Periodic Reporting for period 2 - OPEVA (OPEVA - OPtimization of Electric Vehicle Autonomy)
Reporting period: 2024-01-01 to 2024-12-31
The OPEVA project aims to advance and optimize sustainable electric vehicles (EVs) within the European transport sector, addressing technological advancements and socio-economic challenges.
Key Objectives:
Optimize electric vehicle battery autonomy.
Manage green energy production, conversion, and storage systems.
Enable affordable, safe, and ecologically neutral light mobility solutions.
Reduce energy consumption by more than 10%.
Decrease charging time by at least 10%.
Anticipated Impacts:
Environmental: Lower emissions and carbon footprint.
Economic: Enhance European EV technology competitiveness.
Social: Improve public health and foster sustainable mobility.
During the second year, OPEVA made substantial progress across various Work Packages. Key advancements include developments in battery system design, intelligent energy management, and smart data solutions. Notable achievements include the development of a modular Battery Management System (BMS), implementation of AI-based algorithms for battery state estimation, and successful deployment of demonstrators showcasing innovative EV technologies.
These accomplishments underscore OPEVA's commitment to enhancing EV performance and sustainability for large-scale adoption in the EU.
Key Objectives:
Optimize electric vehicle battery autonomy.
Manage green energy production, conversion, and storage systems.
Enable affordable, safe, and ecologically neutral light mobility solutions.
Reduce energy consumption by more than 10%.
Decrease charging time by at least 10%.
Anticipated Impacts:
Environmental: Lower emissions and carbon footprint.
Economic: Enhance European EV technology competitiveness.
Social: Improve public health and foster sustainable mobility.
During the second year, OPEVA made substantial progress across various Work Packages. Key advancements include developments in battery system design, intelligent energy management, and smart data solutions. Notable achievements include the development of a modular Battery Management System (BMS), implementation of AI-based algorithms for battery state estimation, and successful deployment of demonstrators showcasing innovative EV technologies.
These accomplishments underscore OPEVA's commitment to enhancing EV performance and sustainability for large-scale adoption in the EU.
Work Package 1, Requirements Analysis, involved the development of a high-level architecture identifying main building blocks and interactions. Success criteria and Key Performance Indicators (KPIs) for each demonstration were defined, and a comprehensive gap analysis of electric vehicle technology was conducted, culminating in the completion of deliverables D1.2 and D1.3.
Work Package 2, Design Architecture Optimization, focused on the design and optimization of the complete battery system architecture and inverter for traction control. This included the development of a modular Battery Management System (BMS) with advanced electronic balancing control units, thermal management studies and simulations, and optimization of charging interfaces along with cost-effective analysis.
Work Package 3, Smart Data Management, the OPEVA Data Model concept was developed using UML, XML, and XSD schemas. A data preprocessing infrastructure on the cloud using Docker was deployed, data analysis was conducted, and collection systems for charging station data were designed. Data from EV units was collected and analyzed to aid in BMS development, route planning, and performance analysis.
Work Package 4, Battery Management System, involved the development of AI-based algorithms for precise estimation of battery State of Charge (SoC) and State of Health (SoH). Optimized charge control strategies for managing energy consumption and Vehicle-to-Grid (V2G) energy transfer were developed, along with a battery thermal management system integrated into the BMS. The physical topology of the BMS was defined, incorporating DC/DC converters, On-Board Charger (OBC), and battery pack.
Work Package 5, Intelligent Energy Management, focused on the design of an Integrated Energy Management System (IEMS) to enhance EV battery performance. Driver behaviors were incorporated into intelligent energy management, and a Driver Recommender System was developed. Intelligent energy management algorithms deployable in vehicles or as Software-as-a-Service (SaaS) in the cloud were designed, along with optimization methods for integrating secure EV charging infrastructure into smart grids.
Work Package 6, Demonstrators, showcased various innovative solutions through multiple demonstrations. Hardware-in-the-Loop (HiL) testing for battery balancing and power electronics was conducted, and a Battery Pack with Smart BMS was developed. Improved sensors for accurate battery monitoring were designed and tested, a Digital Twin for performance optimization was created, and energy-efficient route planning for last-mile delivery was implemented. Inductive charging with BMS and power electronics was integrated, modular battery storage solutions were developed, and a flexible charging scheduler was implemented.
Work Package 7, Dissemination, Exploitation, and Communication, involved defining target audiences and setting up appropriate dissemination strategies. Exploitation activities were collected, and strategies for commercialization were defined. KPIs were set and periodically checked to reach potential end-users and achieve the expected impact.
Work Package 8, Project Management, focused on organizing and conducting bi-weekly Work Package and Demo meetings, managing logistics and agendas for face-to-face meetings, monitoring and reminding partners of participation and commitment, updating the GANT table, managing the Grant Agreement Amendment, and producing and submitting periodic reports to Chips-JU.
Work Package 2, Design Architecture Optimization, focused on the design and optimization of the complete battery system architecture and inverter for traction control. This included the development of a modular Battery Management System (BMS) with advanced electronic balancing control units, thermal management studies and simulations, and optimization of charging interfaces along with cost-effective analysis.
Work Package 3, Smart Data Management, the OPEVA Data Model concept was developed using UML, XML, and XSD schemas. A data preprocessing infrastructure on the cloud using Docker was deployed, data analysis was conducted, and collection systems for charging station data were designed. Data from EV units was collected and analyzed to aid in BMS development, route planning, and performance analysis.
Work Package 4, Battery Management System, involved the development of AI-based algorithms for precise estimation of battery State of Charge (SoC) and State of Health (SoH). Optimized charge control strategies for managing energy consumption and Vehicle-to-Grid (V2G) energy transfer were developed, along with a battery thermal management system integrated into the BMS. The physical topology of the BMS was defined, incorporating DC/DC converters, On-Board Charger (OBC), and battery pack.
Work Package 5, Intelligent Energy Management, focused on the design of an Integrated Energy Management System (IEMS) to enhance EV battery performance. Driver behaviors were incorporated into intelligent energy management, and a Driver Recommender System was developed. Intelligent energy management algorithms deployable in vehicles or as Software-as-a-Service (SaaS) in the cloud were designed, along with optimization methods for integrating secure EV charging infrastructure into smart grids.
Work Package 6, Demonstrators, showcased various innovative solutions through multiple demonstrations. Hardware-in-the-Loop (HiL) testing for battery balancing and power electronics was conducted, and a Battery Pack with Smart BMS was developed. Improved sensors for accurate battery monitoring were designed and tested, a Digital Twin for performance optimization was created, and energy-efficient route planning for last-mile delivery was implemented. Inductive charging with BMS and power electronics was integrated, modular battery storage solutions were developed, and a flexible charging scheduler was implemented.
Work Package 7, Dissemination, Exploitation, and Communication, involved defining target audiences and setting up appropriate dissemination strategies. Exploitation activities were collected, and strategies for commercialization were defined. KPIs were set and periodically checked to reach potential end-users and achieve the expected impact.
Work Package 8, Project Management, focused on organizing and conducting bi-weekly Work Package and Demo meetings, managing logistics and agendas for face-to-face meetings, monitoring and reminding partners of participation and commitment, updating the GANT table, managing the Grant Agreement Amendment, and producing and submitting periodic reports to Chips-JU.
The OPEVA project has made significant advancements in electric vehicle (EV) technology by developing AI-based algorithms for Battery Management Systems (BMS) that enhance battery state estimation and vehicle autonomy. Innovations in charge control strategies support fast charging and extend battery life, while advanced communication protocols enable smart grid integration. An optimized thermal management system has also been integrated into the BMS, improving battery health and lifespan.
The project has incorporated driver behaviors into Intelligent Energy Management Systems (IEMS) to enhance battery performance and developed intelligent energy management algorithms for vehicles or cloud-based services. The OPEVA Data Model sets new standards for automotive data handling. Demonstrators have showcased advancements in battery management, energy efficiency, and smart grid integration, aiming to increase EV adoption through improved autonomy and charging infrastructure. These innovations are expected to improve energy efficiency, optimize EV performance, and set new industry standards.
Policy-wise, OPEVA will contribute to developing standards and regulations for EV technologies, promoting sustainable and efficient transportation systems. The project aims to reduce carbon emissions, stimulate growth in the EV sector, and enhance societal acceptance of EVs. For further success, continued research investment, additional pilot projects, financial resources, robust commercialization plans, strong intellectual property rights protection, international market expansion, and a supportive regulatory framework are required.
The project has incorporated driver behaviors into Intelligent Energy Management Systems (IEMS) to enhance battery performance and developed intelligent energy management algorithms for vehicles or cloud-based services. The OPEVA Data Model sets new standards for automotive data handling. Demonstrators have showcased advancements in battery management, energy efficiency, and smart grid integration, aiming to increase EV adoption through improved autonomy and charging infrastructure. These innovations are expected to improve energy efficiency, optimize EV performance, and set new industry standards.
Policy-wise, OPEVA will contribute to developing standards and regulations for EV technologies, promoting sustainable and efficient transportation systems. The project aims to reduce carbon emissions, stimulate growth in the EV sector, and enhance societal acceptance of EVs. For further success, continued research investment, additional pilot projects, financial resources, robust commercialization plans, strong intellectual property rights protection, international market expansion, and a supportive regulatory framework are required.