Next-generation electrified powertrain technologies for sustainable mobility: A systematic review of architectures, intelligent control, energy storage, and grid integration
The global imperative to decarbonise road transport has required the automotive and energy sectors to reconceptualise vehicular powertrain engineering across all scales, from atomic-level electrochemistry to fleet-level grid interaction. This PRISMA-compliant systematic review synthesises 120 peer-reviewed publications, standards, and archival documents identified from a four-database search covering January 2018 to June 2026 (1204 records identified; 847 screened; 120 included). Four interconnected technology frontiers are examined in depth: (i) advanced vehicle architectures spanning Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), Plug-in Hybrid Electric Vehicles (PHEVs), and Fuel Cell Electric Vehicles (FCEVs), including distributed propulsion with active torque vectoring, in-wheel motors, and grid-connected renewable-source integration; (ii) next-generation electrochemical energy storage covering solid-state, sodium-ion, and lithium–sulfur batteries alongside hybrid supercapacitor architectures, with critical appraisal of conflicting experimental findings on dendrite formation, sodium storage mechanisms, and commercialisation timelines; (iii) intelligent Energy Management Systems (EMS) spanning rule-based control, Equivalent Consumption Minimisation Strategy (ECMS), Model Predictive Control (MPC), the full spectrum of Sliding Mode Control (SMC) variants including super-twisting second-order SMC with adaptive gain laws, Deep Reinforcement Learning (DRL), and physics-informed neural networks (PINNs); and (iv) grid-interactive infrastructure encompassing Vehicle-to-Grid (V2G) systems, wireless power transfer under SAE J2954, and cloud–edge digital twin frameworks with federated learning and cybersecurity provisions. Wide-bandgap SiC and GaN power electronics and six thermal management strategies are analysed as cross-cutting enablers. All quantitative comparison figures in this review (Figs. 13–27) are illustrative reconstructions digitised from data reported in the cited primary literature; they are not independently simulated results, and no new experimental or simulation data are reported in this work. A bibliometric analysis of the 120 included studies reveals growth from 8 papers (2018) to 35 papers (2025). A four-criterion quality assessment framework grades each reviewed technology. A structured technology readiness roadmap with 2030 quantitative projections derived from learning-rate battery cost models and IEA fleet scenarios projects battery costs of $55–70/kWh, SiC penetration of 80–95% in premium BEV inverters, and V2G participation of 8–20% of the EU passenger fleet. These are scenario projections carrying explicitly stated model assumptions and uncertainty ranges, not forecasts; the accompanying sensitivity analysis ( Section 12.1 ) identifies the learning rate and the cumulative-deployment trajectory as the dominant drivers, and a demonstrated-versus-projected classification is applied throughout to separate laboratory or pilot evidence from extrapolation.