Mining electric vehicle adoption of users

Rodrigues, R., Albuquerque, V., Ferreira, J. C., Dias, M. S., & Martins, A. L. (2021). Mining electric vehicle adoption of users. World Electric Vehicle Journal, 12(4), 1-31. [233]. https://doi.org/10.3390/wevj12040233 ------------------------------------------------------------------------------------- Funding Information: Funding: This research was funded by the Foundation for Science and Technology (FCT) through ISTAR-IUL’s project UIDB/04466/2020 and UIDP/04466/2020. Funding Information: Acknowledgments: J.C.F. received support from the Portuguese National Funds through FITEC— Programa Interface, with reference CIT INOV—INESC INOVAÇÃO—Financiamento Base. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.The increase of greenhouse gas emissions into the atmosphere, and their adverse effects on the environment, have prompted the search for alternative energy sources to fossil fuels. One of the solutions gaining ground is the electrification of various human activities, such as the transport sector. This trend has fueled a growing need for electrical energy storage in lithium batteries. Precisely knowing the degree of degradation that this type of battery accumulates over its useful life is necessary to bring economic benefits, both for companies and citizens. This paper aims to answer the current need by proposing two research questions about electric motor vehicles. The first focuses on habits EV owners practice, which may harm the battery life, and the second on factors that may keep consumers from purchasing this type of vehicle. This research work sought to answer these two questions, using a methodology from data science and statistical analysis applied to three surveys carried out on electric vehicle owners. The results allowed us to conclude that, except for the Year variable, all other factors had a marginal effect on the vehicles’ absolute autonomy degradation. Regarding obstacles of the adoption of electric vehicles, the biggest encountered was the insufficient coverage of the network of charging stations.publishersversionpublishe

Mining electric vehicle adoption of users

The increase of greenhouse gas emissions into the atmosphere, and their adverse effects on the environment, have prompted the search for alternative energy sources to fossil fuels. One of the solutions gaining ground is the electrification of various human activities, such as the transport sector. This trend has fueled a growing need for electrical energy storage in lithium batteries. Precisely knowing the degree of degradation that this type of battery accumulates over its useful life is necessary to bring economic benefits, both for companies and citizens. This paper aims to answer the current need by proposing two research questions about electric motor vehicles. The first focuses on habits EV owners practice, which may harm the battery life, and the second on factors that may keep consumers from purchasing this type of vehicle. This research work sought to answer these two questions, using a methodology from data science and statistical analysis applied to three surveys carried out on electric vehicle owners. The results allowed us to conclude that, except for the Year variable, all other factors had a marginal effect on the vehicles’ absolute autonomy degradation. Regarding obstacles of the adoption of electric vehicles, the biggest encountered was the insufficient coverage of the network of charging stations.info:eu-repo/semantics/publishedVersio

Are electric vehicle batteries being underused? A review of current practices and sources of circularity

The increasing demand for Lithium-ion batteries for Electric Vehicle calls for the adoption of sustainable practices and a switch towards a circular economy-based system to ensure that the electrification of transportation does not come at a high environmental cost. While driving patterns have not changed much over the years, the current Electric Vehicle market is evolving towards models with higher battery capacities. In addition, these batteries are considered to reach the End of Life at 70–80% State of Health, regardless of their capacity and application requirements. These issues may cause an underuse of the batteries and, therefore, hinder the sustainability of the Electric Vehicle. The goal of this study is to review and compare the circular processes available around Electric Vehicle batteries. The review highlights the importance of prioritizing the first-life of the battery onboard, starting with reducing the nominal capacity of the models. In cases where the battery is in risk of reaching the End of Life with additional value, Vehicle to Grid is encouraged over the deployment of second-life applications, which are being strongly promoted through institutional fundings in Europe. As a result of the identified research gaps, the methodological framework for the estimation of a functional End of Life is proposed, which constitutes a valuable tool for sustainable decision-making and allows to identify a more accurate End of Life, rather than considering the fixed threshold assumed in the literature.This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 963580. This funding includes funds to support research work and openaccess publications.Peer ReviewedPostprint (published version

Online battery state of power prediction using PRBS and extended Kalman filter

This paper presents a hybrid battery parametrisation technique for the purpose of battery state-of-charge (SOC) and state-of-power (SOP) monitoring in real time. The proposed technique is centred around an opportunistic initialisation of a dual Extended Kalman Filter (DEKF) algorithm using Pseudo Random Binary Sequence (PRBS) battery excitation. A Second-order electrical equivalent-circuit battery model is used whose parameters are identified using a carefully designed 10-bit 10-Hz PRBS signal while the battery is in a zero- or low-current quiescent mode. The PRBS-identified resistive elements of the battery model are then utilised to provide an initial estimate for the battery's SOP. Once in load conditions, the DEKF algorithm is implemented recursively to provide an accurate estimate of the battery's parameters, SOC and subsequently its SOP in real time. The experimental results obtained form an electrochemical impedance spectroscopy (EIS) method give confidence to the performance of the proposed hybrid battery parametrisation technique

Remaining useful life estimations applied on the sizing and the prognosis of lithium ion battery energy storage systems

The present thesis develops an accurate sizing tool for the most relevant lithium ion battery energy storage system applications considering the aging and the remaining useful life. The developed tool involves firstly, the construction of the aging models of the lithium ion battery health indicators; secondly, the calculation of the end of life based on the evolution of the modelled health indicators; thirdly, the calculation of the levelized cost of the most relevant applications of lithium ion battery energy storage systems; and fourthly, the minimization of the committed error with the constructed aging models supported by electrode level data and prognosis algorithms. The methodology behind the construction and calculation of all the elements integrated on the sizing tool is described throughout the chapters of this thesis. Firstly, the end of life state of the battery is determined as a combined threshold of all the health indicators of interest. Its calculation requires the implementation of an electro-thermal model in a simulation environment defined by the end of life criteria specified by the application requirements. Secondly, the evolution of health indicators of interest are modelled based on the most relevant stress factors. The methodology to acquire the aging data and the construction of the posterior empirical models are presented. The validation of the constructed models based on the acquired data is performed based on three aspects: the accuracy describing the observed cases, the correctness of interpolations and the real life applicability. Thirdly, the simulation environments for lithium ion battery energy storage systems applied on an electric vehicle application and on a stationary application are developed where the levelized cost of different battery solution sizes is calculated. The simulation environment integrates the already developed electric-thermal model, end of life map and aging models. Fourthly, the error done by the constructed aging models is minimized by focusing on the errors done when extrapolating in time and when facing odd events. On one hand, electrode level data is analysed to generate data artificially and reduce the errors when extrapolating in time. On the other hand, a prognosis stochastic algorithm is selected and employed with real life data to deal with the effect that odd events have on the evolution of the health indicators. The validity of many assumptions made for the development of the end of life map, the aging models, the simulation environment used on the sizing tool, the artificial data generator and the real time prognosis tool are proved experimentally