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The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO 2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO 2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO 2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO 2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy. • A battery pack use-phase carbon footprint assessment strategy is proposed. • The carbon emissions for four battery pack subsystems are calculated. • Temperature has the greatest impact on the battery pack carbon emissions. [ABSTRACT FROM AUTHOR]

Safety risk assessment is essential for evaluating the health status and averting sudden battery failures in electric vehicles. This study introduces a novel safety risk assessment approach for battery systems, addressing both cell and pack levels with three key indexes. The core of the assessment lies in representing the relative deviation of cell voltages through scatter diagrams across various stages of service life. Specifically, the study quantifies voltage deviations and deviation angles within different state of charge intervals to gauge safety risks at the cell level. Leveraging clustering algorithms aids in identifying outlier values. Furthermore, the dispersion of scatter points is utilized to assess safety risks at the pack level. Validation of this proposed model is conducted through cycling tests on battery modules with a deformed cell, demonstrating its efficacy in capturing inconsistent features of mechanical deformation abuse across the three indexes, thereby triggering alarms during operation. Moreover, the method is applied to assess the safety risks of five hazardous and accident-prone vehicles, enabling comprehensive evaluation of potential faulty cells and safety risks at the pack level. This proposed approach offers a fresh perspective on the comprehensive safety risk assessment of battery systems. [ABSTRACT FROM AUTHOR]

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]