Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level


Year : 2024 | Volume : 02 | Issue : 02 | Page : 1-24
    By

    Kamlesh Mahajan,

  • Ravikant Nanwatkar,

  • Shubham Tonde,

  • Parth Sawardekar,

  • Shaikh Aatif,

  1. , Department of Mechanical Engineering, STES’s NBNSTIC, Ambegaon, Pune, India
  2. Assistant Professor, Department of Mechanical Engineering, STES’s NBNSTIC, Ambegaon, Pune, India
  3. , Department of Mechanical Engineering, STES’s NBNSTIC, Ambegaon, Pune, India
  4. , Department of Mechanical Engineering, STES’s NBNSTIC, Ambegaon, Pune, India
  5. , Department of Mechanical Engineering, STES’s NBNSTIC, Ambegaon, Pune, India

Abstract

Lithium-ion batteries play a crucial role in contemporary technology, serving as the power source for everything from consumer gadgets to electric vehicles. However, their safety and longevity are significant influenced by the reperformance under extreme conditions, commonly referred to as ab use testing .This paper explores the simulation and analysis of ab use testing and life cycle prediction for lithium-ion batteries at both the cell and pack levels. Abuse testing evaluates how batteries react to severe conditions such as overcharging, thermal stress, short-circuiting, and mechanical impacts. These evaluations are essential for detecting possible failure mechanisms and ensuring adherence to safety regulations. We employ various simulation techniques, including Finite Element Analysis (FEA) for mechanical and thermal behavior, electrochemical models for internal reactions, and the mal mode ling for predicting thermal run away scenarios. Our analysis extends to life cycle prediction, which involves understanding battery degradation mechanisms through cycle life testing and predictive analytics. By examining factors such as electrode material degradation and electrolyte break down, we can for e cast battery performance and long levity .The integration of advanced  simulation tools and predictive models facilitates the design of safer and more reliable battery systems. It also supports performance optimization and ensures regulatory compliance. Future developments, including the application of machine learning and real-time monitoring technologies, promise to further enhance our ability to predict and improve battery life and safety. This study under scores the importance of comprehensive simulation and analysis in advancing lithium-ion battery technology, aiming to contribute to more efficient, safe, and durable energy storage solutions.

Keywords: Lithium-ion batteries,abuse testing, life cycle prediction, lithium-ion batteries, battery degradation

[This article belongs to International Journal of Mechanical Dynamics and Systems Analysis ]

How to cite this article:
Kamlesh Mahajan, Ravikant Nanwatkar, Shubham Tonde, Parth Sawardekar, Shaikh Aatif. Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level. International Journal of Mechanical Dynamics and Systems Analysis. 2024; 02(02):1-24.
How to cite this URL:
Kamlesh Mahajan, Ravikant Nanwatkar, Shubham Tonde, Parth Sawardekar, Shaikh Aatif. Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level. International Journal of Mechanical Dynamics and Systems Analysis. 2024; 02(02):1-24. Available from: https://journals.stmjournals.com/ijmdsa/article=2024/view=191844


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Regular Issue Subscription Original Research
Volume 02
Issue 02
Received 10/12/2024
Accepted 11/12/2024
Published 31/12/2024
Total Visits: 74


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