Prediction of Electric Vehicle Energy Consumption in an Intelligent and Connected Environment

Accurate energy consumption prediction is essential for improving the driving experience. In the urban road scenario, we discussed the influencing factors of energy consumption and divided the modes from various perspectives. The differences in energy consumption characteristics and distribution laws for electric vehicles using the IDM and CACC car-following models under different traffic flows are compared. An energy consumption prediction framework based on the LightGBM model is proposed. According to the study, driving range, acceleration, accelerating time, decelerating time and cruising time all significantly impact the overall energy consumption of electric vehicles. There are apparent differences in energy consumption characteristics and distribution laws under different traffic flows: average energy consumption is lower under low flow and increased under high flow. The CACC-electric vehicles consume more energy in low flow than IDM-electric vehicles. Under high flow, the opposite is true. The results show that the proposed framework has a high accuracy: the MAPE based on IDM datasets is 3.45% and the RMSE is 0.039 kWh; the MAPE based on CACC datasets is 5.57% and the RMSE is 0.042 kWh. The MAPE and RMSE are reduced by 33.7% and 50.6% (maximum extent) compared to the best comparison algorithm

Intelligent Usage of Internal Combustion Engines in Hybrid Electric Vehicles

none1The chapter describes the optimal usage of an internal combustion engine in an intelligent hybrid electric vehicle able to sense its surrounding and adapt the energy management strategy to the actual driving conditions. After an introduction on hybrid electric vehicles and their challenges, the chapter describes the role of Information and Communication Technologies in the reduction of greenhouse emissions. Then, the chapter focuses on different approaches presented in literature on the usage of information about traffic and weather conditions for the optimal energy management of hybrid electric vehicles. In particular, the chapter describes the application of the prediction&maps approach developed at the University of Salento for the optimization of the engine usage in the ITAN500 plug-in hybrid electric vehicle. Finally, the chapter proposes four metrics to evaluate the performance of the proposed method: the percentage of mission performed before reaching the lowest allowed value for battery state of charge (CBD%), the percentage of mission execute with the engine turned ON (EngON%), the average efficiency of the engine (AEE), calculated according to its actual temperature and the overall well-to-wheel emissions of CO2.T.DonateoDonateo, Teres

Internal Combustion Engines

This book on internal combustion engines brings out few chapters on the research activities through the wide range of current engine issues. The first section groups combustion-related papers including all research areas from fuel delivery to exhaust emission phenomena. The second one deals with various problems on engine design, modeling, manufacturing, control and testing. Such structure should improve legibility of the book and helps to integrate all singular chapters as a logical whole

Electrification of Smart Cities

Electrification plays a key role in decarbonizing energy consumption for various sectors, including transportation, heating, and cooling. There are several essential infrastructures for a smart city, including smart grids and transportation networks. These infrastructures are the complementary solutions to successfully developing novel services, with enhanced energy efficiency and energy security. Five papers are published in this Special Issue that cover various key areas expanding the state-of-the-art in smart cities’ electrification, including transportation, healthcare, and advanced closed-circuit televisions for smart city surveillance

Experimental Characterisation of Real Driving Cycles in Diesel Passenger Vehicles under Different Environmental Conditions

[ES] El futuro de los Motores de Combustión Interna en el sector de la automoción parece incierto, en cierta medida, debido a los cambios recientes en las normativas de homologación. Las regulaciones actuales han reducido considerablemente los límites de emisiones contaminantes , así como también han introducido pruebas más exigentes. La introducción de ciclos de conducción reales supuso un reto para los fabricantes de automóviles a la hora de homologar sus vehículos, ya que el tradicional y poco exigente ciclo de certificación del New European Driving Cycle (NEDC) ha sido sustituido por ciclos más severos como el World Light-Duty Test Cycle (WLTC) y Real Driving Emissions (RDE). Este estudio, en primer lugar, presenta una metodología para implementar ciclos RDE en un banco de ensayos de motores. Aun sabiendo que la esencia de la regulación RDE es evaluar las condiciones reales de conducción, reproducir los ciclos RDE en un banco de pruebas es de gran interés ya que las condiciones controladas y reproducibles que se pueden lograr en un laboratorio aportan información valiosa para entender el comportamiento del motor en conducción real, y por lo tanto contribuyen al desarrollo del motor. Este documento aplica la normativa más reciente de la Comunidad Europea y establece los pasos imprescindibles para realizar un ciclo RDE en un banco de pruebas de motores. En segundo lugar, gracias a que se ha demostrado la viabilidad de una sala de pruebas para realizar ciclos RDE, se han realizado diferentes ciclos RDE bajo diferentes solicitaciones dinámicas y condiciones externas como tempera- tura ambiente o temperatura del aire de admisión. Posteriormente, se analizó la emisión de contaminantes y el consumo de combustible con el fin de caracterizar los ciclos y condiciones de RDE. Además, se ha llevado a cabo una comparación de las emisiones y el consumo de combustible de las pruebas RDE frente a las obtenidas en las pruebas de estado estacionario, donde se encontraron discrepancias bastante bajas[CA] El futur dels Motors de Combustió Interna al sector de l'automoció sembla incert, en certa mesura, a causa dels canvis recents a les normatives d'homologació. Les regulacions actuals han reduït considerablement els límits d'emissions contaminants i també han introduït proves més exigents. La introducció de cicles de conducció reals va suposar un repte per als fabricants d'automòbils a l'hora d'homologar els seus vehicles, ja que el tradicional i poc exigent cicle de certificació del New European Driving Cycle (NEDC) ha estat substituït per cicles més severs com el World Light-Duty Test Cycle (WLTC) i Real Driving Emissions (RDE). Aquest estudi, en primer lloc, presenta una metodologia per implemen- tar cicles RDE a un banc d'assajos de motors. Tot i saber que l'essència de la regulació RDE és avaluar les condicions reals de conducció, reproduir els cicles RDE en un banc de proves és de gran interès ja que les condicions controlades i reproduïbles que es poden aconseguir en un laboratori aporten informació valuosa per entendre el comportament del motor en conducció real, i per tant contribueixen al desenvolupament del motor. Aquest document aplica la normativa més recent de la Comunitat Europea i estableix els passos imprescindibles per fer un cicle RDE en un banc de proves de motors. En segon lloc, gràcies al fet que s'ha demostrat la viabilitat d'una sala de proves per fer cicles RDE, s'han realitzat diferents cicles RDE sota diferents sol·licitacions dinàmiques i condicions externes com ara temperatura ambient o temperatura de l'aire d'admissió. Posteriorment, es va analitzar l'emissió de contaminants i el consum de combustible per tal de caracteritzar els cicles i les condicions de RDE. A més, s'ha dut a terme una comparació de les emissions i el consum de combustible de les proves RDE davant de les obtingudes a les proves d’estat estacionari, on es van trobar discrepàncies força baixes-[EN] The future of Internal Combustion Engines in the automotive sector seems uncertain, to some extent, due to the recent changes in type approval regulations. Current regulations have considerably reduced the engine pollutant emissions limits, as well as introduced more demanding testing conditions. The introduction of real driving cycles presented a challenging issue for car manufacturers when homologating their vehicles, since the traditional and undemanding New European Driving Cycle (NEDC) certification cycle has been replaced by more severe cycles such as World Light-Duty Test Cycle (WLTC) and Real Driving Emissions (RDE). This study, in the first place, presents a methodology for implementing RDE cycles in an engine test bench. Even knowing that the essence of RDE regulation is to assess actual driving conditions, reproducing RDE cycles in a test bench is of great interest since, the controlled and reproducible conditions that can be achieved in a laboratory lead to valuable information to understand engine behaviour in real driving conditions, and therefore contribute to engine development. This document applies the most recent European Community regulation and sets the essential steps to carry out an RDE cycle in an engine test bench. Secondly, as the feasibility of a test bench to perform RDE cycles has been proven, different RDE cycles have been performed under different dynamic solicitations and external conditions such as ambient or intake air temperatures. After that, the pollutant's emission and fuel mass consumption were analysed with the aim of characterising RDE cycles and conditions. Furthermore, a comparison of RDE test emissions and fuel consumption versus those obtained from steady-state tests has been carried out, where very small discrepancies were found.Redondo Puelles, F. (2023). Experimental Characterisation of Real Driving Cycles in Diesel Passenger Vehicles under Different Environmental Conditions [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19665

Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact

Recent trends in vehicle engineering are testament to the great efforts that scientists and industries have made to seek solutions to enhance both the performance and safety of vehicular systems. This Special Issue aims to contribute to the study of modern vehicle dynamics, attracting recent experimental and in-simulation advances that are the basis for current technological growth and future mobility. The area involves research, studies, and projects derived from vehicle dynamics that aim to enhance vehicle performance in terms of handling, comfort, and adherence, and to examine safety optimization in the emerging contexts of smart, connected, and autonomous driving.This Special Issue focuses on new findings in the following topics:(1) Experimental and modelling activities that aim to investigate interaction phenomena from the macroscale, analyzing vehicle data, to the microscale, accounting for local contact mechanics; (2) Control strategies focused on vehicle performance enhancement, in terms of handling/grip, comfort and safety for passengers, motorsports, and future mobility scenarios; (3) Innovative technologies to improve the safety and performance of the vehicle and its subsystems; (4) Identification of vehicle and tire/wheel model parameters and status with innovative methodologies and algorithms; (5) Implementation of real-time software, logics, and models in onboard architectures and driving simulators; (6) Studies and analyses oriented toward the correlation among the factors affecting vehicle performance and safety; (7) Application use cases in road and off-road vehicles, e-bikes, motorcycles, buses, trucks, etc

Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project

A survey of free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle

The objective of this paper is to analyze free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle (UAV). Free software is the best choice when the reduction of production costs is necessary; nevertheless, the quality of free software may vary. This paper probably does not include all of the free software, but tries to describe or mention at least the most interesting programs. The first part of this paper summarizes the essential knowledge about UAVs, including the fundamentals of flight mechanics and aerodynamics, and the structure of a UAV system. The second section generally explains the modelling and simulation of a UAV. In the main section, more than 50 free programs for the design, analysis, modelling, and simulation of a UAV are described. Although the selection of the free software has been focused on small subsonic UAVs, the software can also be used for other categories of aircraft in some cases; e.g. for MAVs and large gliders. The applications with an historical importance are also included. Finally, the results of the analysis are evaluated and discussed—a block diagram of the free software is presented, possible connections between the programs are outlined, and future improvements of the free software are suggested. © 2015, CIMNE, Barcelona, Spain.Internal Grant Agency of Tomas Bata University in Zlin [IGA/FAI/2015/001, IGA/FAI/2014/006

Analysis of Near-Surface Relative Humidity in a Wind Turbine Array Boundary Layer Using an Instrumented Unmanned Aerial System and Large-Eddy Simulation

Previous simulations have shown that wind farms have an impact on the near-surface atmospheric boundary layer (ABL) as turbulent wakes generated by the turbines enhance vertical mixing of momentum, heat and moisture. These changes alter downstream atmospheric properties. With the exception of a few observational data sets that focus on the impact to near-surface temperature within wind farms, little to no observational evidence exists with respect to vertical mixing. These few experimental studies also lack high spatial resolution due to their use of a limited number of meteorological sensors or remote sensing techniques. This study utilizes an instrumented small unmanned aerial system (sUAS) to gather high resolution in-situ field measurements from two state-of-the-art Midwest wind farms in order to differentially map downstream changes to relative humidity. These measurements are complemented by numerical experiments conducted using large eddy simulation (LES). Observations and numerical predictions are in good general agreement around a single wind turbine and show that downstream relative humidity is altered in the vertical, lateral, and downstream directions. A suite of LES is then performed to determine the effect of a turbine array on the relative humidity distribution in compounding wakes. In stable and neutral conditions, and in the presence of a positive relative humidity lapse rate, it is found that the humidity decreases below the turbine hub height and increases above the hub height. As the array is transitioned, the magnitude of change increases, differentially grows on the left-hand and right-hand side of the wake, and move slightly upward with downstream distance. In unstable conditions, the magnitude of near-surface decrease in relative humidity is a full order of magnitude smaller than that observed in a stable atmospheric regime

IoT-driven scheduling of residential HVAC and virtual bus lanes for energy savings

The availability of commodity Internet connection and the decrease in price and form factor of consumer electronics led to the emergence of Internet of Things (IoT), with which our world becomes more connected and instrumented. IoT is a great vehicle for enabling solutions to problems in the connected environment that surrounds us (i.e., smart homes and smart cities). An example is the use of sensors and IoT to address issues related to energy efficiency, the broad area of this dissertation. Our hypothesis is that data processing and decision making need to be carried out at the network edge, specifically as close to the physical system as possible, where data are generated and used, to produce results in real-time and make sure the data is not exposed to privacy and security risks. To this end, we propose to leverage scheduling principles and statistical techniques in the context of two applications, namely aiming to reduce duty cycle of HVAC (Heating, Ventilation, and Air Conditioning) systems in smart homes and to mitigate road congestion in smart cities. The common goal in these two aims is the reduction of energy consumption and the reduction of atmospheric pollution. To achieve our first aim we propose intelligent scheduling of the duty cycles of HVAC systems in residential buildings. Our solution combines linear and polynomial regression enabled estimator that drives the calculations about the amounts of time thermally conditioned air should be supplied to each room. The output from our estimator is fed into our scheduler based on integer linear programming to decrease the duty cycle of the home's HVAC systems. We evaluate the effectiveness and efficiency of our HVAC solution with a dataset collected from several residential houses in the state of Pennsylvania. To achieve the second aim, we propose the concept of virtual bus lanes, that combines on-demand creation of bus lanes with dynamic control of traffic lights. Moreover, we propose to guide drivers through less congested routes using light boards that provide to drivers information in real-time for such routes. Our methods are anchored to priority scheduling, incremental windowed-based aggregation, and shortest path first Dijkstra's algorithm. We evaluate the effectiveness and efficiency of our virtual bus lanes solution with a real dataset from the city of Beijing, China, and a synthetic traffic scenario from the city of Luxembourg