The ENERGETIC project, now at its halfway mark, is driving transformative advancements in battery management technology to enhance the safety, efficiency, and longevity of lithium-ion batteries. By integrating low-cost sensors, advanced modeling, artificial intelligence (AI), and cloud-connected digital twins, the project is pioneering a predictive, intelligent approach to battery monitoring and maintenance.
Key Innovations and Progress:
Central to the project’s success are novel, cost-effective sensors that provide real-time insights into battery health. Ultrasonic sensors, validated on commercial cells, enable precise tracking of aging and performance metrics like State of Charge (SoC) and State of Health (SoH). Flexible distributed temperature sensors offer detailed thermal mapping to prevent overheating, while AI-driven thermal imaging systems detect anomalies with minimal computational effort. These sensors are unified through a scalable hardware platform based on ESP32 microcontrollers, ensuring seamless integration with existing Battery Management Systems (BMS).
To process this data, a robust Hardware Abstraction Layer (HAL) standardizes and synchronizes sensor inputs, enabling real-time communication with cloud platforms. Advanced multiphysics models simulate electrical, thermal, and chemical behaviors, while AI frameworks—including Transformer-based algorithms and hybrid LSTM architectures—achieve exceptional accuracy in predicting battery lifespan (errors below 1.5%) and detecting faults. A cloud-connected Digital Twin (DT), validated in virtual environments mirroring real-world conditions, integrates predictive maintenance tools powered by Google Cloud’s scalable infrastructure.
Current Focus and Future Goals:
With 20 months remaining, the team is refining prototypes for real-world reliability. Lab-tested ultrasonic and thermal sensors will undergo rigorous field trials under extreme conditions (temperature fluctuations, vibrations) to ensure robustness. AI algorithms, already demonstrating over 98% accuracy in predicting battery wear, are being optimized for diverse applications, from electric vehicles to renewable energy storage. A critical challenge remains the seamless integration of these technologies into a unified, cloud-based platform. Collaborative testing with industry partners, including Forsee Power and EDF, will validate system performance by late 2025.
Ultimately, ENERGETIC aims to extend battery lifespans through predictive maintenance, reducing waste and supporting the global energy transition. By bridging cutting-edge sensor technology, AI, and digital innovation, the project empowers a sustainable future where batteries operate smarter, last longer, and reliably power an electrified world.
