Simulation and Validation of a Battery Charging Model Using Dymola: A Case Study with Tata Nexon EV

Abstract: The document presents a comprehensive study on the modeling and simulation of battery management systems (BMS) using Dymola, focusing on electric vehicle (EV) applications. It explores the behavior of two battery models with differing complexities: a simplified model with linear state-of-charge (SOC) dynamics and an advanced model incorporating real-world effects such as transient responses, self-discharge, and RC (resistor-capacitor) network dynamics. The detailed model simulates non-linear SOC-open-circuit voltage (OCV) relationships, energy losses, and thermal effects, offering insights into battery performance under varying operating conditions.

The research compares charge-discharge cycles with a focus on transient voltage behavior, internal resistance energy losses, and thermal considerations. Significant measurements like SOC development, energy efficiency, and thermal stability are compared, citing the influence of design factors such as pulse currents, self-discharge rates, and RC values. The results highlight the necessity of advanced model approaches for the optimization of battery systems in electric vehicles to achieve working efficiency, safety, and durability. This project showcases Dymola's ability to simulate multidomain systems properly, connecting theoretical modeling and real-world applications in contemporary energy storage devices

Battery Management System (BMS), State of Charge (SOC), Open Circuit Voltage (OCV), RC Network Dynamics, Self-Discharge Modeling, Dymola Simulation, Energy Efficiency, Thermal

1. Dassault Systèmes, Dymola Documentation: Introduction to Dynamic Modelling with Modelica, 2021. [Google Scholar] [Crossref]

2. A. Kumar and S. Verma, “Dynamic Modeling of Batteries for Simulation and Optimization,” Journal of Power Sources, vol. 320, pp. 45–53, 2020. [Google Scholar] [Crossref]

3. Tata Motors, Tata Nexon EV Specifications. [Online]. Available: https://www.tatamotors.com [Google Scholar] [Crossref]

4. M. Sharma, R. K. Gupta, and V. Arora, “State of Charge Estimation Methods: A Review,” Renewable and Sustainable Energy Reviews, vol. 104, pp. 113–126, 2019. [Google Scholar] [Crossref]

5. J. Lee and D. Kim, “Energy Efficiency in Battery Charge and Discharge Cycles,” IEEE Transactions on Energy Conversion, vol. 35, no. 4, pp. 1507–1516, 2020. [Google Scholar] [Crossref]

6. L. Wang and F. Zhao, “The Effect of OCV-SOC Relationships on Battery Performance,” Electrochimica Acta, vol. 295, pp. 867–876, 2018. [Google Scholar] [Crossref]

7. S. Patel and R. Singh, “Laboratory Framework for Modelica-Based Tools,” IEEE Access, vol. 10, pp. 11234–11242, 2022. [Google Scholar] [Crossref]

8. T. Nair and A. Bhosale, “Advanced Battery Modelling Techniques in Dymola,” in Proc. IEEE Conf., 2019, pp. 123–130. [Google Scholar] [Crossref]

9. J. Dalby, M. Woodburn, A. Thomas, and R. Green, “Hybrid Powertrain Technology Assessment through an Integrated Simulation Approach,” SAE Technical Paper 2019-24-0198, 2019, doi: 10.4271/2019-24-0198. [Google Scholar] [Crossref]

10. E. Apostolaki-Iosifidou, W. Kempton, and A. F. Shuba, “Measurement of Power Loss During EV Charging and Discharging,” Energy, vol. 127, pp. 730–742, 2017. [Google Scholar] [Crossref]

11. A. G. Boulanger, A. C. Chu, S. Maxx, and D. L. Waltz, “Vehicle Electrification: Status and Issues,” Proceedings of the IEEE, vol. 99, no. 6, pp. 1116–1138, Jun. 2011. [Google Scholar] [Crossref]

12. H. El-Bayeh, M. H. Saad, and T. Barakat, “A Novel Wave Spring Energy Absorber for Impact Applications,” Journal of Mechanical Science and Technology, vol. 35, no. 4, pp. 1737–1747, 2021. [Google Scholar] [Crossref]

13. Y. He, M. Lu, and K. Liu, “Sustainability Impact of Remanufacturing: A Life Cycle Assessment Perspective,” Journal of Cleaner Production, vol. 33, pp. 261–273, 2012. [Google Scholar] [Crossref]

14. K. He, Z. Zhang, and X. Li, “Multi-Objective Optimization of PEM Fuel Cells Using NSGA-II,” International Journal of Hydrogen Energy, vol. 37, no. 5, pp. 4390–4402, 2012. [Google Scholar] [Crossref]

15. M. Brückner, M. Hesse, and D. U. Sauer, “Battery Safety and Reliability in Electric Vehicles,” Journal of Energy Storage, vol. 32, 101756, 2020. [Google Scholar] [Crossref]

• Exploring the Concept of Generative Artificial Intelligence: A Narrative Review
• Design, Development, and Evaluation of a Critiquing-Based Mobile-Web Employment Recommender System
• Integrating Bhagavad Gita Principles with Modern Supply Chain Management: A Framework for Ethical and Resilient Operations
• Soilless Indoor Farming: A Systematic Review of Iot-Based Monitoring Systems and Physiochemical Characterization Methods for Lactuca Sativa
• Financial Awareness: A Survey of Students in Bhopal