scholarly journals Neuro-Fuzzy System for Energy Management of Conventional Autonomous Vehicles

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1745 ◽  
Author(s):  
Duong Phan ◽  
Alireza Bab-Hadiashar ◽  
Reza Hoseinnezhad ◽  
Reza N. Jazar ◽  
Abhijit Date ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Autonomous Vehicles ◽  
Pid Controller ◽  
Autonomous Vehicle ◽  
Subtractive Clustering ◽  
Energy Management System ◽  
Power Demand ◽  
Neuro Fuzzy ◽  
Simulation Results

This paper investigates the energy management system (EMS) of a conventional autonomous vehicle, with a view to enhance its powertrain efficiency. The designed EMS includes two neuro-fuzzy (NF) systems to produce the optimal torque of the engine. This control system uses the dynamic road power demand of the autonomous vehicle as an input, and a PID controller to regulate the air mass flow rate into the cylinder by changing the throttle angle. Two NF systems were trained by the Grid Partition (GP) and the Subtractive Clustering (SC) methods. The simulation results show that the proposed EMS can reduce the fuel consumption of the vehicle by 6.69 and 6.35 l/100 km using the SC and the GP, respectively. In addition, the EMS based on NF trained by GP and NF trained by SC can reduce the fuel consumption of the vehicle by 11.8% and 7.08% compared with the case without the controller, respectively.

scholarly journals Energy management system and supervision in a micro-grid using artificial neural network technique

2021 ◽  
Vol 12 (4) ◽  
pp. 2570
Author(s):  
Ezzitouni Jarmouni ◽  
Ahmed Mouhsen ◽  
Mohammed Lamhammedi ◽  
Hicham Ouldzira
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Management Technique ◽  
Energy Management System ◽  
Power Demand ◽  
Random Behavior ◽  
New Energy ◽  
Variable Power ◽  
Artificial Neural ◽  
Real Challenge

Nowadays, the combination of conventional and renewable energy sources such as solar energy is one of the most widespread solutions to surmount the challenge of the climate and energy crisis. In the presence of random behavior of photovoltaic systems and variable power demand by consumers, energy management is a real challenge. In this paper, we propose a new energy management technique based on artificial neural networks in a smart grid. This will ensure the continuous supply of electricity to the consumer in the presence of random operation in energy consumption and generation. The global system is modeled and simulated under the MATLAB/Simulink tool.

Real-time flight simulation with highly resolved wind fields from a LES model

2021 ◽  
Author(s):  
Xinying Liu ◽  
Julien Gérard Anet ◽  
Leonardo Manfriani ◽  
Yongling Fu
Keyword(s):  
Large Eddy Simulation ◽  
Energy Management ◽  
Management System ◽  
General Aviation ◽  
Energy Management System ◽  
Energy Reserves ◽  
Wind Fields ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Simulation Results

<p>An overproportioned number of accidents involving general aviation occur in complex terrain. According to the statistics included in the accident investigation reports published by the Swiss Transportation Safety Investigation Board, in some cases, pilots overestimated the energy reserves of their aircraft leading to a loss of control. In order to increase flight safety for private pilots in mountainous regions, on behalf of the Swiss Federal Office of Civil Aviation, the Centre for Aviation (ZAV) at the Zurich University of Applied Sciences  develops an energy management system for general aviation, which displays the remaining airplane’s energy reserves taking into account meteorological information. The research project comprises two phases: i) concept and feasibility study and ii) prototype development. The project is currently running in phase one. In this phase, the first implementation of the energy management system was completed. The system was evaluated in the ZAV’s Research and Didactics Simulator (ReDSim). In order to generate highly resolved wind fields in the ReDsim, a well-established large-eddy simulation model, the Parallelized Large-Eddy Simulation (PALM) framework, was used in the concept study, focusing on a small mountainous region in Switzerland, not far from Samedan. For a more realistic representation of specific meteorological situations, PALM was driven with boundary conditions extracted from the COSMO-1 reanalysis of MeteoSwiss. The environment model in the ReDSim was modified to include a new subsystem simulating atmospheric disturbance. The essential variables (wind components, temperature and pressure) were extractred from the PALM output and fed into the subsystem after interpolation to obtain the values at any instant and any aircraft position. Within the subsystem, it is also possible to generate statistical atmospheric turbulence based on the Dryden turbulence model which refers to the military specification MIL-F-8785. This work focuses on the presentation of the PALM model setup and discusses the COSMO-1 forced PALM simulation results, including a statistical comparison of the simulation results with meteorological data from different meteorological reference stations.</p>

An Optimal Energy Management System for Electric Vehicles Hybridized With Supercapacitor

2015 ◽  
Author(s):  
Parisa Golchoubian ◽  
Nasser L. Azad
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Control Strategies ◽  
Control Law ◽  
Energy Management System ◽  
Vehicle Performance ◽  
Optimal Energy Management ◽  
Driving Range ◽  
Simulation Results

In this study, the potential merits of integrating a supercapacitor into an electric vehicle (EV), namely a Toyota RAV4 EV, is investigated. In particular, the impacts of energy management system (EMS) with a buffer scheme and a dynamic programming (DP)-based control law on the vehicle performance characteristics are examined and compared to the vehicle with no supercapacitor in use. While the simulation results show improvements in the vehicle’s driving range and heat loss for the both considered EMSs, the DP-based controller significantly outperforms the buffer policy. The investigations also demonstrate promising results regarding the use of supercapacitors in EVs, intriguing interest for further studies on online control strategies for these systems.

scholarly journals Fuel Saving on Diesel Genset using PV/Battery Spike Cutting in Remote Area Microgrid

2018 ◽  
Vol 164 ◽  
pp. 01045
Author(s):  
Tinton Dwi Atmaja ◽  
Ant Ardath Kristi ◽  
Agus Risdiyanto ◽  
Bambang Susanto ◽  
Dian Andriani ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Management System ◽  
Remote Area ◽  
Photovoltaic Module ◽  
Energy Management System ◽  
Diesel Generator ◽  
Storage Unit ◽  
Fuel Price ◽  
Remote Island

Diesel Generator set was found to be a favorite power generator in a remote area. In this area, diesel genset usually consumes a significant amount of diesel fuel with higher fuel price than an urban area. Diesel Generator capacity conventionally prepared twice bigger or more than the existing load to prevent any load spike from designated equipment. This work implements an Energy Management System to cut the spike with the support from battery storage unit and photovoltaic module. Once the Energy Management System cut the load spike using battery/photovoltaics, Diesel Generator loads no longer need to be irrelevantly bigger than the existing load. The current experiment in the remote island at Raja Ampat archipelago indicates that the using of 80 kVA Diesel Generator can be reduced to 42 kVA Diesel Generator. This Diesel Generator replacement induces fuel consumption up to 50 %. With this designed work, a smart microgrid with PV-Battery-Diesel can be installed in a designated remote area with lower fuel consumption.

scholarly journals An Investigation of Autonomous Vehicle Roundabout Situation

2019 ◽  
Vol 48 (3) ◽  
pp. 236-241
Author(s):  
Hang Cao ◽  
Máté Zöldy
Keyword(s):  
Fuel Consumption ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Preliminary Test ◽  
Driving Behavior ◽  
Physical Parameters ◽  
Test Scenario ◽  
Vehicle Type ◽  
Fuel Consumption And Emissions ◽  
The Impact

The aim of this paper is to evaluate the impact of connected autonomous behavior in real vehicles on vehicle fuel consumption and emission reductions. Authors provide a preliminary theoretical summary to assess the driving conditions of autonomous vehicles in roundabout, which attempts exploring the impact of driving behavior patterns on fuel consumption and emissions, and including other key factors of autonomous vehicles to reduce fuel consumption and emissions. After summarizing, driving behavior, effective in-vehicle systems, both roundabout physical parameters and vehicle type are all play an important role in energy using. ZalaZONE’s roundabout is selected for preliminary test scenario establishment, which lays a design foundation for further in-depth testing.

Design of Neuro-Fuzzy based Intelligent Inference Algorithm for Energy Management System with Legacy Device

2015 ◽  
Vol 64 (5) ◽  
pp. 779-785 ◽  
Author(s):  
In-Hwan Choi ◽  
Sung-Hyun Yoo ◽  
Jun-Ho Jung ◽  
Myo-Taeg Lim ◽  
Jung-Jun Oh ◽  
...  
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Management System ◽  
Inference Algorithm ◽  
Neuro Fuzzy
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