دوره 13، شماره 1 - ( 12-1401 )                   جلد 13 شماره 1 صفحات 4050-4041 | برگشت به فهرست نسخه ها


XML English Abstract Print


چکیده:   (5916 مشاهده)
As electric vehicles become more popular, we need to keep improving the lithium-ion batteries that power them. Electrochemical impedance spectroscopy (EIS) is used based on a discrete random binary sequence (DRBS) to reduce excitation time in the low-frequency region and excite the input of the battery. In this paper, voltage and current signals are processed with wavelet transform for impedance evaluation. In using wavelet transform, choosing the most optimal mother wavelet is crucial for impedance evaluation since different mother wavelets can produce different results. We aim to compare three types of continuous Morse mother wavelet, continuous Morlet, and continuous lognormal wavelet, which are among the most important mother wavelets, to determine the best method for impedance evaluation. We used the dynamic time-warping algorithm to quantify the difference between the initial values obtained from standard laboratory equipment and the impedance evaluation through three different continuous wavelets. Our proposed method (lognormal wavelet) has the lowest difference (3.4086) from the initial values compared to the Morlet (3.5504), and Morse (3.5457) methods. As a result, our simulation shows that the lognormal wavelet transform is the best method for impedance evaluation compared to Morlet and Morse wavelets.
متن کامل [PDF 573 kb]   (2615 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: سوخت های جایگزین

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.