Battery management by multi-domain digital twins

Battery management by multi-domain digital twins

Physics and data-based battery management by multi-domain digital twins (BATMAX) sets out to pave the way for advanced next generation data-based and adaptable battery management systems capable of fulfilling the needs and requirements of various mobile and stationary applications and use cases. The main objective of the project is to contribute to improving battery system performance, safety, reliability, service life, lifetime cost and therefore to maximise the value created by operation of the battery systems in various kinds of end use applications. This is approached by creating a framework for next generation of battery management based on large amounts of data, both experimental, operational and synthetic, adaptable physics-based models, suitable reduced-order models for both physical BMS algorithms and real-time multi-scale digital twins. BATMAX develops a framework to efficiently parameterise physics-based models is essential to reduce the cost of model development and encourage their use in BMSs. Advanced numerical methods accelerate the extraction of relevant parameters from experimental and numerical simulation data. BATMAX develops hardware and sensorisation on cell and system level for collection and communication of battery measurement data and integrates an open source BMS platform to a laboratory scale prototype system. The BATMAX BMS framework (hardware and software) will enable to exploit advanced battery models with integrated digital twin framework that is capable to cope with high amount of measured data, which will enable to monitor the battery aging in depth and to facilitate the key functions of systems. A central output is an extensive multi-purpose and scalable digital twin framework is developed and validated for advanced battery management. Key impacts from BATMAX contribute to 10% battery lifetime increase on average scenario, 20% performance increase in specific scenarios and contribution to lifecycle cost reduction by at least 10%.