Electrified transport and digitally instrumented logistics are converging on a common engineering problem: how to size, operate, and recover energy and material flows under uncertainty. This review synthesizes recent work on plug-in hybrid battery sizing, automotive and electric-vehicle cell chemistries and management systems, intelligent transportation architectures, solar-assisted hybrid vehicle design, multi-scale spectral analysis of hybrid-vehicle and supply-chain dynamics, quantum computing for transportation and unit-load configuration, artificial intelligence and blockchain for green and transparent logistics, digital twins for adaptive global chains, and resilience frameworks for internally and externally disrupted networks. Classical two-port and time-shift properties of the FKF transform are recalled only where they supply a linear operator for delayed demand signals. The paper does not claim new laboratory measurements; it organizes published engineering arguments, writes the governing energy and optimization relations in professional mathematical form, and maps each theme to the literature in which that theme was developed. Across domains the same pattern appears: usable energy is a constrained fraction of nameplate capacity; mobility service quality depends on multimodal assignment rather than vehicle count alone; resilience is the integral of lost performance after a shock; and emerging quantum and twin platforms are decision aids, not replacements for validated physical models.

Keywords: electric vehicle batteries; plug-in hybrid sizing; smart mobility; solar-assisted vehicles; supply-chain resilience; digital twins; quantum logistics; FKF transform; green logistics