Abstract
Lithium-ion batteries are indispensable in various applications owing to their high specific energy and long service life. Lithium-ion battery models are used for investigating the behavior of the battery and enabling power control in applications. The Doyle-Fuller-Newman (DFN) model is a popular electrochemistry-based model, which characterizes the dynamics in the battery through diffusions in solid and electrolyte and predicts current/voltage response. However, the DFN model contains a large number of parameters that need to be estimated to obtain an accurate battery model. In this paper, a computationally feasible two-step estimation approach is proposed that only uses voltage and current measurements of the battery under consideration. In the two-step procedure, the parameters are divided into 2 groups. The first group contains thermodynamic parameters, which are estimated using low-current discharges, while the second group contains kinetic parameters, which are estimated using a well-designed highly-dynamic pulse (dis-)charge current. A parameter sensitivity analysis is done to find a subset of parameters that can be reliably estimated using current and voltage measurements only. Experimental data are collected for 12 Ah nickel cobalt aluminum pouch lithium-ion cell. The voltage predictions of the identified model are compared with several experimental data sets to validate the model. A root mean square error between model predictions and experimental data smaller than 16 mV is achieved.
Highlights
Lithium-ion (Li-ion) batteries are known to have a high energy density and a long service life. They have been successfully used in the automotive industry, which enables the production of low-emission hybrid vehicles and zero-emission full electric vehicles.[1,2]
The equivalent circuit model (ECM) describes the input/output behavior of batteries through an electrical circuit consisting of a voltage source, a series resistance and a parallel connection of a resistor and capacitor, see, eg, Liaw et al,[8] while the DFN model is an electrochemistry-based model, which characterizes the dynamics in Li-ion battery based on concentrations and potentials.[9,10]
The thermodynamic parameters describe the system in equilibrium, when all concentration profiles and potentials are stable over the time and all net reaction currents are zero
Summary
Lithium-ion (Li-ion) batteries are known to have a high energy density and a long service life They have been successfully used in the automotive industry, which enables the production of low-emission hybrid vehicles and zero-emission full electric vehicles.[1,2] To facilitate the analysis, design and control of the batteries, models of Li-ion batteries are required. Ing the designed current input to the model and measuring the experimental voltage of the battery, the DFN model is parameterized through the estimation of the sensitive parameters using nonlinear least-square optimization.[23,24] The estimated model is validated by comparing the predictions of model to the measurements on different data sets so as to ensure the model is reliable.
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