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Adaptive control for estimating insulation resistance of high‐voltage battery system in electric vehicles
Author(s) -
Chiang YiHsien,
Sean WuYang,
Huang ChihYung,
Chiang Hsieh LinHan
Publication year - 2017
Publication title -
environmental progress and sustainable energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.495
H-Index - 66
eISSN - 1944-7450
pISSN - 1944-7442
DOI - 10.1002/ep.12644
Subject(s) - waveform , parasitic capacitance , voltage , capacitance , electrical engineering , battery (electricity) , automotive engineering , engineering , track circuit , internal resistance , electronic engineering , computer science , electronic circuit , electrode , power (physics) , chemistry , physics , quantum mechanics
To ensure electrical safety in electric vehicles equipped with a high‐voltage battery pack, an insulation monitoring circuit is indispensible to continuously monitor the insulation resistance during charging or driving. Existing methods such as to inject specific signals into the monitoring circuit and earth help to extract the resistance value from the voltage waveform. However, parasitic or stray capacitances in the monitoring circuit, which might introduce higher‐order dynamics into the waveform are ignored. Or to avoid estimation error, the insulation resistance must be known in advance to carry out parameter calibration. In this work, one parasitic capacitance is applied in the circuit model and employ a new adaptive algorithm based on Lyapunov stability to estimate the insulation resistance. This new online monitoring method and circuit are verified through simulation and experimentation, respectively. The results demonstrate that the proposed method can quickly react and track variations of insulation resistance on both positive and negative DC lines. © 2017 American Institute of Chemical Engineers Environ Prog, 36: 1882–1887, 2017