Smart EV Charging via Wi-SUN and oneM2M Integration

Introduction

Streetlights play a crucial role in cities by providing illumination to enhance the safety and security of road users and pedestrians. However, beyond their primary function, street lights can also serve as a versatile and extensible platform for smart city applications because they are electrically operated, densely deployed, immobile and publicly owned. Augmenting streetlights presents opportunities to integrate sensors, actuators, computing systems, networking capabilities, and Internet of Things (IoT) components. This integration can unlock a wide array of innovative services and applications for urban environments, including traffic monitoring, environmental sensing, digital signage, Wi-Fi access, and E-vehicle charging.

We propose transforming these streetlights into an intelligent Electric Vehicle (EV) charging ecosystem by incorporating Wi-SUN networks and the oneM2M middleware. Additionally, we have incorporated the Arduino Nano BLE 33 Sense module to enhance functionality and extend connectivity options.

By embedding Level-2 EV charging stations into streetlights, we create a smart charging ecosystem that ensures seamless communication, optimized energy utilization, and real-time data exchange. The system integrates the Open Charge Point Protocol (OCPP) for interoperability and the Wi-SUN protocol for reliable long-range connectivity, ensuring low-latency authentication and billing. Additionally, the oneM2M middleware acts as the backbone for integration with broader smart city infrastructure, enabling functionalities like real-time resource discovery, subscription-based notifications, dynamic power management during surges, and priority access for emergency vehicles.

Our proof-of-concept, tested on a campus-wide Wi-SUN network, demonstrates a reliable range of 470 meters and an authentication latency of just 0.7 seconds. This project marks a significant step toward scalable, eco-friendly e-mobility solutions, addressing the critical need for accessible EV charging infrastructure.

For more information on Wi-SUN technology, visit: Wi-SUN Docs

Key Components and Architecture

Wi-SUN Communication Protocol:

• Wi-SUN provides the backbone for long-range connectivity across the entire system, enabling reliable communication between EV chargers and the central management system (CMS).
• The oneM2M platform acts as the middleware layer, allowing seamless integration of charging stations into the broader smart city ecosystem, including smart grids and emergency services.

Arduino Nano BLE 33 Sense for BLE Connectivity:

• The Arduino Nano BLE 33 Sense enables Bluetooth communication for local connectivity. This allows EV users to interact with chargers through a smartphone app for authentication and charging control.
• BLE also plays a crucial role in detecting nearby emergency vehicles. When an emergency vehicle passes within range of a streetlight, the Arduino Nano BLE 33 Sense detects the vehicle's unique UUID and sends this data to the central system, triggering dynamic traffic management to clear pathways for emergency vehicles.

oneM2M Middleware for System Integration:

• The oneM2M middleware facilitates seamless communication between EV chargers and smart city infrastructures by providing a standardized Common Service Layer (CSL). It supports real-time data exchange for user authentication, energy consumption tracking, billing, and traffic management. With features like resource discovery and subscription-based notifications, oneM2M ensures efficient communication across devices.
• Integration of the Open Charge Point Protocol (OCPP) further guarantees interoperability between different EV chargers and the central management system (CMS), making the solution scalable and adaptable for future expansions.

Level-2 EV Charging Stations:

• Each charger is designed to be easily deployable at various locations, including in parking lots, housing complexes, and commercial areas. They support Level-2 charging (240V).

Prerequisites

Before proceeding with the setup, ensure you have the following:

• Wireless Gecko (EFR32) Kits: Purchase one of the Wireless Gecko kits with compatible radio boards, available at Silicon Labs Wi-SUN Products.
• Simplicity Studio 5 (SSv5) and Gecko SDK: Download SSv5 and the Gecko SDK, and familiarize yourself with the SSv5 Launcher perspective. Detailed instructions are available in the Simplicity Studio 5 User's Guide.

Raspberry Pi Setup: You will need two Raspberry Pi devices:

• The first will configure the Wi-SUN Bridge Router (BR). Set up Raspbian OS, connect it to Ethernet, and enable SSH and VNC Viewer for remote access.
• The second will be used for the EV charging setup. Similarly, install Raspbian OS and Python to run the EV charging scripts. Getting Started with Rpi.

Hardware Fabrication for EV Charger

Public EV chargers must be durable, as they will face frequent use. Therefore, selecting components based on their strengths and weaknesses is essential to ensure reliability. The selection criteria for each component include:

• Technological Requirements: The component should meet power supply specifications, interface easily with the processor, and be simple to code.
• Validation: Components are assessed based on brand reputation, user reviews, and the quality of available documentation.

In the context of India's rapidly growing EV market, we have focused on creating a charger design that aligns with local vehicular standards, building requirements, and government regulations. Special attention was given to ensure the charger’s ease of fabrication, affordability, and potential for large-scale production. The proposed architecture follows the Level 2 charging standards (240 Volts).

Devices Used in EV Charging System (EVCS)

• Solid-State Relay (SSR): A semiconductor relay with no moving parts, providing high durability and resistance to magnetic interference. Initially used for controlling power flow but replaced due to wiring issues.
• Bare Relay: Used in the third prototype to replace Surface-Mount Devices (SMD) components and minimize connection failures, resulting in improved reliability.
• PZEM-004T Power Meter: Monitors voltage, current, and energy consumption. This compact module communicates via a TTL serial interface for seamless integration with the system.
• 7-Inch Touchscreen LCD Display: Displays the Graphical User Interface (GUI) and allows user interaction via a keypad, following Government of India guidelines.
• 16A 3-Pin Plug: Provides power output for EV charging, controlled by the processor through the relay.
• Raspberry Pi 4: Acts as the central controller, managing all components like the relay, power meter, and LCD display.
• Arduino Nano BLE 33 Sense: Integrate this device to enable Bluetooth Low Energy (BLE) connectivity for last-mile communication and emergency vehicle detection.

Enclosure Design

The enclosure, designed in Autodesk Fusion 360, has an IP65 rating for weather protection and is sized at 25cm x 30cm x 8.5cm to fit all components securely. The design also integrates an emergency stop button for safety, placed in the power supply circuit before the relay module. AC power is used for powering the processor and other electronic components.

Software Development Section

The software development for the Smart EV Charging System is designed to integrate the various components (Wi-SUN, BLE, oneM2M middleware, EV charging hardware, and Raspberry Pi) into a cohesive, user-friendly system. The primary goal is to ensure reliable communication between the EV charger, Arduino Nano BLE 33 Sense, and Raspberry Pi, while also handling tasks such as user authentication, billing, charging control, and emergency vehicle detection.

This section outlines the key software components and the communication protocols used in the system.

1. Overview of the Software Architecture

The system relies on the following core software components:

• Raspberry Pi (EV Charger Controller): Runs the core control software for managing the EV charger and communication with external systems.
• Arduino Nano BLE 33 Sense: Handles Bluetooth communication and local sensor input (e.g., proximity detection of emergency vehicles).
• Wi-SUN: Provides long-range communication between the charger and the central system.
• oneM2M Middleware: Facilitates seamless integration of the EV charger with the smart city infrastructure for data exchange and management.
• Mobile Application: Allows EV users to connect to the charger via Bluetooth for authentication and to initiate charging.

Mobile application:

• Web Interface (Central Management System): Displays charger details, user authentication, billing information, and real-time status updates. The dashboard integrates seamlessly with oneM2M to fetch and display updates in an organized and user-friendly manner. Leveraging key features of oneM2M, the system ensures efficient data management through its Common Service Layer (CSL), enabling standardized data exchange across devices. It utilizes resource discovery, subscription/notification mechanisms for real-time updates, and secure communication protocols to ensure data integrity and reliability. These features provide a robust and scalable foundation for managing IoT-enabled charger systems efficiently.

Login Page:

Role-based authentication page where users log in with credentials specific to their roles (admin or user).

Admin Dashboard:

• Features an app bar with the organization's logo, dashboard title, and a profile icon. Hovering over the profile icon reveals options like viewing the username and logging out.
• Includes a map visualization with markers indicating the locations of chargers.
• Displays periodic energy consumption statistics for chargers using clear bar graphs.

User Dashboard:

• Accessible only to users with the "user" role.
• Displays transaction details, including the time of each transaction, the specific charger used, and the amount charged.

2. Key Technologies Used

• Python 3: The primary programming language used for the Raspberry Pi controller. Python's simplicity and wide support for libraries (such as RPi.GPIO, serial, WebSocket) make it ideal for managing the interactions between hardware and communication protocols.
• Arduino C++: Used to program the Arduino Nano BLE 33 Sense for BLE communication and emergency vehicle detection.
• oneM2M APIs: Used to integrate the charger into the broader smart city infrastructure.
• Serial Communication: Establishes communication between the Arduino Nano BLE 33 Sense and the Raspberry Pi for local data exchange (e.g., emergency vehicle detection, BLE pairing).
• Kotlin: Development of the android app to connect to EV charger via BLE.

EV Charger on the oneM2M Platform

The integration of the EV Charger with the oneM2M platform enables standardized communication and data exchange between non-oneM2M-compliant nodes (e.g., EV chargers) and the oneM2M service layer via an Interworking Proxy Entity (IPE). Through resource containerization, oneM2M supports seamless functionalities such as real-time authentication, billing, and data synchronization with broader smart city systems like traffic management, energy grids, and emergency response services.

Authentication Process

Figure 6 illustrates the data flow from the EV charger (non-oneM2M node) to the oneM2M service layer. The authentication process begins when a user interacts with the EV charger:

User Authentication:

• The EV charger retrieves the User ID and sends a GET request to the oneM2M platform using REST APIs.
• Data is exchanged in JSON format, allowing lightweight and efficient communication.

Unregistered Users:

• If the User ID is not found on the platform, an error message is returned, and the charger interface displays “User Not Found.” Users are prompted to register before proceeding.

Registered Users:

• For valid users, the platform fetches associated account details, including the e-wallet balance. If the balance is sufficient for the requested charging session, the system authorizes the user. Otherwise, an “Insufficient Balance” message is displayed.

Billing Process

Once authenticated:

• The platform provides the cost per unit of energy consumption and the user’s e-wallet balance in JSON format.
• The EV charger deserializes the JSON data for local computation using Python, ensuring quick responses without dependency on real-time network stability.

During the session, the system logs:

• Total energy consumption.
• Cost of the session.
• Updated user balance.

If the charging process is interrupted (e.g., due to a power outage or emergency), the system updates the platform with the energy consumed before the interruption. Once the session is complete, any unused balance is refunded, and the updated transaction details are synchronized with the platform.

Data Structure and Containers on the oneM2M Platform

Figure 7 shows the hierarchical organization of the EV Charger Application Entity (AE) within the oneM2M smart city resource tree. The AE structure includes separate User and Charger Containers for managing data.

User Container

The User Container stores details about each user's transactions and wallet status. Each entry includes:

• Timestamp: Date and time of the transaction.
• User ID: Unique identifier for the user.
• Charger ID: Identifier for the charger used.
• Transaction Amount: Total cost of the session.
• Unit Price: Cost per unit of energy.
• Units Consumed: Total energy consumed in kWh.
• Wallet Balance: Remaining balance in the user’s e-wallet.

Charger Container

The Charger Container tracks data related to the utilization and performance of individual chargers. Each entry includes:

• Timestamp: Date and time of the session.
• Charger ID: Unique identifier for the charger.
• User ID: Identifier for the user using the charger.
• Transaction Amount: Total cost of the session.
• Unit Price: Cost per unit of energy.
• Units Consumed: Total energy consumed in kWh.

This structured organization ensures accurate record-keeping and real-time synchronization of charging and transaction details.

System Updates and Synchronization

Authentication Phase:

• The EV charger commicates via wi-sun with Border Routrer(BR) to fetch user data (e.g., balance, registration status) from the oneM2M platform during the authentication process.
• User details are checked against the User Container, ensuring only authorized users proceed.
• Authentication Phase:The EV charger fetches user data (e.g., balance, registration status) from the oneM2M platform during the authentication process.User details are checked against the User Container, ensuring only authorized users proceed.

Session Logging:

• As the charging progresses, real-time session data is recorded locally and synchronized with the platform. Data is logged in both the User and Charger Containers.

Post-Session Updates:

• Once charging is complete, the system updates the User Container with the remaining wallet balance and transaction history.
• The Charger Container is updated with session performance metrics, providing insights for system monitoring and diagnostics.

By leveraging the oneM2M platform, this system achieves:

• Scalable Integration: New users and chargers can be easily added to the platform.
• Real-Time Monitoring: Ensures accurate updates for user accounts and charger utilization.
• Interoperability: Allows seamless interaction with other smart city systems.

This architecture provides a reliable, future-ready solution for managing EV charging stations as part of a smart city ecosystem.

Detailed Workflow and User Experience

1. EV User Authentication via BLE/RFID

• Users connect their smartphones to the charger using Bluetooth. They can verify themselves through a dedicated mobile app when they approach a charging station.
• The Arduino Nano BLE 33 Sense handles the BLE connection, sending user credentials to the backend server. If authentication is successful, the charger prepares to begin the charging process.
• Users also have an option to scan registered RFID card for authentication.

2. Charging Process

• Once authenticated, the user enters the desired amount of charging, and the system checks the user’s balance in their e-wallet (via oneM2M) to ensure sufficient funds.
• If the user’s account balance is adequate, the charger begins the charging process and the Power Meter monitors real-time energy consumption.
• The 7-inch LCD touchscreen provides real-time updates on charging progress. Upon completion, the system resets for the next user.

3. Emergency Vehicle Detection and Traffic Management

• Emergency Vehicle UUID Detection: When an emergency vehicle with a preconfigured BLE UUID comes into the proximity of a streetlight, the Arduino Nano BLE 33 Sense detects the vehicle and sends this information to the Wi-SUN Border Router.
• This data is relayed to the central management system (CMS), which can trigger immediate actions, such as adjusting traffic signals or clearing pathways for the emergency vehicle, thereby improving response times and reducing congestion

How to Set Up Software for This Project:

1. Set up the Linux Bridge (BR) by following the Silicon Labs setup guide. GitHub

2. Flash the CLI application code onto the router nodes. A detailed, step-by-step guide is included in the attached presentation to help you complete this task easily.

3. Run the attached Python code (GitHub) on the Raspberry Pi for the EV charging setup. This will connect with the BR and start functioning.

4. guptarohan6502/Wisun_EV-onem2m_Hackathon - github link for all the codes for this project

Communication Protocol (oneM2M & OCPP Integration)

This project uses the Open Charge Point Protocol (OCPP) for communication between the EV charger and a central management system (CMS). The CMS, hosted on a cloud platform, controls the charging process. By integrating OCPP with the oneM2M middleware, our charger becomes compatible with smart city IoT systems, allowing seamless interaction with other connected devices.

Conclusion

Our project presents a comprehensive solution for smart EV charging infrastructure integrated into urban landscapes, combining Wi-SUN for long-range communication, BLE for last-mile connectivity, and oneM2M middleware for IoT integration. The introduction of Arduino Nano BLE 33 Sense enhances user experience by allowing smartphone-based authentication and enabling emergency vehicle detection to improve traffic management.

By addressing the challenges of scalability, efficiency, and emergency services integration, our system represents a forward-thinking approach to e-mobility in smart cities, demonstrating how existing urban infrastructure can be leveraged to meet future transportation and safety needs.

Meet Our Team

1) Rohan Gupta

2) Vaibhav Naware

3) Peri Reddy Vaka

4) Deepthi Teegavarapu

5) Surya Teja

Mentos:-

1) Dr. Aftab M Hussain

2) Ms. Anuradha Vattem