Abstract: The accurate evaluation of charging and discharging power capability is the basis of safe and efficient operation of the batteries and electric vehicles. Aims at electric transport equipment, the main works are as follow. A battery model with input/output power as the control target is established, and the charging and discharging behaviour of battery-driven by power demand is described. A multi-step power prediction method has been proposed through setting a fixed charge-discharge cut-off control voltage to a dynamic control objective, and the detailed prediction strategy for the charging and discharging power capacity has been established. Considering the influence of the state of charge, temperature, and duration, etc, the power update model is established with the long- and short-term memory neural network to improve the prediction performance of battery charge and discharge power capability. The results show that the proposed method can take into account the prediction accuracy and calculation efficiency, and the maximum error is less than 3%; the power correction method can reasonably predict the power capacity under the full state of charge range, wide temperature, and long duration. The error is less than 3%, and the root mean square error is less than 1%.

Key words: electric vehicles, battery, charge and discharge capacity, multi-step prediction method, long and short-term memory neural network, power correction