Parameter estimation of lithium-ion batteries dynamic model based on water cycle algorithm

Lithium Ion batteries are widely used in electric propulsion systems as electric and hybrid electric vehicles and in many other electrical devices as well. This is why it is important to accurately model this type of batteries. The modified shepherd model, which shows the electrochemical action of the battery, is constructed. This model is valid for both charge and discharge modes of the battery operation. The five unknown parameters of the model are obtained using only three points of the battery discharge curve at a certain discharge current based on water cycle algorithm (WCA). To ensure the accuracy of WCA, the results are compared with other optimization methods of Particle Swarm Optimization (PSO), Ant Lion Optimizer (ALO), Gray Wolf Optimizer (GWO) and Teaching Learning Based Optimizer (TLBO). A good agreement between the results obtained by all methods and the data sheet readings at different discharge current is obtained. This agreement validates the accuracy of the obtained battery model.