Simple parameterization method using differential evolution algorithm to estimate state of charge for Li-ion batteries and packs for electric vehicles

An accurate method is proposed to measure the electrical parameters describing the experimental charge-discharge curves of Li-ion batteries and a pack through an equivalent electric dynamic model based on heuristic optimization algorithms (eg, differential evolution approach). The accuracy of these parameters is critical for on-board state of charge and Health (SOH) estimations of numerous applications and devices. The procedure is constructed, based on the simple Thévenin electrical model. Charge-discharge experimental curves collected for different chemistry and capacity batteries are described with the model, revealing better estimation results with respect to other algorithms such as impedance-based methodologies (decreasing the error until 64.19%) and particle swarm optimization based approaches (decreasing the error until 94.02%). The proposal was assessed with different chemistries, capacities and with a 28 battery pack (LiFeMnPO (Formula presented.), 100 Ah) used in an electric vehicle.