This review discusses the mechanisms and estimation methods of lithium-ion battery ageing in automotive applications. Lithium-ion batteries are widely used in vehicles due to their high energy density and performance. However, battery ageing significantly affects their performance and lifespan, with degradation occurring throughout the battery's life, even when not in use. Ageing is influenced by various factors, including temperature, state of charge (SOC), and usage conditions, leading to capacity fade and increased resistance. Understanding and estimating battery ageing is crucial for improving battery performance and longevity in automotive applications. The paper reviews various aspects of battery ageing, including electrochemical and statistical methods used to estimate battery state of health (SOH) and remaining useful life (RUL). Electrochemical models, equivalent circuit models, and performance-based models are discussed, along with analytical models and statistical approaches. These methods aim to quantify battery degradation and predict its future performance. The paper highlights the complexity of battery ageing, which is influenced by multiple factors and interactions. Calendar ageing, related to storage conditions, and cycle ageing, related to usage, are both important aspects of battery degradation. The paper also discusses the challenges in estimating battery ageing, including the need for large datasets, the impact of environmental conditions, and the difficulty in accurately predicting degradation. The review concludes that battery ageing estimation remains a challenging task, requiring a balance between accuracy and real-time performance. Current methods have limitations, and further research is needed to develop more effective and accurate estimation techniques for lithium-ion batteries in automotive applications. The paper emphasizes the importance of understanding battery ageing mechanisms and developing robust estimation methods to improve battery performance and longevity in electric vehicles.This review discusses the mechanisms and estimation methods of lithium-ion battery ageing in automotive applications. Lithium-ion batteries are widely used in vehicles due to their high energy density and performance. However, battery ageing significantly affects their performance and lifespan, with degradation occurring throughout the battery's life, even when not in use. Ageing is influenced by various factors, including temperature, state of charge (SOC), and usage conditions, leading to capacity fade and increased resistance. Understanding and estimating battery ageing is crucial for improving battery performance and longevity in automotive applications. The paper reviews various aspects of battery ageing, including electrochemical and statistical methods used to estimate battery state of health (SOH) and remaining useful life (RUL). Electrochemical models, equivalent circuit models, and performance-based models are discussed, along with analytical models and statistical approaches. These methods aim to quantify battery degradation and predict its future performance. The paper highlights the complexity of battery ageing, which is influenced by multiple factors and interactions. Calendar ageing, related to storage conditions, and cycle ageing, related to usage, are both important aspects of battery degradation. The paper also discusses the challenges in estimating battery ageing, including the need for large datasets, the impact of environmental conditions, and the difficulty in accurately predicting degradation. The review concludes that battery ageing estimation remains a challenging task, requiring a balance between accuracy and real-time performance. Current methods have limitations, and further research is needed to develop more effective and accurate estimation techniques for lithium-ion batteries in automotive applications. The paper emphasizes the importance of understanding battery ageing mechanisms and developing robust estimation methods to improve battery performance and longevity in electric vehicles.