Parameter identification of Li-ion battery models is important for efficiently charge and discharge the most widely used energy storage devices. In this work, we propose a simplified battery model with a parameter identification method for time-domain charging and discharging. Staircase PotentioElectrochemical Impedance Spectroscopy technique (SPEIS) is chosen to characterize the batteries during charging and discharging cycles at different voltage steps values. Marine Predator Algorithm (MPA) is used to identify the proposed model parameters on two commercial Li-ion coin-shaped batteries. The proposed model shows very good matching with the experiments with absolute current error less than 10 4. Hence, the proposed model can be used for real-time applications to predict the battery’s behavior under different operating conditions. © 2021 IEEE.
On Fractional-order Capacitive Wireless Power Transfer System
Wireless power transfer is becoming an increasingly viable solution for the electrical powering of various electronic gadgets. However, precise outputs are not guaranteed with integer systems, so fractional-order capacitors are vital. This paper studies a four-plate fractional capacitive power transfer system by varying six orders of capacitors between the plates along with the load resistance. A mathematical model based on a 4× 4 mutual fractional capacitance matrix is established for equidistantly placed four identical metal plates. Moreover, the chosen circuit topology is identified and analyzed based on the proposed model. © 2022 IEEE.
Capacitive Power Transfer Modeling of Charging Inner-body Devices
Wireless power transfer (WPT) is highly desirable for applications with battery restrictions, such as biomedical applications. For example, in the case of implantable devices, power is transmitted through the human body, which has dielectric characteristics that must be considered during the design of the WPT system. This paper examines capacitive power transfer through the human body and formulates the complete WPT system, including the human body model. The power delivered to the implantable device is also analyzed. Finally, the system efficiency is discussed under different body and load scenarios to determine the optimal transmission frequency and load impedance. © 2023 IEEE.
Battery Modeling with Mittag-Leffler Function
In various areas of life, rechargeable lithium-ion batteries are the technology of choice. Equivalent circuit models are utilized extensively in characterizing and modeling energy storage systems. In real-time applications, several generic-based battery models are created to simulate the battery’s charging and discharging behavior more accurately. In this work, we present two generic battery models based on Mittag-Leffler function using a generic Standard battery model as a reference. These models are intended to fit the continuous discharging cycles of lithium-ion, Nickel-cadmium, and Nickel-metal hydride batteries, as well as one set from the NASA randomized battery usage dataset. We formulate the parameter identification as an optimization problem, solved with Marine Predator Algorithm. The optimized models show very good matching against the measured data. © 2024 IEEE.
Parameter Identification of Commercial Li-ion Batteries with Marine Predator Algorithm
The accurate identification of Li-ion battery models is important to ensure efficient and safe operating conditions
Parameter Identification of Li-ion Batteries: A Comparative Study
Lithium-ion batteries are crucial building stones in many applications. Therefore, modeling their behavior has become necessary in numerous fields, including heavyweight ones such as electric vehicles and plug-in hybrid electric vehicles, as well as lightweight ones like sensors and actuators. Generic models are in great demand for modeling the current change over time in real-time applications. This paper proposes seven dynamic models to simulate the behavior of lithium-ion batteries discharging. This was achieved using NASA room temperature random walk discharging datasets. The efficacy of these models in fitting different time-domain responses was tested through parameter identification with the Marine Predator Algorithm (MPA). In addition, each model’s term’s impact was analyzed to understand its effect on the fitted curve. The proposed models show an average absolute normalized error as low as (Formula presented.). © 2023 by the authors.