نوع مقاله : مقاله پژوهشی
نویسنده
دانشگاه بیرجند
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسنده [English]
In Battery Management Systems (BMS), State of charge of Battery (SOC) estimation is very important to ensure performance and to prevent overcharging and discharging. So far, various methods have been presented to estimate state of charge of Battery. In most of these methods, the statistical characteristics of process noise and measurement are assumed to be known. By choosing the wrong statistical characteristics of process noise and measurement, the performance of the filters is affected and the accuracy of the charging state estimation is reduced and may even lead to divergence. To solve this problem, in this paper, adaptive robust square-root cubature filter is used to estimate state of charge of battery and the least squares recursive algorithm is used to estimate the battery parameters. The proposed method, along with the benefits of reducing computational cost, has advantages such as increased compatibility leading to greater numerical stability and better performance. This is because in the proposed method, all variance matrices remain positive definite. In addition, the proposed method is robust to inaccurate noise information as well as non-Gaussian noise. To evaluate the performance of the proposed method, this method is compared with the classical methods. To evaluate the performance of the proposed method, this method has been compared with the classical method of estimating the state of charge of a battery. The results show the effective performance of the proposed method compared to the other methods.
کلیدواژهها [English]
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