No abstract

Under the net-zero carbon transition, lithium-ion batteries (LIB) plays a critical role in supporting the connection of more renewable power generation, increasing grid resiliency and creating more flexible energy systems. However, poor useful life and relatively high cost of batteries result in barriers that hinder the wider adoption of battery technologies e.g., renewable resources storage. Furthermore, the useful life of a battery is significantly affected by the materials composition, system design and operating conditions, hence, made the control and management of battery systems more challenging. Digitalisation and artificial intelligence (AI) offer an opportunity to establish a battery digital twin that has great potentials to improve the situational awareness of battery management systems and enable the optimal operation of battery storage units. An accurate estimation of the state of charge (SOC) can indicate the battery's status, provide valuable information for maintenance and maximise its useful life. In this paper, a digital twin-driven framework based on a hybrid model that connects LSTM (long short-term memory) and EKF (extended Kalman filter) has been proposed to estimate the SOC of a li-ion battery. LSTM provides more accurate initial SOC estimations and impedance model data to EKF. According to experimental results, the developed battery digital twin is considered less dependent on the initial SOC conditions and is deemed more robust compared to traditional means with a lower RMSE (root mean squared error).

The double–double (DD) laminate families that contain two continuous angles, which were proposed by Tsai (“Double–Double: New Family of Composite Laminates,” AIAA Journal, Vol. 59, No. 11, 2021, pp. 4293–4305), opened up a whole new era for composite layups, which are easy to manufacture and design. In the present study, the design space referred to as feasible regions is derived explicitly based on novel formulations for the lamination parameters of DD laminates. This enables the boundaries of the design space to be obtained analytically, providing mathematical support for DD families. The obtained result shows that their design space is larger than that of conventional quadaxial laminates in terms of industrial practices. A homogenization criterion is implemented into the design space, based on which a tailored DD laminate is proposed, expanding design possibilities and enabling homogenization to be achieved using only 16 plies/4 repeats. The work proposed offers significant benefits through practical solutions to making design, manufacturing, and testing simpler and more competitive.