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GPU-accelerated parallel coevolutionary algorithm for parameters identification and temperature monitoring in permanent magnet synchronous machines

journal contribution
posted on 28.09.2016, 08:59 by Zhao-Hua Liu, Xiao-Hua Li, Liang-Hong Wu, Shao-Wu Zhou, Kan Liu
A hierarchical fast parallel co-evolutionary immune particle swarm optimization (PSO) algorithm, accelerated by graphics processing unit (GPU) technique (G-PCIPSO), is proposed for multiparameter identification and temperature monitoring of permanent magnet synchronous machines (PMSM). It is composed of two levels and is developed based on compute unified device architecture (CUDA). In G-PCIPSO, the antibodies (Abs) of higher level memory are selected from the lower level swarms and improved by immune clonal-selection operator. The search information exchanges between swarms using the memory-based sharing mechanism. Moreover, an immune vaccine-enhanced operator is proposed to lead the Pbests particles to unexplored areas. Optimized parallel implementations of G-PCIPSO algorithm is developed on GPU using CUDA, which significantly speeds up the search process. Finally, the proposed algorithm is applied to multiple parameters identification and temperature monitoring of PMSM. It can track parameter variation and achieve temperature monitoring online effectively. Compared with a CPU-based serial execution, the computational efficiency is greatly enhanced by GPU-accelerated parallel computing technique.

Funding

This work was supported in part by the China Postdoctoral Science Foundation funded project under Grant 2013M540628 and Grant 2014T70767, in part by the National Natural Science Foundation of China under Grant 61174140 and Grant 51374107, and in part by the Hunan Provincial Natural Science Foundation of China under Grant 13JJ8014 and Grant 14JJ3107. Paper no. TII-14-0700.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Industrial Informatics

Volume

11

Issue

5

Pages

1220 - 1230

Citation

LIU, Z.-H. ... et al, 2015. GPU-accelerated parallel coevolutionary algorithm for parameters identification and temperature monitoring in permanent magnet synchronous machines. IEEE Transactions on Industrial Informatics, 11 (5), pp. 1220-1230.

Publisher

© IEEE

Version

VoR (Version of Record)

Publication date

2015

Notes

This paper is closed access.

ISSN

1551-3203

eISSN

1941-0050

Language

en

Exports