe operations. A lot of methods have been used to predict the state of charge. The coulomb counting method is the famous and widely used among them, but have limitation due to its accuracy. Another used approach is the Kalman Filter, which improves the estimation efficiency, to reach a good performance in SOC prediction. The version of adaptive extended Kalman filter (AEKF) technique is applied in this paper. This paper presents an experimental performance of technique of Kalman filter, for solving the problem of accurate SOC. The method is used to compute the terminal voltage in such a way to estimate the SOC. The proposed algorithm is based on preselected Thevenin model after the identification of its parameters. It has been used to predict the SOC based on nonlinear equations, and evaluation of the approach is verified with the experimental results. The final results signify that the estimation matched with the proposed model and the algorithm is performed optimally, thus the maximum soc estimation error is the finest
Highlights
In recent years, applications of the battery become widespread because it is friendly to the environment
The validation of adaptive extended Kalman filter (AEKF) state of charge estimation is checked by the comparison of the experimental SOC and the estimated SOC
It is very accurate towards the measurements noise and poor initialisation of the SOC. By comparing these two results of tracking the output of experiment and the algorithm, we find that the AEKF can reach almost the same asthe experiment and are very close to each other
Summary
Applications of the battery become widespread because it is friendly to the environment. Many advantages are available in energy transforming from battery, which provides benefits in stakeholders and integration of renewable sources including solar and wind. The main objective of renewable sources is to take advantages of a question of reliability of the systems supply, bring vitality to the demand response of electric storage, and addressing the issues of eco-friendly and economic [1, 2]. The battery storage devices response in a short period of time. They can be distributed in various sizes and can be evaluated by fast control systems [3]
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