Electric vehicles are emerging as a sustainable alternative to conventional transportation. However, route planning in Internet of Vehicles environments remains challenging because conventional routing algorithms based on travel distance or time do not adequately consider electric vehicle-specific constraints. Existing routing strategies often overlook the combined effects of battery energy, traffic congestion, and charging requirements, resulting in inefficient routing decisions. This paper proposes an adaptive Energy, Congestion, and Charging-Aware Routing (ECCAR) protocol that uses energy-feasibility verification, cost-based charging-station selection, and route re-optimization for electric vehicles in Internet of Vehicles environments. ECCAR integrates residual battery energy, traffic congestion, travel time, charging station availability, and charging delay into a unified routing decision framework. It first evaluates whether the remaining battery energy is sufficient to reach the destination. Otherwise, it identifies all reachable charging stations and selects the one that minimizes the routing cost rather than the nearest station. After charging, the route is recalculated using traffic and charging information obtained through V2V and V2I communications. Simulation results demonstrate that ECCAR reduces total energy consumption by up to 19.4%, travel time by up to 25.3%, and charging waiting time by up to 39.1% compared with existing routing schemes. These results demonstrate the benefits of integrating energy, traffic, and charging information for reliable electric vehicle routing in dynamic Internet of Vehicles environments.
