Estimation of Remaining Useful Life in Lithium-Ion Batteries using Bidirectional Long-Short Term Memory

Lithium-ion batteries are a type of rechargeable battery known for their high energy capacity and extended lifespan. Although lithium-ion battery technology is advancing rapidly, these batteries have a limited operational lifespan and their energy storage capability decreases with time and usage. This is where Remaining Useful Life (RUL) calculations become essential for battery maintenance planning. This study aims to employ the Bidirectional Long-Short Term Memory (BiLSTM) technique to predict the RUL of Li-ion batteries and compare it with the Long-Short Term Memory (LSTM) method to determine the most effective approach. The training data included batteries B0005, B0006, B0007, B0018, B0025, B0026, B0027, B0028, and B0055 for experiments. The BiLSTM approach consistently outperformed the LSTM method for each battery. The best results were achieved with battery B0005 using BiLSTM, with RMSE, MSE, MAE, and MAPE values of 0.01612, 0.00026, 0.00971, and 0.00684, respectively, indicating that the BiLSTM method is capable of accurately estimating the RUL of lithium-ion batteries.