Enabling Intelligent Bidirectional Charging: A Real-World Communication Interface Between Electric Vehicles, Charging Infrastructure, and a Control Optimizer

TL;DR

This paper details the real-world implementation and validation of a bidirectional EV charging system that integrates vehicle data, user preferences, and grid conditions via a multi-level communication architecture for urban deployment.

Contribution

It introduces a practical, field-validated communication interface and control system for bidirectional EV charging, advancing from simulation to real-world urban environment deployment.

Findings

Feasibility of real-world bidirectional charging demonstrated

Improved load balancing and vehicle-to-grid operation achieved

Early data acquisition enhances system efficiency

Abstract

This paper presents the real-world implementation and field validation of a user-aware bidirectional electric vehicle (EV) charging system developed within the Mobilities for EU and DymoBat projects in Dresden. Building on earlier simulation frameworks, the system enables transition from conceptual models to operational deployment in urban environments. To support grid flexibility and sustainable mobility, the solution combines real-time vehicle and user data with a centralized optimization platform to enable dynamic charging and discharging decisions. The architecture integrates a wireless On-Board Diagnostic II (OBD-II) interface and an open middleware node connected via a 5G campus network, allowing early access to vehicle state-of-charge before plug-in. A tablet-based interface captures user preferences such as departure time and energy demand, which are incorporated into the optimization together with grid conditions. A key contribution is a multi-level communication architecture linking the EV, charging station, user interface, and grid control center using the Open Charge Point Protocol (OCPP). The system integrates software, embedded hardware, and network communication for real-time charging management. Field deployment at Ostra Sport Park in Dresden demonstrates feasibility, improved load balancing, and robust vehicle-to-grid operation. The results show that early data acquisition and predictive control can enhance system efficiency. This work provides a practical benchmark for positive energy districts and future urban e-mobility systems.