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@article{205390,
        author = {Padmaja Gulhane},
        title = {Analytical Modeling of Electric Vehicle Battery Systems and Global Supply Chain Resilience using the Laplace-Weierstrass Transform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {6130-6135},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205390},
        abstract = {The Laplace-Weierstrass (LW) transform combines the Laplace transform with Gaussian smoothing to solve dynamic systems involving temporal evolution and regularization. Building on the 2013 foundational work, this paper introduces key extensions including an inversion outline, convolution theorem, fractional-order operators, and numerical implementation strategies. These advances enable efficient analytical treatment of differential and integro-differential equations with inherent noise handling.
The framework is applied to lithium-ion battery modeling and electric vehicle power systems, supporting parameter estimation, state-of-charge analysis, and hybrid architecture design. It is further demonstrated in resilient supply chain modeling, where it facilitates disruption analysis, inventory dynamics under delay, and bullwhip mitigation. By bridging rigorous transform theory with practical challenges in automotive batteries and global supply chains, the LW transform provides a versatile new analytical tool for researchers and engineers. Future directions include integration with quantum-inspired optimization for logistics.},
        keywords = {Laplace-Weierstrass transform; lithium-ion battery modeling; electric vehicle battery systems; supply chain resilience; operational calculus; analytical framework; disruptions; hybrid electric vehicles.},
        month = {June},
        }