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

Abstract

AbstractAn 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, 100 Ah) used in an electric vehicle.