Lithium-ion batteries are now widely used as energy storage units in electric vehicles. Achieving high accuracy in state of charge (SOC) estimation in the battery management system (BMS) is critical for safe operation of electric vehicles. However, accurate SOC estimation remains a challenging task due to the complex dynamics of batteries and the wide range of ambient temperature. Here we propose a new method called ResNet-GRNN for accurate SOC estimation. Our approach combines a Residual network (ResNet) and a gated recurrent neural network (GRNN). Compared to traditional GRNNs, the proposed ...
