Prediction of Remaining Useful Life of Lithium-ion Battery based on Multi-kernel Support Vector Machine with Particle Swarm Optimization

Dong Gao; Miaohua Huang

Prediction of Remaining Useful Life of Lithium-ion Battery based on Multi-kernel Support Vector Machine with Particle Swarm Optimization

Dong Gao

Miaohua Huang

Vol. 17, No. 5, pp. 1288-1297, Sep. 2017

10.6113/JPE.2019.17.5.1288

Lithium-ion battery RUL

Multi-kernel support vector machine

Particle swarm optimization algorithm

RUL prediction

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Abstract

The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.

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Cite this article

[IEEE Style]

D. Gao and M. Huang, "Prediction of Remaining Useful Life of Lithium-ion Battery based on Multi-kernel Support Vector Machine with Particle Swarm Optimization," Journal of Power Electronics, vol. 17, no. 5, pp. 1288-1297, 2017. DOI: 10.6113/JPE.2019.17.5.1288.

[ACM Style]

Dong Gao and Miaohua Huang. 2017. Prediction of Remaining Useful Life of Lithium-ion Battery based on Multi-kernel Support Vector Machine with Particle Swarm Optimization. Journal of Power Electronics, 17, 5, (2017), 1288-1297. DOI: 10.6113/JPE.2019.17.5.1288.