The successful operation of Electric-Vehicle Batteries (EVB) is paramount for the ever-continuing goal of approaching a low carbon emission future. The Lithium-ion battery (LIB) is currently the best wager to implement on Electric Vehicles (EV). Nonetheless, it comes with its fair trade of challenges. The complexity involved in the design, manufacturing and operating conditions for these batteries has made their control and monitoring paramount. Digital Twin (DT) is concretely defined as a virtual replica of a physical object, process or system. The DT can be implemented in conjunction with the EVB physical embodiment to analyse and enhance its performance. ERP is a system designed to control production and planning amongst others. This paper presents the state-of-the-art battery design, production with the combination of DT and Enterprise system. A five-dimensional DT framework has been proposed linking the physical data and virtual data with ERP. The proposed method was used to model the digital twin of EVB at the concept level and solve its challenges faced in the industry Also the potential application & benefits of the framework have been formalised with the help of a case study from Tesla EVBs.

With many of the world’s governments committing to achieve net-zero greenhouse gas (GHG) emissions by mid-century, with well-defined milestones along the road, it is important to investigate how each sector can contribute towards achieving this global goal. The manufacturing sector, with its energy-intensive processes, large amounts of wastes, and hazardous and harmful emissions, is one of the main contributors to global GHG emissions, as well as other sustainability aspects, and, thus, it has great potential to contribute substantially to achieve net-zero objectives. This paper presents a techno-environmental-economic analysis of technologies that can play a key, enabling and leading role in the quest towards net-zero. Such technologies typically bring modest improvement in the environmental performance; however, the aim of this paper is to demonstrate how such small changes, when implemented in an industrial setting, can contribute significantly to the collective improvement in the environmental performance. In order to put the potential improvements into perspective, a real case study from the UK aerospace manufacturing sector is conducted. In the case study, metrics measuring potential improvements from the installation of a low-to-medium waste heat recovery system, and the upgrade of electric motors in the shopfloor to more energy efficient ones, are calculated through environmental and economic models. The models are then subject to a series of sensitivity analyses experiments to help understand the impact of different sources of uncertainty on the perceived GHG emissions, and economic and energy savings. The techno-environmental-economic analysis results revealed that these small changes, when implemented in an industrial setting, can indeed bring valuable improvements in the environmental performance of a manufacturing institute. Further, the sensitivity analysis experiments demonstrated how the environmental and economic performances are not adversely affected by different levels of fluctuations in key, likely to fluctuate, input parameters.