Coordinated by Joseph Fitoussi, a researcher at PIMM, the OptUSeH2 project paves the way for a new generation of hydrogen systems that are safer, more sustainable, and more efficient.
Co-financed by Carnot funding with a view to strengthening scientific resources, OptUSeH2 aims to design one or more multi-purpose digital twins, a powerful tool for the intelligent optimization of hydrogen use. Multidisciplinary and resolutely focused on innovation, this large-scale project marks a strategic step forward for the energy performance and sustainability of hydrogen technologies, laying the foundations for a new generation of high value-added solutions.
A comprehensive and innovative approach to designing the hydrogen systems of tomorrow
Against a backdrop of accelerating energy transition, green hydrogen is emerging as a solution for the future, both for mobility needs and stationary applications. The OptUSeH2 project is part of this dynamic. "We don't want to limit ourselves to just one aspect," emphasizes Joseph Fitoussi. " Our ambition is to capitalize on the wealth of expertise developed over more than 25 years in the Carnot ARTS laboratories to build a systemic and coherent approach." The goal is to consider the hydrogen system as a whole, no longer as a simple addition of components but as an integrated and intelligently controlled whole.
OptUSeH2 brings together complementary cross-disciplinary expertise in structural mechanics, material durability, fluid analysis, systemic optimization, heat transfer, electrochemistry, and artificial intelligence. This unique synergy enables the project to simultaneously address issues related to storage tanks and fuel cells (PaC) with a view to developing a generic methodology that can be adapted to all types of hydrogen systems.
The roadmap is clear: develop two separate digital twins, test them on experimental benches, then combine them to master both the design and operation of a complete hydrogen system. This ambitious approach paves the way for a new generation of high-performance, reliable, and sustainable hydrogen solutions.
Digital intelligence for the performance and sustainability of hydrogen systems
Given the inherent complexity of hydrogen systems, the OptUSeH2 project relies on a cutting-edge approach: hybrid digital twins. By combining detailed physical modeling of components with artificial intelligence, these tools enable real-time processing of sensor data for optimal understanding and control of system behavior.
- When it comes to tanks, the materials they are made of are subjected to extreme thermomechanical stresses: pressure, thermomechanical fatigue, shocks, and humidity. "It is essential to understand the cumulative effect of these factors to ensure the durability of the tanks," emphasizes Joseph Fitoussi. The digital twin developed aims to predict the degradation of hydrogen gas tanks subjected to severe thermomechanical cycles and harsh environments.
Mohammadali Shirinbayan, a researcher at PIMM, explains: " New-generation materials, particularly thermoplastic matrix composites, are being evaluated. They are easier to recycle and also offer better resistance to fatigue and impact. We model the degradation mechanisms at different scales using multiphysics simulations, before validating them on dedicated test benches. Artificial intelligence plays a central role, optimizing the durability of the tank from the design stage onwards. Once in operation, data collected in real time (acoustic measurements, deformations, temperatures, piezoelectric signals) feed into the digital twin to dynamically adjust predictions and conditions of use. - On the fuel cell (PAC) side, the project's second digital twin targets the simultaneous optimization of energy efficiency and component longevity: membranes, humidifiers, compressors, auxiliary circuits. "Dense instrumentation allows us to continuously monitor temperature, humidity, pressure, flow rates, and current. Each piece of field data refines our understanding of the phenomena involved and, by the same token, our model, and each simulation guides our tests," explains Stéphane Chevalier, senior lecturer at I2M.
For Michael Deligant, professor at LIFSE, the challenge is clear: " Thanks to systemic modeling, we can simulate different operating scenarios. This allows us to precisely control boost pressure, water flow rates, and thermal management, with the aim of extending component life while maximizing their efficiency. With these intelligent digital twins, OptUSeH2 is paving the way for a new generation of hydrogen systems that are safer, more sustainable, and more efficient.
A simulation-experimentation loop for precision
The OptUSeH2 project is based on a closed-loop approach that closely links modeling and experimental validation. " We define usage scenarios, urban cycles, extreme conditions, and long-term storage, then develop the associated digital twins and test benches," explains Joseph Fitoussi.
The data collected feeds into learning algorithms, allowing the models to be fine-tuned. Each iteration reveals new critical points, inspires new tests, and refines predictions. Ultimately, this virtuous cycle should achieve an accuracy of over 95% between simulation and reality.
A ready-to-use technological solution for the hydrogen industry
Beyond its scientific advances, the OptUSeH2 project stands out as a truly operational tool for industry. Its ambition is to offer a turnkey solution capable of reducing operating costs, optimizing design, and implementing effective predictive maintenance. Thanks to real-time monitoring, the system can adjust usage parameters to maximize energy performance, monitor the condition of critical components, and anticipate their deterioration, even under extreme conditions (shocks, vibrations, high pressure).
The coupling of digital twins dedicated to storage and fuel cells will enable comprehensive control, from tank filling to energy management, paving the way for the establishment of industrial pilot sites and future large-scale commercialization.
" The goal is not to design a single system, but to build an adaptable methodology that can be used for both embedded systems and stationary installations, " concludes Joseph Fitoussi.
