Journal
IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 33, Issue 1, Pages 332-342Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2017.2670081
Keywords
Battery in the loop; capacity; dualHinfinity filters (HIFs); lithium-ion battery; multiscale; state of charge (SoC)
Categories
Funding
- National Natural Science Foundation of China [51507012]
- Australian Research Council Linkage Grant [LP110200302]
- Sino-Polish Collaborative Research in E-mobility Public Transportation [2015DFG81930]
- Beijing Nova Program [Z171100001117063]
- Joint Funds of the National Natural Science Foundation of China [U1564206]
- Australian Research Council [LP110200302] Funding Source: Australian Research Council
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An accurate battery capacity and state estimation method is one of the most significant and difficult techniques to ensure efficient and safe operation of the batteries for electric vehicles (EVs). Since capacity and state of charge (SoC) are strongly correlated, the SoC is hardly to be accurately estimated without knowing accurate battery capacity. Thus, a multiscale dual Hinfinity filter (HIF) has been proposed to estimate battery SoC and capacity in real time with dual timescales in response to slow-varying battery parameters and fast-varying battery state. The proposed method is first evaluated and verified using off-line experimental data and then compared with the single/multiscale dual Kalman filters (KFs). The results show that the proposed multiscale dual HIFs has better robustness and higher estimation accuracy than the single/multiscale dual KFs. To further validate the feasibility of the proposed method for EV applications, a lithium-ion battery-in- the-loop approach is applied to verify the stability and accuracy of the SoC estimation, and it is found that the SoC estimated from the proposedmethod can converge to the reference value gradually and be stabilized within 2%.
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