Transfer Learning Techniques for the Lithium-Ion Battery State of Charge Estimation

State of Charge (SOC) estimation is vital for battery management systems (BMS), impacting battery efficiency and lifespan. Accurate SOC estimation is challenging due to battery complexity and limited data for training Machine Learning based models. Transfer learning (TL) leverages pre-trained models, reducing training time and improving generalization in SOC estimation. In this paper, 8 different transfer learning techniques are examined, which were applied in four different models (LSTM, GRU, BiLSTM, and BiGRU) for SOC estimation. These transfer learning techniques have been applied to three datasets for re-training the models and results have been compared with the same models defined by Bayesian Hyperparameter Optimization. The TL4 and TL5 techniques consistently stood out as among the most efficient in both accuracy and computational time

Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries: An Overview

In recent years, there has been a noticeable shift towards electric mobility and an increasing emphasis on integrating renewable energy sources. Consequently, batteries and their management have been prominent in this context. A vital aspect of the BMS revolves around accurately determining the battery pack’s SOC. Notably, the advent of advanced microcontrollers and the availability of extensive datasets have contributed to the growing popularity and practicality of data-driven methodologies. This study examines the developments in SOC estimation over the past half-decade, explicitly focusing on data-driven estimation techniques. It comprehensively assesses the performance of each algorithm, considering the type of battery and various operational conditions. Additionally, intricate details concerning the models’ hyperparameters, including the number of layers, type of optimiser, and neuron, are provided for thorough examination. Most of the models analysed in the paper demonstrate strong performance, with both the MAE and RMSE for the estimation of SOC hovering around 2% or even lower

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example

A new method to retrieve the real part of the equivalent refractive index of atmospheric aerosols

This document is the Accepted Manuscript version of the following article: S. Vratolis, et al, ‘A new method to retrieve the real part of the equivalent refractive index of atmospheric aerosols’, Journal of Aerosol Science, Vol. 117: 54-62, March 2018. Under embargo until 29 December 2019. The final, published version is available online at DOI: https://doi.org/10.1016/j.jaerosci.2017.12.013.In the context of the international experimental campaign Hygroscopic Aerosols to Cloud Droplets (HygrA-CD, 15 May to 22 June 2014), dry aerosol size distributions were measured at Demokritos station (DEM) using a Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 550 nm (electrical mobility diameter), and an Optical Particle Counter (OPC model Grimm 107 operating at the laser wavelength of 660 nm) to acquire the particle size distribution in the size range of 250 nm to 2.5 μm optical diameter. This work describes a method that was developed to align size distributions in the overlapping range of the SMPS and the OPC, thus allowing us to retrieve the real part of the aerosol equivalent refractive index (ERI). The objective is to show that size distribution data acquired at in situ measurement stations can provide an insight to the physical and chemical properties of aerosol particles, leading to better understanding of aerosol impact on human health and earth radiative balance. The resulting ERI could be used in radiative transfer models to assess aerosol forcing direct effect, as well as an index of aerosol chemical composition. To validate the method, a series of calibration experiments were performed using compounds with known refractive index (RI). This led to a corrected version of the ERI values, (ERICOR). The ERICOR values were subsequently compared to model estimates of RI values, based on measured PM2.5 chemical composition, and to aerosol RI retrieved values by inverted lidar measurements on selected days.Peer reviewe

Participatory decision-support model in the context of building structural design embedding BIM with QFD

The design and optimisation of building structures is a complex undertaking that requires the effective collaboration of various stakeholders and involves technical and non-technical expertise. The paper investigated an integrated decision-support framework using Quality Function Deployment (QFD) in structural design optimisation. The aim of the study was to develop and test a systematic participatory model that utilises Building Information Modelling (BIM)-enabled technologies for data collection and group decision-making theory. The uncertainties associated with the decision-makers’ preferences were computed using Evidential Reasoning (ER) algorithms in the QFD house of quality. An actual decision scenario was used to test the proposed framework and investigate its capabilities in the context of reinforced concrete buildings. The study demonstrated how the proposed QFD model could effectively enhance decision-making by managing the diversity of stakeholders’ preferences via design integration, enhanced communication and shared domain knowledge

BIM-embedded life cycle carbon assessment of RC buildings using optimised structural design alternatives

The implications of optimised structural designs in the life cycle carbon performance of buildings have been systematically overlooked in previous studies. The paper addresses this common limitation offering an integrated sustainable structural analysis at building level. To achieve this, a BIM-embedded approach was established utilising embodied carbon metrics and results from heuristic structural optimisation. A real building scenario was used to test the proposed approach in the context of multi-storey reinforced concrete (RC) buildings. Results show how the building life cycle performance is affected by the use of structurally optimised designs. The structural floors in particular, not only cover the largest proportion of the embodied carbon in the structure but they are also responsible for a large proportion of the carbon emissions of the tested building elements. The results obtained in this paper justified the need for more comprehensive efforts in the design optimisation of RC floors. Overall, it is suggested that the unclear interpretation of the optimisation outputs would result in the selection of structural designs that could compromise the buildings carbon performance

User Rofde Identification in Future Mobile Telecommunications Systems

Nevertheless, researchers are working for the specification of the Universal Mobile Telecommunications System (UMTS), which will be a third-generation system for mobile telecommunications. The UMTS [3] will provide a wide range of telecommunication services to a very large number of Mobile Users (MUS). Services highly comparable to those offered by fixed networks will be available via various Mobile Terminals (MTs). The UMTS will be a multi-operator system and will consist of a range of sub-networks, providing userswith access to different environments, according to the entitlement of the subscriptionswith which they are associated. As a user moves between sub-networks during a call, handover functions from one environment to another may take place [4]. Each of these environments has different technical and economic constraints and will require different solutions. In addition, the UMTS radio access point must be able to connect to or cooperate with fixed networks and be capable of operating as a stand-alone network for operation in non-B-ISDN environments, although itsintegrationwithB-ISDNisanobjectivefor UMTS. Other critical aspects of UMTS are the techniques used to store and manipulate the large amount of information involved, and the intelligence needed in order to control calls and cope with user and terminal mobility. In order to make use of a service, a UMTS user will be able to register on an MT for this particular service [5]. Since user registrations will be performed on a per service basis, a user may be registered on more than one MT for different services. Moreover, some types of UMTS terminals will support multiple user registrations,' but only one of the registered users will be allowed to make use of the terminal at a time. The UMTS will also support Universal Personal Telecommunications (UPT), which means that UPT users will be able to register onto (one or more) UMTS terminals in order to make and accept calls. The ability of a user to roam into the various UMTS environments and make use of the resources and services via different terminals will be checked every time this user enters an environment and/or uses resources and services. This means that an information entity must exist for every user so as to be retrieved every time such achecking is required. This user-related information entity is called the UMTS User Profile (UUP). The UUP is stored in the UMTS Distributed Data Base (UMTS DDB) and can be accessed from every point in the network.2 Management operations on a particular user profile can b e performed only by authorized UMTS operators and possibly by the subscriber concemedorbyauser authorizedbythissubscriber. A U U P includes user authentication information, service access information, access domain information, user charging and accounting information, etc. This article discusses the UMTS user profile identification issues. The authors introduce first the concept of user profile and the UMTS entities related to it. Then, the user profile is described and its management requirements are discussed followed by the description of two scenarios proposed for the user profile identification. Finally, the authors give a comparison of the two scenarios and their concluding remarks. The study of the impact of the proposed scenarios upon UMTS operators, subscribers, users, and mobile terminals is beyond the authors' intent for the scope of this article. Entities Related to the UMTS User Profile efore introducing the UMTS User Profile, we B attempt to identify a number of UMTS entities related to this concept

Automated specification of steel reinforcement to support the optimisation of RC floors

A Building Information Modelling (BIM)-enabled computational approach was presented in this paper for the automated specification of steel reinforcement to support the optimisation of reinforced concrete (RC) flat slabs. After importing slab geometries from BIM, the proposed procedure utilised internal forces output from Finite Element Model (FEM) to map required reinforcement in two stages. In the first stage, the reinforcement specifications matched the spatial resolution of the FEM. In the second, the reinforcement was adjusted by imposing constructability functions to limit the number of arrangements in terms of zones and bar spacing. The aim of the paper was to investigate the parametric capabilities of the proposed approach in the context of an optimisation model for the generation of material-efficient structural designs. Numerical examples were presented to demonstrate the efficiency of the automated specification procedure. The material efficiency and the design complexity of the developed reinforcement configurations were also assessed against a conventional solution under realistic design conditions

Investigating relationships between cost and CO₂ emissions in reinforced concrete structures using a BIM-based design optimisation approach

An integrated design approach for the cost and embodied carbon optimisation of reinforced concrete structures is presented in this paper to inform early design decisions. A BIM-based optimisation approach that utilises Finite Element Modelling (FEM) and a multi-objective genetic algorithm with constructability constraints is established for that purpose. A multilevel engineering analysis model is developed to perform structural layout optimisation, slab and columns sizing optimisation, and slab and columns reinforcement optimisation. The overall approach is validated using real buildings and the relationships between cost and carbon optimum solutions are explored. The study exhibits how cost effective and carbon efficient solutions could be obtained without compromising the feasibility of the optimised designs. Results demonstrate that the structural layout and the slab thickness are amongst the most important design optimisation parameters. Finally, the overall analysis suggests that the building form can influence the relationships between cost and carbon for the different structural components