An SOC and SOP Joint Estimation Method of Lithium-ion Batteries in Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are widely used in industry and military scenarios due to the advantages of low-cost. For drones using lithium-ion batteries as the energy storage component, accurate state estimation plays an important role in the properly decision making and safely control and maintenance. However, under dynamic operating conditions, only one state is often estimated, in fact there is often a certain correlation between each state, ignoring this will lead to inaccurate estimation results. To address these challenging issues, this paper proposes a joint estimation method for lithium-ion battery’s state-of-charge (SOC) and state-of-power (SOP). Firstly, a method based on Long Short-Term Memory (LSTM) is used to predict the SOC of lithium batteries. There is no need to build a complex battery model. Based on the prediction results, according to the coupling relationship between SOC and SOP, the multi-parameter constraint method is used to obtain the estimated SOP value in a period of time. The experiment was conducted based on the battery simulation data. The results based on the lithium-ion battery simulation data show that the method used in this paper can accurately predict the battery SOC and SOP state parameters.