Modeling of one and two RC model and state estimation of Lithium-Ion Battery using Thevenin’s equivalent Circuit Model
The performance of Electric Vehicles (EVs) undergoes rapid changes over time. EVs are equipped with an Energy Storage System (ESS) consisting of a battery, controller, charger, BMS, and a dynamically designed vehicle. The performance of an EV primarily depends on the mentioned parameters. Researchers are keen on designing and developing rigid, efficient, and long-lasting vehicles. Within the ESS field, lithium-ion batteries are known for their extended lifespan, making battery model parameter estimation a crucial aspect of EVs. Currently, many scholars present great relation studies on equivalent circuit models (ECM) for ESS i.e Li-ion batteries. They are focus on the primarily order model with resistor and capacitor (RC) and the secondarily order model with RC, which are commonly used in thevenin’s model. This paper aims to simulate both I st and II nd order models with RC. MATLAB/Simulink software is utilized for simulation and analysis, providing insights into the correct evaluation of State of charge (SOC) and terminal voltage of the Energy Storage System in the cell (ESS). The paper concludes by presenting an accurate LIB model for thevenin’s model parameter estimation, comparing the outputs of both models and providing comments. The simulation methodology helps in identifying the best method for accurate SOC estimation and analyzing the diferences between conventional and computational methods under various operating conditions.
Authors
- Arvind S. Pande (ORCID: https://orcid.org/0000-0003-3358-9109)
- Ankit Kumar Sharma (ORCID: https://orcid.org/0000-0002-3569-5047)
- Bhanu Pratap Soni (ORCID: https://orcid.org/0000-0001-8138-5392)
Institutions
- University of Engineering & Management (IN)
- Fiji National University (FJ)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procs.2025.03.351
- Citations
- 6
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 4.10