ENERGETIC: Next Generation Battery Management System Based on Data Rich Digital Twin

ENERGETIC：基于数据丰富的数字孪生的下一代电池管理系统

• 批准号: 10080396
• 金额: $ 49.43万
• 依托单位: UNIVERSITY OF BATH
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10080396
• 关键词: ENERGETIC; Next; Generation; Battery; Management

The EU roadmap towards a climate-neutral economy by 2050 sets ambitious decarbonisation targets that shall be achieved by a massive deployment of renewable energy sources. Energy storage improves grid flexibility and allows higher penetration levels of renewable energy sources to create a decarbonised and more electrified society by means of leveraging second-life batteries. Battery management plays an essential role by ensuring an efficient and safe battery operation. However, current battery management systems (BMS) typically rely on semi-empirical battery models (such as equivalent-circuit models) and on a limited amount of measured data. Therefore, ENERGETIC project aims to develop the next generation BMS for optimizing batteries’ systems utilisation in the first (transport) and the second life (stationary) in a path towards more reliable, powerful and safer operations. ENERGETIC project contributes to the field of translational enhanced sensing technologies, exploiting multiple Artificial Intelligence models, supported by Edge and Cloud computing. ENERGETIC’s vision not only encompasses monitoring and prognosisthe remaining useful life of a Li-ion battery with a digital twin, but also encompasses diagnosis by scrutinising the reasons for degradation through investigating the explainable AI models. This involves development of new technologies of sensing, combination and validation of multiphysics and data driven models, information fusion through Artificial Intelligence, Real time testing and smart Digital Twin development. Based on a solid and interdisciplinary consortium of partners, the ENERGETIC R&D project develops innovative physics and data-based approaches both at the software and hardware levels to ensure an optimised and safe utilisation of the battery system during all modes of operation.

到2050年，欧盟通往气候中性经济的路线图设定了雄心勃勃的脱碳目标，应通过大量的可再生能源部署来实现。能源存储可提高网格灵活性，并通过利用第二寿命电池来创造更高的可再生能源渗透水平，从而创造出脱碳和更具电动性的社会。电池管理通过确保高效且安全的电池操作起着至关重要的作用。但是，当前的电池管理系统（BMS）通常依赖于半经验电池模型（例如等效电路模型）和有限量的测量数据。因此，充满活力的项目旨在开发下一代BMS，以优化电池系统在第一（运输）和第二寿命（固定）中使用更可靠，强大和安全的操作的道路。充满活力的项目有助于转化增强的灵敏度技术的领域，利用了由边缘和云计算支持的多个人工智能模型。充满活力的视野不仅包含监视和预后，具有数字双胞胎的锂离子电池的剩余使用寿命，而且还包括通过研究可解释的AI模型来审查退化的原因，包括诊断。这涉及开发多物理和数据驱动模型的敏感性，组合和验证的新技术，通过人工智能，实时测试和智能数字双胞胎开发的信息融合。基于合作伙伴的坚实而跨学科的联盟，充满活力的研发项目开发是在软件和硬件级别上的创新物理和基于数据的方法，以确保在所有操作模式下对电池系统的优化和安全利用。