Electric Road Systems: Infrastructure & Applications

Updated 21 December 2025

Electric Road Systems are infrastructures that deliver grid electricity in-motion using conductive and inductive technologies, reducing stationary charging needs.
They employ fixed installations like overhead catenaries and inductive in-road coils, as well as mobile energy disseminators, to optimize power transfer.
ERS deployments integrate traffic-aware grid sizing and dynamic routing optimization to cut operational costs and enhance urban mobility.

An Electric Road System (ERS) is a roadway infrastructure that supplies grid electricity directly to compatible vehicles in motion, enabling traction and/or battery charging while eliminating or reducing stationary charging requirements. ERSs include fixed installations—overhead catenaries, in-road conductive rails, or inductive coils—and, in some schemes, mobile energy disseminators fitted on public vehicles. ERSs are deployed to support the electrification of fleet, freight, and passenger transport, with substantial implications for energy modeling, power systems, economics, traffic management, and logistics (Gutierrez-Alcoba et al., 2022, Agnihotri et al., 14 Dec 2025, Llanes-Estrada et al., 2010, Gupta et al., 25 Nov 2025, Gupta et al., 2 Sep 2025, Kosmanos et al., 2017, Nguyen et al., 2022, Wang et al., 2019, Gaete-Morales et al., 2023, Ghose et al., 2 Nov 2025, Nakanishi et al., 11 Feb 2024).

1. Technology Fundamentals and Architectures

Electric Road Systems implement various power delivery modalities:

Conductive Overhead Catenary & Rail: Overhead lines or rails supply DC or AC power to vehicles via pantograph or pick-up arm (e.g., 3 kV DC at ~50–400 kW/vehicle, used for heavy-duty vehicles and buses) (Llanes-Estrada et al., 2010, Gaete-Morales et al., 2023).
Inductive In-Road Coils (Dynamic Wireless Power Transfer – DWPT): Modular coils (2–5 m segments, spaced at ~10 m) embedded into pavement transfer energy via magnetic resonance to vehicle receiver pads. Realized system efficiency is typically 75–90% (including inverter and coil losses); segment activation is event-driven for loss minimization (Agnihotri et al., 14 Dec 2025, Gupta et al., 25 Nov 2025).
Mobile Energy Disseminators (Editor's term): Fleet vehicles (e.g., buses, trucks) equipped with large batteries and inductive transmitters form moving charging stations, enabling dynamic wireless charging by trailing EVs through near-field coupling at rates of 20–50 kW (Kosmanos et al., 2017).

Onboard equipment varies by approach and use case. In typical ERS implementations, vehicles carry a moderate-size Li-ion traction battery (e.g., 3–200 kWh) and power electronics for seamless transfer between grid power, battery, and/or internal combustion engine (in hybrid vehicles) (Gutierrez-Alcoba et al., 2022, Gaete-Morales et al., 2023). The ERS interface ensures safe, automatic connection/disconnection during lane changes or transit interruptions (Llanes-Estrada et al., 2010).

The ERS is underpinned by supporting road-side infrastructure—power converters, smart metering, wireless or PLC billing, V2I/IoT communications, and real-time energy management systems integrating renewables and grid balancing (Agnihotri et al., 14 Dec 2025).

2. Energy Transfer Modeling and Power System Considerations

The power drawn by a vehicle on ERS is a nonstationary function of vehicle mass, speed, traction demand, and (for DWPT) spatial overlap of vehicle receiver and road transmitter coils (Gutierrez-Alcoba et al., 2022, Gupta et al., 25 Nov 2025, Gupta et al., 2 Sep 2025).

Conductive ERS: Mechanical power requirement per arc (i, j) is

$P_{ij} = M g \sin \theta_{ij}\,v_{ij} + \frac{1}{2} C_dA\,\rho v_{ij}^3 + M g C_r \cos \theta_{ij}\,v_{ij}$

Energy draw $r_{ij}(M)$ is mass-dependent and decomposed into $(\alpha_{ij}M+\beta_{ij})$ components (Gutierrez-Alcoba et al., 2022).

Inductive DWPT: The instantaneous load of an EV traversing periodic coil segments is a trapezoidal pulse train; its fundamental frequency is $f_0 = v/D$ $f_{0} = v / D$ (with $D=$ $D =$ spatial period, $v=$ $v =$ speed). The aggregate ERS load is characterized by harmonics whose amplitude and frequency content depend on vehicle phasing, platooning, and speed dispersion:
- Synchronized traffic: Harmonic amplitudes scale as $N$ (number of EVs).
- Free flow traffic: Amplitudes scale as $\sqrt{N}$ ; speed variance broadens harmonics into bands.
- Platoons: Harmonics scale as $\sqrt{QN}$ for platoon size $Q$ .
- Harmonics can occupy sub-2 Hz lattice, with potential to excite inter-area grid oscillations if not designed accordingly (Gupta et al., 2 Sep 2025, Gupta et al., 25 Nov 2025).

Design recommendations for grid integration include sizing substation and buffer storage to absorb harmonic content (up to 30% of DC load), dynamic control to avoid synchronism peaks, and randomized entry/coil patterns to smooth aggregate spectrum (Gupta et al., 25 Nov 2025, Gupta et al., 2 Sep 2025). Voltage stability analyses using radial feeder and continuation power flow models identify maximum feasible road length ( $L_{max}$ ) or vehicle number ( $N_{max}$ ) before voltage collapse, with critical dependencies on feeder impedance, vehicle charge, and local compensation (Wang et al., 2019).

3. Operational Optimization and Logistics

ERS fundamentally alters vehicle routing, inventory management, and operational costs, especially for freight and delivery systems (Gutierrez-Alcoba et al., 2022).

Electric Roads Routing Problem (ERRP): Integrates mass-dependent energy cost modeling, spatiotemporal routing, battery SOC, and delivery planning. The objective minimizes the sum of energy (electric/fuel) cost plus inventory-out penalty for lost sales. The ERRP is formulated as a mixed-integer linear program (MILP) and solved via stochastic dynamic programming (SDP) or heuristic rolling-horizon MILP (Gutierrez-Alcoba et al., 2022).
Fleet Routing in Hybrid Heavy Goods Vehicles: Hybrid HGVs exploit ERS-equipped arcs to operate in least-cost mode, balancing grid (C^e) and fuel (C^f) pricing and strategic battery charging. Optimal routing seeks “ERS-rich loops” when $C^f \gg C^e$ and may forgo deliveries if the penalty cost $p$ for lost sales is low.
Dynamic Wireless Charging with Mobile Energy Disseminators: MED-based eco-routing combines inter-vehicle communication (VANET) and constraint programming to optimize rendezvous, reducing average travel time and range anxiety compared to static-charging alternatives (Kosmanos et al., 2017).

4. Large-Scale Deployment: Planning, Grid, and Urban Integration

ERS deployment at scale requires traffic-aware grid planning, integration with urban mobility, and consideration of capital and operational expenditure (Agnihotri et al., 14 Dec 2025, Ghose et al., 2 Nov 2025, Llanes-Estrada et al., 2010, Nguyen et al., 2022).

Traffic-Aware Grid Sizing: Coupling macroscopic traffic models (e.g., Cell Transmission Model) with AC Optimal Power Flow (OPF) allows just-in-time, scenario-adaptive sizing of solar, grid-coupling, and storage assets for ERS corridors. Traffic-aware design (using realistic traffic profiles and incident scenarios) can yield >70% capital cost savings relative to worst-case flat-load assumptions while achieving 100% reliability (Ghose et al., 2 Nov 2025).
Cost-Benefit Analysis: Battery downsizing (e.g., from 24 kWh to 3.3 kWh for passenger vehicles) and reduced under-vehicle mass translates to lower up-front cost; infrastructure costs for left-lane electrification and DWPT are on the order of 1–1.8 M€/km, with break-even thresholds dependent on fleet utilization and electricity/fuel price differentials (Llanes-Estrada et al., 2010, Agnihotri et al., 14 Dec 2025).
Urban Scaling Principles: Traffic-based ERS deployment strategies, leveraging statistical models of vehicle flow (e.g., Manhattan Poisson Line Process thinning by network location and density), can achieve substantial coverage benefits with as little as 5–10% of urban road length electrified—adequate for battery maintenance or net SOC gain for city vehicles (Nguyen et al., 2022).
Equity, Tolling, and Traffic Assignment: Simple ERS toll systems may lead to suboptimal network states—non-minimal travel times, underutilized charging assets, or even non-utilization—if not dynamically aligned with real-time battery SOC and electricity value. Adaptive or per-kWh pricing, rather than fixed tolling, is required for robust social and economic performance (Nakanishi et al., 11 Feb 2024).

5. Systemic Impacts and Power Sector Interactions

The energy, carbon, and power system implications of ERS scale with technology choice, operational flexibilities, and integration with renewables (Gaete-Morales et al., 2023).

ERS-BEV vs. Pure BEV & Indirect Electrification: Compared to hydrogen or e-fuel pathways, ERS-equipped battery-electric vehicles (ERS-BEVs) minimize power sector costs (ΔCost ≈ +2.2 bn €/yr for 17–18 TWh/yr demand, vs. +12–16 bn €/yr for fuel cell or synthetic fuel options) and favor solar PV over wind (Gaete-Morales et al., 2023).
Grid-Friendly Operations: Flexible ERS charging (including vehicle-to-grid participation) reduces renewable curtailment and improves utilization of diurnal solar surpluses; inflexible deployment increases peak grid loads and renewable spillage.
Battery and Environmental Effects: Frequent shallow-charging cycles made possible by ERS extend battery life by 50–80% (static deep-cycle reference: 6 y; ERS: ~9 y as empirically modeled for Indian urban corridors), reduce range anxiety (30–35% fewer out-of-charge events), and deliver quantifiable CO₂ and noise reductions (Agnihotri et al., 14 Dec 2025).
Voltage Stability and Power Quality: ERS introduces unique “moving load” profiles on distribution networks, with dynamic effects including voltage swings, harmonic loads, and contingent requirements for grid-side compensation or reinforcement. System sizing rules emerge from continuation power flow studies of maximal vehicle densities and segment lengths, balancing operational flexibility with network security margins (Wang et al., 2019, Gupta et al., 25 Nov 2025).

6. Challenges, Open Problems, and Future Directions

ERS presents a range of deployment bottlenecks and research directions:

Grid Harmonics and Power Quality: The oscillatory load imposed by DWPT segments requires careful harmonic management, sizing of inverters and BESS, and adoption of nonlinear control for clipping, especially as high harmonics or vehicle synchronism can excite grid eigenmodes (Gupta et al., 2 Sep 2025, Gupta et al., 25 Nov 2025).
Infrastructure Scalability and Retrofit: Pavement cutting for coil embedding, overhead line maintenance, interoperability standardization, and attack surfaces for billing and safety (e.g., exposure, automatic detachment on lane change) remain operational priorities (Agnihotri et al., 14 Dec 2025, Llanes-Estrada et al., 2010).
Adaptive Pricing and Social Optima: Uncoordinated or static tolling is ineffective in matching real-time traffic and battery state heterogeneity. Dynamic and usage-based tariffing, possibly aligned with real-time grid marginal pricing and SOC telemetry, is essential for societal optimality (Nakanishi et al., 11 Feb 2024).
Joint Network Design and Control: Location and timing of ERS segment rollout should be co-optimized with routing, grid reinforcement schedules, and renewable expansion, possibly incorporating vehicle fleet V2G, demand response, and resilience objectives (Gutierrez-Alcoba et al., 2022, Agnihotri et al., 14 Dec 2025, Ghose et al., 2 Nov 2025).
Empirical Validation: Pilot deployments, co-simulation studies coupling SUMO-traffic and electromagnetic models (as in the Delhi Outer Ring Road corridor), and field voltage/harmonic monitoring are necessary for validating design assumptions and scaling laws (Agnihotri et al., 14 Dec 2025, Ghose et al., 2 Nov 2025, Gupta et al., 2 Sep 2025, Nguyen et al., 2022).

ERS research synthesizes advances across power electronics, transportation systems, optimization, and urban design. Its quantitative foundation supports technical, economic, and policy strategies for decarbonizing surface transportation at scale.