Expanding the Peukert equation for battery capacity modeling through inclusion of a temperature dependency

The accuracy of Peukert's equation for battery capacity lessens under dynamic loading and varying temperature conditions. Previous attempts by others endeavor to overcome the current shortfall; however, many still neglect the inclusion of a temperature dependency. This paper investigates the feasibility of Peukert's equation for practical automotive situations and expands upon the equation in order to include both variable current and temperature effects. The method proposed captures these requirements based on the theory that a battery contains a relative maximum absolute capacity, different from manufacturer 20-h specifications, and the specific discharge conditions determine the rate at which to remove this capacity. Experimental methods presented in the paper provide an economical testing procedure capable of producing the required coefficients in order to build a high-level, yet accurate state of charge prediction model. Finally, this work utilizes automotive grade lithium-based batteries for realistic outcomes in the electrified vehicle realm.

► The shortcomings of Peukert's battery capacity model are discussed.
► The need for a simplistic and accurate battery state of charge model is outlined.
► An efficient and capable test setup is demonstrated.
► The resulting model yields promising accuracy through minimal data requirements.