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The durability and reliability of battery management systems in electric vehicles to forecast the state of charge (SoC) is a tedious task. As the process of battery degradation is usually non-linear, it is extremely cumbersome work to predict SoC estimation with substantially less degradation. This paper presents the SoC estimation of lithium-ion battery systems using six machine learning algorithms for electric vehicles application. The employed algorithms are artificial neural network (ANN), support vector machine (SVM), linear regression (LR), Gaussian process regression (GPR), ensemble bagging (EBa), and ensemble boosting (EBo). Error analysis of the model is carried out to optimize the battery’s performance parameter. Finally, all six algorithms are compared using performance indices. ANN and GPR are found to be the best methods based on MSE and RMSE of (0.0004, 0.00170) and (0.023, 0.04118), respectively.

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This review describes the preparation of nonedible vegetable oil (NEVO)-based polyols and their application in anticorrosive and antimicrobial polyurethane (PU) coatings. PUs are a class of versatile polymers made up of polyols and isocyanates. Renewable vegetable oils are promising resources for the development of ecofriendly polyols and the corresponding PUs. Researchers are interested in NEVOs because they provide an alternative to critical global food issues. The cultivation of plant resources for NEVOs can also be popularized globally by utilizing marginal land or wastelands. Polyols can be prepared from NEVOs following different conversion routes, including esterification, etherification, amidation, ozonolysis, hydrogenation, hydroformylation, thio-ene, acrylation, and epoxidation. These polyols can be incorporated into the PU network for coating applications. Metal surface corrosion and microbial growth are severe problems that cause enormous economic losses annually. These problems can be overcome by NEVO-based PU coatings, incorporating functional ingredients such as corrosion inhibitors and antimicrobial agents. The preferred coatings have great potential in high performance, smart, and functional applications, including in biomedical fields, to cope with emerging threats such as COVID-19.

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