Journal
JOURNAL OF POWER ELECTRONICS
Volume 16, Issue 1, Pages 217-226Publisher
KOREAN INST POWER ELECTRONICS
DOI: 10.6113/JPE.2016.16.1.217
Keywords
Characteristic value; Health states; Hidden Markov model; Internal resistance
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Funding
- CQ CSTC [CSTC2013yykfC60005, CSTC2014jcyjA6004, CSTC2013jcsf-jcssX0022]
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A new method is proposed based on a hidden Markov model (HMM) to estimate and analyze battery states of health. Battery system health states are defined according to the relationship between internal resistance and lifetime of cells. The source data (terminal voltages and currents) can be obtained from vehicular battery models. A characteristic value extraction method is proposed for HMM. A recognition framework and testing datasets are built to test the estimation rates of different states. Test results show that the estimation rates achieved based on this method are above 90% under single conditions. The method achieves the same results under hybrid conditions. We can also use the HMMs that correspond to hybrid conditions to estimate the states under a single condition. Therefore, this method can achieve the purpose of the study in estimating battery life states. Only voltage and current are used in this method, thereby establishing its simplicity compared with other methods. The batteries can also be tested online, and the method can be used for online prediction.
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