AI RESEARCH
A Hybrid Tucker-LSTM Tensor Network Model for SOC Prediction in Electric Vehicles
arXiv CS.LG
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ArXi:2605.13200v1 Announce Type: new Accurate state of charge estimation is critical for the success of electric vehicle battery management strategies, but it is well known that conventional estimators suffer from two fundamental shortcomings: cumulative errors that grow over time and reliance on simplified battery models that do not reflect real world dynamics. Therefore, this paper presents a novel hybrid approach combining Tucker tensor decomposition with LSTM networks, using full - lifecycle EV field data for SOC prediction.