  Citation: Croce, A.I.; Musolino, G.; Rindone, C.; Vitetta, A. Traffic and Energy Consumption Modelling of Electric Vehicles: Parameter Updating from Floating and Probe Vehicle Data. Energies 2022, 15, 82. https://doi.org/10.3390/en15010082 Academic Editor: Balázs Németh Received: 20 November 2021 Accepted: 16 December 2021 Published: 23 December 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article Traffic and Energy Consumption Modelling of Electric Vehicles: Parameter Updating from Floating and Probe Vehicle Data Antonello Ignazio Croce 1 , Giuseppe Musolino 2, * , Corrado Rindone 2 and Antonino Vitetta 2 1 Dipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Feo di Vito, 89122 Reggio Calabria, Italy; antonello.croce@unirc.it 2 Dipartimento di ingegneria dell’Informazione, delle Infrastrutture e dell’Energia Sostenibile, Università degli Studi Mediterranea di Reggio Calabria, Feo di Vito, 89122 Reggio Calabria, Italy; corrado.rindone@unirc.it (C.R.); vitetta@unirc.it (A.V.) * Correspondence: giuseppe.musolino@unirc.it; Tel.: +39-096-5169-3272 Abstract: This paper focuses on the estimation of energy consumption of Electric Vehicles (EVs) by means of models derived from traffic flow theory and vehicle locomotion laws. In particular, it proposes a bi-level procedure with the aim to calibrate (or update) the whole parameters of traffic flow models and energy consumption laws by means of Floating Car Data (FCD) and probe vehicle data. The reported models may be part of a procedure for designing and planning transport and energy systems. This aim is to verify if, and in what amount, the existing parameters of the resistances/energy consumptions model calibrated in the literature for Internal Combustion Engines Vehicles (ICEVs) change for EVs, considering the above circular dependency between supply, demand, and supply–demand interaction. The final results concern updated parameters to be used for eco-driving and eco-routing applications for design and a planning transport system adopting a multidisciplinary approach. The focus of this manuscript is on the transport area. Experimental data concern vehicular data extracted from traffic (floating car data and probe vehicle data) and energy consumption data measured for equipped EVs performing trips inside a sub-regional area, located in the Città Metropolitana of Reggio Calabria (Italy). The results of the calibration process are encouraging, as they allow for updating parameters related to energy consumption and energy recovered in terms of EVs obtained from data observed in real conditions. The latter term is relevant in EVs, particularly on urban routes where drivers experience unstable traffic conditions. Keywords: sustainable mobility; smart energy; energy consumption models; traffic flow models; internal combustion engines vehicles (ICEVs); electric vehicles (EVs); floating car data (FCD); probe vehicle data 1. Introduction Mobility of people and goods inside a smart energy environment is a cross-cutting issue to be addressed in order to help achieve the 2030 agenda for sustainable development. Transport infrastructure and services are means allowing people and business to access destinations (e.g., workplaces, schools, markets) in order to perform activities. At the same time, these means require natural, economic and financial resources. Among them, energy resources are crucial, in order to reach sustainability ([1,2]). Electric Vehicles (EVs) play a relevant role in sustainable mobility. In recent years, there has been an increasing use of EVs in the mobility of people and goods, and they are replacing traditional internal combustion engine vehicles (ICEVs). This evolution has several implications in the so-called tank-to-wheel process. This paper focuses on energy consumption for mobility. Particular attention is devoted to the estimation of energy consumption of EVs by means of models derived from traffic flow theory and vehicle locomotion laws. The objective is to calibrate (or update) the whole parameters of traffic flow models, vehicle locomotion laws and energy consumption by means of Floating Car Data (FCD), and probe vehicle data. Energies 2022, 15, 82. https://doi.org/10.3390/en15010082 https://www.mdpi.com/journal/energies