Abstract
The DE algorithm has strong global search ability and robustness, but also has the shortcoming of slow convergence speed and local search ability is insufficient, and TLBO algorithm has the advantage of strong local search ability and faster convergence speed, but will be fall into the local optimum when dealing with complex problems. In this paper, the DE algorithm and TLBO algorithm are combined to construct a two-population co-evolutionary algorithm based on the DE and TLBO algorithm (DPCEDT). By theory analysis, the proposed DPCEDT algorithm can be used to improve the SOC estimation algorithm of power battery which is an extremely complex problem.
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Acknowledgement
This work was jointly supported by Natural Science Foundation of China (61773296), the Education Department of Jiangxi Province of China Science and Technology research projects with the Grant No. GJJ151433, GJJ161687, GJJ161688 and GJJ161691.
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Zhong, W., Gu, F., Wang, W. (2018). A New SOC Estimation Algorithm. In: Li, K., Li, W., Chen, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2017. Communications in Computer and Information Science, vol 874. Springer, Singapore. https://doi.org/10.1007/978-981-13-1651-7_27
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DOI: https://doi.org/10.1007/978-981-13-1651-7_27
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