IJCOPE Journal

UGC Logo DOI / ISO Logo

International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
Journal Information
ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 03

Published on: March 2026 2026

INTEGRATING BATTERY AGING IN THE OPTIMIZATION FOR BIDIRECTIONAL CHARGING OF ELECTRIC VEHICLES

S.Bharath kalyan K.Jayaprakash S. Prasanth T.Mahandhraselvan

S.Naveena

Department of Electrical and Electronics Engineering Jayalakshmi Institute of Technology-Thoppur
DOI:https://doi.org/10.55041/ijcope.v2i3.248

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Download PDF Review Report

Abstract

Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles The increasing adoption of electric vehicles (EVs) and their integration into smart grids have enabled bidirectional charging technologies, commonly referred to as Vehicle-to-Grid (V2G) systems. While V2G offers significant benefits such as grid stability, peak load management, and renewable energy integration, it also accelerates battery degradation due to frequent charge– discharge cycles. This study focuses on integrating battery aging considerations into the optimization framework for bidirectional EV charging. A comprehensive battery degradation model is incorporated, accounting for key factors such as depth of discharge, state of charge, temperature, and cycle frequency. The proposed optimization approach aims to balance economic benefits from energy trading with the long-term cost associated with battery wear. Advanced algorithms are employed to determine optimal charging and discharging schedules that minimize degradation while maximizing grid support and user profit. Simulation results demonstrate that incorporating battery aging into the optimization process significantly improves battery lifespan and ensures sustainable operation without compromising grid services. The findings highlight the importance of degradation-aware strategies in enhancing the efficiency, reliability, and economic viability of V2G-enabled electric vehicle systems.

How to Cite this Paper

kalyan, S., K.Jayaprakash, , Prasanth, S. & T.Mahandhraselvan, (2026). Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(03). https://doi.org/10.55041/ijcope.v2i3.248

kalyan, S.Bharath, et al.. "Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i3.248.

kalyan, S.Bharath, K.Jayaprakash,S. Prasanth, and T.Mahandhraselvan. "Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles." International Journal of Creative and Open Research in Engineering and Management 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i3.248.

Search & Index

Google Scholar Crossref DOI ResearchGate

References


  1. Zhao, , Kong, S., Bo, B., Li, X., Hao, L., Xu, F.,  &  Chen,  L.  (2025).Research on battery aging and user revenue of electric vehicles in V2G scenarios.Electronics, 14(23), 4567.Develops integrated aging and economic models for V2G



  1. Lehtola,(2025). Vehicle-to-grid applications and battery cycleaging:A review. Renewable and Sustainable Energy Reviews, 208.Comprehensive review on battery aging impact in V2G systems.

  2. Chen,J., et (2025). V2G grid optimization with battery state- of-health based     incentives. Energies, 18(24), 6450.Proposes SOH-based optimization and incentive

  3. Mallick, , Pantazis, G., Khosravi, M., Esfahani, P., & Grammatico, S. (2025). User-centric V2G optimization with neural network-based battery degradation model.Introduces AI-based degradation- aware optimization.



  1. Popolizio, , Wik, T., Lee, C. F., & Zou, C.(2025).Nonlinear online optimization for V2H– V2G systems with battery degradation.Combines real-time optimization and degradation modeling.



  1. Nnorom , O., Ogut, G., Boyd, S., & Levis, P.   (2025). Aging-aware battery control via convex optimization.Focuses on               balancing performance and battery



  1. Zhong, C., Ma, Q., Ren, M., & Xiong, L. (2026).  Optimization framework for battery health management in V2G systems. Scientific Reports.Uses transformer-based models for degradation prediction.



  1. Lee, C. F., et al. (2023/2025 relevance). Vehicle-to-grid optimization considering battery aging.IFAC-PapersOnLine.Demonstrates aging-aware scheduling improves performance.



  1. Preis, V., et al. (2023–2025 relevance). Battery degradation modeling in V2G optimization.Energy Informatics.Compares throughput-based and performance-based aging



  1. Chalmers University Research (2025). Optimal V2G scheduling with calendar and cycle aging.Uses MILP-based optimization including degradation effects.

Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Apr 01 2026
CCBYNC

This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

View License
Back to Volume 02, Issue 03View All Issues Next Article

← Previous Article

Indigenous Leadership and Its Role in Anglo-Sirmaur Relations

Next Article →

Integrating Ethical Standards in AI-Driven Physical Education: Challenges and Opportunities in School Settings
Scroll to Top