IEEE Access (Jan 2024)
Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art
Abstract
Lithium-ion (Li-ion) batteries are used in electric vehicles to reduce reliance on fossil fuels because of their high energy density, design flexibility, and efficiency compared to other battery technologies. However, they undergo complex nonlinear degradation and performance decline when abused, making their reliability crucial for effective electric vehicle performance. This survey paper presents a comprehensive review of state-of-the-art battery reliability assessments for electric vehicles. First, the operating principles of Li-ion batteries, their degradation patterns, and degradation models are briefly discussed. Subsequently, the reliability assessments of Li-ion batteries are detailed using both qualitative and quantitative approaches. The qualitative approach encompasses failure modes mechanisms and effects analysis, X-ray computed tomography, and scanning electron microscopy. In contrast, quantitative approaches involve multiphysics modelling, electrochemical impedance spectroscopy, incremental capacity and differential voltage analysis, machine learning, and transfer learning. Each technique is examined in terms of its principles, advantages, limitations, and applicability in Li-ion batteries for electric vehicles. Comparative analysis reveals that qualitative methods are primarily used in the early design stages to assess potential risks and in post-mortem battery analysis in the laboratory, whereas quantitative techniques such as machine learning and transfer learning offer real-time prognostic health management and anomaly prevention. Additionally, the quantitative techniques tend to be more cost-effective than their counterparts. The potential for consolidating reliability methods through standardization of testing protocols, real-world data integration, controller area network use, and policy regulation is highlighted to guide further research.
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