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The studies on an integrated approach for the battery (cell level), battery pack (system level) and battery pack enclosure (system level) are nascent till date. The present work proposes a combined approach for studying the coupled electrochemical-mechanical performance of the battery (cell level), battery pack and enclosure (system level). In this context, five research problems are undertaken involving the design parameters for the performance evaluation of batteries. The first issue undertaken is battery performance under stress conditions and for that varying initial stress and real-time stresses were applied, and variation in the capacity of the battery packs was studied. Initial stress was found to be in negative relation with the battery capacity. For understanding the mechanical damage (leakage, deformation, etc.), characterization of the battery cell under impact loading was done by subjecting battery cells to different impact loads and impact analysis was done using six statistical features extracted from the impact force processed signal of each test, namely: peak value, mean value, variance, skewness, kurtosis and pulse width. The third issue regards the manufacturing defects in the cell, which can potentially lead to inconsistency of cells performance in a pack and thus lower its total cycle life. Support vector classification clustering methods were applied to form a battery pack with similar performing cells and performance of the pack was compared with industrial packs in which earlier one was found to be better. The fourth research challenge involved the mechanical performance parameters such as strength, deformation, and natural frequency, which, in addition to temperature, are also critical to battery pack safety in the event of impact and vibrations under driving conditions. ANSIS and NSGA-II based approaches were used to optimize the battery design and resultant device shown maximum deformation reduced by 22.2%, the value of minimum inherent frequency improved by 3.2% and the value of mass decreased by 11.6%. The fifth research problem highlighted how, due to the enormous production of electric vehicles, by 2020, there will be 250,000 tons of batteries that need to be recycled. A combined experimental-numerical framework has been thereby suggested to mitigate it. The study resulted in the formation of an online monitoring system and safety design of batteries at both cell and system level (pack and enclosure). [ABSTRACT FROM AUTHOR]

State-of-health (SOH) monitoring of lithium-ion batteries plays a key role in the reliable and safe operation of battery systems. Influenced by multiple factors, SOH is an aging path-dependent parameter, which challenges its accurate estimation and prediction. Numerous methods have been proposed for lithium-ion batteries SOH diagnostics and prognostics, but there is little discussion on how to characterize SOH. In this paper, we first review the existing characteristic parameters in defining battery SOH at cell-level and pack-level, and then propose some suggestions for SOH definitions. The impact of external influencing factors on battery degradation is introduced to lay a foundation for SOH estimation. SOH estimation methods are categorized by the parameters used to define SOH, i.e. capacity, impedance and aging-mechanism parameters. We discuss the goals of SOH monitoring and summarize its applications from short- and long-term perspectives accordingly. Finally, the challenges and future trends of battery SOH diagnostics and prognostics are thoroughly analyzed and discussed, in order to provide a comprehensive understanding for researchers and technologists. • Discuss how to comprehensively characterize battery SOH at cell-level and pack-level. • Analyze the strengths and weaknesses of the SOH estimation methods from the perspective of data acquisition sources. • Present the gaps between existing research on SOH estimations and SOH applications. • Summarize the challenges and prospects for SOH characterizations, estimations and applications. [ABSTRACT FROM AUTHOR]