کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6903928 | 1446995 | 2018 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A GPU-accelerated parallel Jaya algorithm for efficiently estimating Li-ion battery model parameters
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
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چکیده انگلیسی
A parallel Jaya algorithm implemented on the graphics processing unit (GPU-Jaya) is proposed to estimate parameters of the Li-ion battery model in this paper. Similar to the generic Jaya algorithm (G-Jaya), the GPU-Jaya is free of tuning algorithm-specific parameters. Compared with the G-Jaya algorithm, three main procedures of the GPU-Jaya, the solution update, fitness value computation, and the best/worst solution selection are all computed in parallel on GPU via a compute unified device architecture (CUDA). Two types of memories of CUDA, the global memory and the shared memory are utilized in the execution. The effectiveness of the proposed GPU-Jaya algorithm in estimating model parameters of two Li-ion batteries is validated via real experiments while its high efficiency is demonstrated by comparing with the G-Jaya and other considered benchmarking algorithms. The experimental results reflect that the GPU-Jaya algorithm can accurately estimate battery model parameters while tremendously reduce the execution time using both entry-level and professional GPUs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 65, April 2018, Pages 12-20
Journal: Applied Soft Computing - Volume 65, April 2018, Pages 12-20
نویسندگان
Long Wang, Zijun Zhang, Chao Huang, Kwok Leung Tsui,