scholarly journals Passenger Car Energy Demand Assessment: a New Approach Based on Road Traffic Data

2020 ◽  
Vol 197 ◽  
pp. 05006
Author(s):  
Umberto Previti ◽  
Sebastian Brusca ◽  
Antonio Galvagno
Keyword(s):  
Energy Management ◽  
Energy Demand ◽  
Electric Propulsion ◽  
Road Traffic ◽  
Driving Cycle ◽  
City Centre ◽  
Automotive Market ◽  
Driving Cycles ◽  
Traffic Level ◽  
The One

Nowadays the automotive market is oriented to the production of hybrid or electric propulsion vehicle equipped with Energy Management System that aims to minimize the consumption of fossil fuel. The EMS, generally, performs a local and not global optimization of energy management due to the impossibility of predicting the user’s energy demand and driving conditions. The aim of this research is to define a driving cycle (speed time) knowing only the starting and the arrival point defined by the driver, considering satellite data and previous experiences. To achieve this goal, the data relating to the energy expenditure of a car (e.g. speed, acceleration, road inclination) will be acquired, using on-board acquisition system, during road sections in the city of Messina. At the same time, the traffic level counterplot and others information provided, for these specific sections, from GPS acquisition software will be collected. On-board and GPS data will be compared and, after considering an adequate number of acquisitions, each value of the traffic level will be associated with a driving cycle obtained by processing the acquired data. After that, the numerical model of a car will be created which will be used to compare the energy demand of two driving cycles. The first one acquired on a section with a random starting and destination point inside the historic city centre of Messina. The second is the one assigned, for that same section, considering only the value of the traffic level counterplot.

scholarly journals A Neural Network Fuzzy Energy Management Strategy for Hybrid Electric Vehicles Based on Driving Cycle Recognition

2020 ◽  
Vol 10 (2) ◽  
pp. 696
Author(s):  
Qi Zhang ◽  
Xiaoling Fu
Keyword(s):  
Neural Network ◽  
Energy Management ◽  
Membership Function ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Fuzzy Energy

Aiming at the problems inherent in the traditional fuzzy energy management strategy (F-EMS), such as poor adaptive ability and lack of self-learning, a neural network fuzzy energy management strategy (NNF-EMS) for hybrid electric vehicles (HEVs) based on driving cycle recognition (DCR) is designed. The DCR was realized by the method of neural network sample learning and characteristic parameter analysis, and the recognition results were considered as the reference input of the fuzzy controller with further optimization of the membership function, resulting in improvement in the poor pertinence of F-EMS driving cycles. The research results show that the proposed NNF-EMS can realize the adaptive optimization of fuzzy membership function and fuzzy rules under different driving cycles. Therefore, the proposed NNF-EMS has strong robustness and practicability under different driving cycles.

scholarly journals User-Related Issues in Design and Use of Smartgrids Seen as Complex Sociotechnical Systems: Example of the VERTPOM Project

2020 ◽  
Vol 13 (4) ◽  
pp. 76
Author(s):  
Emilie Loup-Escande ◽  
Sophie Capo ◽  
Helios Raharison
Keyword(s):  
Energy Management ◽  
Energy Demand ◽  
Fossil Fuels ◽  
Sociotechnical Systems ◽  
Positive Energy ◽  
User Centered Design ◽  
Consumer Control ◽  
The One ◽  
And Control ◽  
The Impact

The impact of human activities on the environment is no longer to be demonstrated today and concerns many fields. With a view to environmental protection, applied to global warming limitation and fossil fuels preservation, Smartgrids are currently emerging, especially, under the impetus of European and French legislation. In emerging technologies, end-user-related issues, articulated with the design process, continue to raise conceptual, methodological and operational questions. The perspective of complex sociotechnical systems is useful for Smartgrids and to underline the necessary multidisciplinary approach to design. Yet raised for decades, the articulation of multidisciplinary approaches in the design of complex systems still questions fundamental problems today. These questions are all more unresolved in the context of innovative technologies such as Smartgrids. The objective of this paper is to propose 1) a conceptual reflection applied to the design of these Smartgrids seen as emerging sociotechnical systems, and 2) a case study by illustrating with the VERTPOM project. On the one hand, we discuss four fundamental points in user-centered design of Smartgrids: we describe the legislative impulses for the rollout of smart metters and the emergence of Smartgrids, we highlight the supplier/consumer synergy that is essential for efficient energy management, we explain the importance of adapting systems to the wide public in domestic, professional and public situations in the context of consumer control of energy demand, and we address the issue of the more traditional field of supervision and control of complex dynamic processes by operators. On the other hand, we present the VERTPOM project aiming at developing a set of digital tools for energy management and energy efficiency in order to make a positive energy territory that produces more energy than it consumes by introducing the project and its actors and explaining how design acceptable Smartgrids for consumers and operators of energy suppliers.

An outlook of electric vehicle daily use in the framework of an energy management system

2015 ◽  
Vol 26 (4) ◽  
pp. 588-606 ◽  
Author(s):  
Hugo Neves de Melo ◽  
João P. Trovão ◽  
Carlos Henggeler Antunes ◽  
Paulo G. Pereirinha ◽  
Humberto M. Jorge
Keyword(s):  
Energy Management ◽  
Energy Demand ◽  
Free Market ◽  
End Users ◽  
Driving Cycle ◽  
Special Focus ◽  
Sustainable Mobility ◽  
Content Type ◽  
Energy Management Systems ◽  
Trade Offs

Purpose – The purpose of this paper is to present a prospective study of sustainable mobility in the framework of a supporting energy management systems (EMS). Technological advances are still required, namely electric vehicles (EV) endowed with improved EMS in order to increase their performance by making the most of available energy storage technologies. As EVs may be seen as a special domestic load, EMS are proposed based on demand-sensitive pricing strategies such as the Energy Box discussed in this paper. Design/methodology/approach – The study presents an overview of electric mobility and an urban EV project, with special focus on the utilization of its energy sources and their relation with the energy demand of a typical urban driving cycle. Results based on the ECE 15 standard driving cycle for different free market electricity tariffs are presented. Findings – The analysis based on present Portuguese power and energy tariffs reveals that it is highly questionable whether the resulting profit will be enough to justify the potential inconveniences to the vehicle user, as well as those resulting from the increased use of batteries. Practical implications – The conclusions indicate that more studies on the trade-offs between grid to vehicle and vehicle to grid schemes and electricity pricing mechanisms are needed in order to understand how the utilization of EVs can become more attractive in the end-users’ and utilities’ perspectives. Originality/value – The paper proposes an approach for future electricity tariff behavior that could be applied to EVs in order to understand whether or not their grid integration in charge and discharge situations would be beneficial for end-users and utilities, in the framework of smart energy management technologies.

The Driving Cycle Characteristic Parameters Research for Hybrid Electric Vehicle

2012 ◽  
Vol 462 ◽  
pp. 271-276 ◽  
Author(s):  
Nan Zhou ◽  
Qing Nian Wang ◽  
Peng Yu Wang
Keyword(s):  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Uniform Design ◽  
Driving Cycle ◽  
Control Algorithms ◽  
Characteristic Parameters ◽  
Simulation Experiments ◽  
Management Algorithm ◽  
Driving Cycles ◽  
And Control

The study on standard driving cycles is of great significance on design and control algorithms for HEV. This article applies the theory of uniform design on the driving cycle parameters research. According to the uniform design scheme for driving cycle parameters, not only greatly reduce the number of simulation experiments, by analyzing the experiment results, but also efficiently and intuitively identify the primary and secondary factors of driving cycle experiment parameters. Through the relevant energy management algorithm, simulation proves that the driving cycle parameters research on HEV is significance to improve the fuel economy.

scholarly journals Sustainable Energy-Related Infrastructure Development in the Mekong Subregion: Key Drivers and Policy Implications

2021 ◽  
Vol 13 (10) ◽  
pp. 5720
Author(s):  
Han Phoumin ◽  
Sopheak Meas ◽  
Hatda Pich An
Keyword(s):  
Carbon Dioxide Emissions ◽  
Energy Demand ◽  
Power Plants ◽  
Policy Implications ◽  
Infrastructure Investment ◽  
Infrastructure Development ◽  
Low Carbon ◽  
Energy Access ◽  
Low Carbon Economy ◽  
The One

Many players have supported infrastructure development in the Mekong Subregion, bridging the missing links in Southeast Asia. While the influx of energy-related infrastructure development investments to the region has improved the livelihoods of millions of people on the one hand, it has brought about a myriad of challenges to the wider region in guiding investments for quality infrastructure and for promoting a low-carbon economy, and energy access and affordability, on the other hand. Besides reviewing key regional initiatives for infrastructure investment and development, this paper examines energy demand and supply, and forecasts energy consumption in the subregion during 2017–2050 using energy modeling scenario analysis. The study found that to satisfy growing energy demand in the subregion, huge power generation infrastructure investment, estimated at around USD 190 billion–220 billion, is necessary between 2017 and 2050 and that such an investment will need to be guided by appropriate policy. We argue that without redesigning energy policy towards high-quality energy infrastructure, it is very likely that the increasing use of coal upon which the region greatly depends will lead to the widespread construction of coal-fired power plants, which could result in increased greenhouse gas and carbon dioxide emissions.

scholarly journals Understanding Spatial Variability of NO2 in Urban Areas Using Spatial Modelling and Data Fusion Approaches

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 179
Author(s):  
Said Munir ◽  
Martin Mayfield ◽  
Daniel Coca
Keyword(s):  
Data Fusion ◽  
Spatial Variability ◽  
Urban Areas ◽  
Road Traffic ◽  
Dispersion Model ◽  
Low Cost ◽  
Spatial Modelling ◽  
City Centre ◽  
Small Scale ◽  
The City

Small-scale spatial variability in NO2 concentrations is analysed with the help of pollution maps. Maps of NO2 estimated by the Airviro dispersion model and land use regression (LUR) model are fused with measured NO2 concentrations from low-cost sensors (LCS), reference sensors and diffusion tubes. In this study, geostatistical universal kriging was employed for fusing (integrating) model estimations with measured NO2 concentrations. The results showed that the data fusion approach was capable of estimating realistic NO2 concentration maps that inherited spatial patterns of the pollutant from the model estimations and adjusted the modelled values using the measured concentrations. Maps produced by the fusion of NO2-LCS with NO2-LUR produced better results, with r-value 0.96 and RMSE 9.09. Data fusion adds value to both measured and estimated concentrations: the measured data are improved by predicting spatiotemporal gaps, whereas the modelled data are improved by constraining them with observed data. Hotspots of NO2 were shown in the city centre, eastern parts of the city towards the motorway (M1) and on some major roads. Air quality standards were exceeded at several locations in Sheffield, where annual mean NO2 levels were higher than 40 µg/m3. Road traffic was considered to be the dominant emission source of NO2 in Sheffield.

Machine Learning and statistic predictive modeling for road traffic flow

2021 ◽  
Vol 03 (01) ◽  
pp. 17-24
Author(s):  
Nadia Slimani ◽  
Ilham Slimani ◽  
Nawal Sbiti ◽  
Mustapha Amghar
Keyword(s):  
Road Traffic ◽  
Smart Cities ◽  
Moving Average ◽  
Ann Model ◽  
Important Place ◽  
Traffic Forecasting ◽  
Absolute Relative Error ◽  
History Of ◽  
The One ◽  
Motorized Vehicles

Traffic forecasting is a research topic debated by several researchers affiliated to a range of disciplines. It is becoming increasingly important given the growth of motorized vehicles on the one hand, and the scarcity of lands for new transportation infrastructure on the other. Indeed, in the context of smart cities and with the uninterrupted increase of the number of vehicles, road congestion is taking up an important place in research. In this context, the ability to provide highly accurate traffic forecasts is of fundamental importance to manage traffic, especially in the context of smart cities. This work is in line with this perspective and aims to solve this problem. The proposed methodology plans to forecast day-by-day traffic stream using three different models: the Multilayer Perceptron of Artificial Neural Networks (ANN), the Seasonal Autoregressive Integrated Moving Average (SARIMA) and the Support Machine Regression (SMOreg). Using those three models, the forecast is realized based on a history of real traffic data recorded on a road section over 42 months. Besides, a recognized traffic manager in Morocco provides this dataset; the performance is then tested based on predefined criteria. From the experiment results, it is clear that the proposed ANN model achieves highest prediction accuracy with the lowest absolute relative error of 0.57%.

Energy Management System for Hybrid Microgrids

2021 ◽  
Vol 69 (2) ◽  
pp. 21-30
Author(s):  
Nasreddine ATTOU ◽  
Sid-Ahmed ZIDI ◽  
Mohamed KHATIR ◽  
Samir HADJERI
Keyword(s):  
Energy Management ◽  
Electricity Market ◽  
Management System ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Energy Sources ◽  
Variable Load ◽  
Energy Management System ◽  
Price Variation

Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

Development of a Driving Cycle for Amman City With Performance Evaluation for ICE Vehicle

2014 ◽  
Author(s):  
M. Abu Mallouh ◽  
B. W. Surgenor ◽  
E. Abdelhafez ◽  
M. Salah ◽  
M. Hamdan
Keyword(s):  
Performance Evaluation ◽  
Fuel Cell ◽  
Fuel Economy ◽  
Performance Comparison ◽  
Driving Cycle ◽  
Accurate Estimation ◽  
Accurate Evaluation ◽  
Driving Cycles ◽  
Considerable Research ◽  
Future Work

A good driving cycle is needed for accurate evaluation of a vehicle’s performance in terms of emission and fuel consumption. Driving cycles obtained for certain cities or countries are not usually applicable to other cities or countries. Therefore, considerable research has been conducted on developing driving cycles for certain cities and regions. In this paper, a driving cycle for a taxi in Amman city, the capital of Jordan, is developed. Significant differences are noted when comparing the Amman driving cycle with other driving cycles. A model of a gasoline powered vehicle is used to conduct a performance comparison in terms of fuel economy and emissions utilizing the developed Amman driving cycle and six other worldwide driving cycles. The developed Amman driving cycle is very useful in obtaining accurate estimation of fuel economy and emissions for vehicles running on Amman roads and will be used in future work to study the performance of hybrid fuel cell/ battery vehicles.

Sign in / Sign up

Export Citation Format

Share Document