پیاده‌سازی سیستم تطبیقی فازی-عصبی در مدل‌سازی و تخمین حالت شارژ باتری‌های لیتیوم-یون

نویسندگان
محمد نصیری 1
محمدحسین کاظمی 2
1 کارشناسی ارشد، مهندسی برق – کنترل، دانشگاه شاهد، تهران، ایران
2 دانشیار، دانشکده فنی و مهندسی، دانشگاه شاهد، تهران، ایران
چکیده
در این مقاله با بکارگیری یک شبکه عصبی فازی‌ و براساس مدل فضای حالت باتری‌های لیتیوم-یون، حالت شارژ باطری تخمین زده می‌شود. داده‌های آزمایشگاهی نمونه‌برداری از باتری، عبارتند از سیگنال‌های ولتاژ و جریان پایانه‌های باتری که برای مدلسازی باتری مورد استفاده قرار می‌گیرند. با اجرای پنجره لغزان، پارامترهای مدل سیستم در پنجره‌های کاری مختلف براساس روش کمترین مربعات خطا شناسایی شده و با استفاده از یک شبکه عصبی فازی‌ آموزش داده می‌شوند. سپس از تئوری فیلتر کالمن بهره برده و یک الگوریتم جهت تخمین حالت شارژ ارائه می‌شود. سه دسته داده عملی از اطلاعات ولتاژ و جریان باتری به صورت جداگانه جمعآوری شده و برای آموزش شبکه عصبی فازی‌ ، تعیین صحت عملکرد تخمین پیشنهادی و مدل آموزش یافته، بکار گرفته می‌شوند. برای هر سه دسته از داده‌ها، مقایسه تخمین به روش پیشنهادی و روش‌های فیلتر تطبیقی H و EKF و SRUKF صورت پذیرفت که نتایج نشان می‌داد روش پیشنهادی در تمام حالات از شاخص خطای تخمین مناسب‌تری برخوردار می‌باشد.

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علوم رایانش و فناوری اطلاعات
دوره 19، شماره 1
بهار و تابستان
بهار 1400