scholarly journals User Automotive Powertrain-Type Choice Model and Analysis Using Neural Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 585
Author(s):  
Fabio Luis Marques dos Santos ◽  
Paolo Tecchio ◽  
Fulvio Ardente ◽  
Ferenc Pekár
Keyword(s):  
Internal Combustion Engine ◽  
User Behavior ◽  
Choice Model ◽  
Combustion Engine ◽  
Stated Preference ◽  
Operating Cost ◽  
Internal Combustion ◽  
Ann Model ◽  
Purchase Cost ◽  
Artificial Neural Network Ann

This paper presents an artificial neural network (ANN) model that simulates user’s choice of electric or internal combustion engine automotive vehicles based on basic vehicle attributes (purchase price, range, operating cost, taxes due to emissions, time to refuel/recharge and vehicle price depreciation), with the objective of analyzing user behavior and creating a model that can be used to support policymaking. The ANN was trained using stated preference data from a survey carried out in six European countries, taking into account petrol, diesel and battery electric automotive vehicle attributes. Model results show that the electric vehicle parameters (especially purchase cost, range and recharge times), as well as the purchase cost of internal combustion engine vehicles, have the most influence on consumers’ vehicle choices. A graphical interface was created for the model, to make it easier to understand the interactions between different attributes and their impacts on consumer choices and thus help policy decisions.

scholarly journals Exploring Factors that Influence Individuals’ Choice Between Internal Combustion Engine Cars and Electric Vehicles

2020 ◽  
Vol 1 ◽  
pp. 1-23
Author(s):  
Dominik Bucher ◽  
Henry Martin ◽  
Jannik Hamper ◽  
Atefeh Jaleh ◽  
Henrik Becker ◽  
...  
Keyword(s):  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Choice Model ◽  
Combustion Engine ◽  
Renewable Energy Sources ◽  
Internal Combustion ◽  
Transport Sector ◽  
Wide Range ◽  
Range Anxiety

Abstract. The adoption of electric vehicles has the potential to help decarbonizing the transport sector if they are powered by renewable energy sources. Limitations commonly associated with e-cars are their comparatively short ranges and long recharging cycles, leading to anxiety when having to travel long distances. Other factors such as temperature, destination or weekday may influence people in choosing an e-car for a certain trip. Using a unique dataset of 129 people who own both an electric vehicle (EV) as well as one powered by an internal combustion engine (ICE), we analyze tracking data over a year in order to have an empirically verified choice model. Based on a wide range of predictors, this model tells us for an individual journey if the person would rather choose the EV or the ICE car. Our findings show that there are only weak relations between the predictor and target variables, indicating that for many people the switch to an e-car would not affect their lifestyle and the related range anxiety diminishes when actually owning an electric vehicle. In addition, we find that choice behavior does not generalize well over different users.

scholarly journals PREDICTION OF INTERNAL COMBUSTION ENGINE PERFORMANCE USING ARTIFICIAL INTELLIGENCE

2020 ◽  
Vol 14 (2) ◽  
pp. 153-162
Author(s):  
Lukman Shalahuddin ◽  
Adityo Suksmono ◽  
Yohanes P Sembiring
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Internal Combustion Engine ◽  
Combustion Engine ◽  
Engine Performance ◽  
Internal Combustion ◽  
Simulation Software ◽  
Operating Conditions ◽  
Ann Model ◽  
Mean Square Errors

The potential of artificial intelligence (AI) application for prediction of internal combustion engine performance is assessed in this paper. A literature survey on this subject is first reviewed, in which previous researches utilized the advance of artificial neural networks (ANN) as one type of AI. Previous works commonly obtained the data from experimental engine tests. Under the same engines, they varied the fuel compositions or the engine operating conditions. Whereas in this study, an ANN model is developed to calculate the inputs from an engine simulation software package database and to predict the engine performance based on the simulation software outputs as the ANN target outputs. Results from the ANN model in the “learning” step indicates good agreement with the software simulation outputs. Improvement and development of the program are required, including optimation of the ANN model architecture, such as the choice of activation function, the number of neurons in the hidden layer, and the number of iterations, as well as the number and option of input engine parameters. The ANN model seems promising to predict engine performance, with root mean square errors in the range of 0.4-1.8%. Keywords: Artificial Intelligence; Neural Networks; Engine Performance.

АКУСТИЧНА ПОМІТНІСТЬ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ З СИЛОВИМИ УСТАНОВКАМИ НА БАЗІ ПОРШНЕВИХ ДВИГУНІВ

2020 ◽  
pp. 62-80
Author(s):  
В. В. Руденко ◽  
И. В. Калужинов ◽  
Н. А. Андрущенко
Keyword(s):  
Control System ◽  
Internal Combustion Engine ◽  
Power Plants ◽  
Combustion Engine ◽  
Spectral Characteristics ◽  
Experimental Studies ◽  
Internal Combustion ◽  
Detection Range ◽  
Acoustic Signature ◽  
Static Conditions

The presence in operation of many prototypes of UAVs with propeller propellers, the use of such devices at relatively low altitudes and flight speeds makes the problem of noise reduction from UAVs urgent both from the point of view of acoustic imperceptibility and ecology.The aim of the work is to determine a set of methods that help to reduce the visibility of UAVs in the acoustic range. It is shown that the main source of noise from the UAV on the ground is the power plant, which includes the engine and the propeller. The parameters of the power plants influencing the processes that determine the acoustic signature of the UAV were investigated. A comprehensive analysis of the factors affecting visibility was carried out. The power plants include two-stroke and four-stroke engines, internal combustion and two-blade propellers. The use of silencers on the exhaust of the internal combustion engine was considered. The spectral characteristics of the acoustic fields of the propeller-driven power plants for the operating sample of the UAV "Eco" were obtained. The measurements were carried out in one-third octave and 1/48 octave frequency bands under static conditions. The venue is the KhAI airfield. Note that the propellers that were part of the power plants operated at Reynolds numbers (Re0,75<2*105), which can significantly affect its aerodynamic and acoustic characteristics. It is shown that when choosing a UAV control system, one should take into account the fact that two-stroke piston engines are the dominant source in the noise of propeller-driven control systems in the absence of a hood and mufflers in the intake and exhaust tracts. The use of a four-stroke internal combustion engine significantly reduces the noise of the control system. In the general case, the position of the boundaries of the zone of acoustic visibility of a UAV at the location of the observer is determined by the ratio between the intensity of acoustic radiation perceived by the observer from the UAV and the intensity of sound corresponding to the natural acoustic background and depends on the degree of manifestation of acoustic effects accompanying the propagation of sound in a turbulent atmosphere - the refraction of sound waves. Absorption and dissipation of acoustic energy. The calculation and comparison of the UAV detection range was carried out taking into account the existing natural maskers.The results of experimental studies are presented that allow assessing the degree of acoustic signature of the UAV. A set of measures aimed at reducing the intensity of the acoustic signature of the UAV in various regions of the radiation spectrum has been determined.

CONVERTING THE VEHICLE BY REPLACING THE INTERNAL COMBUSTION ENGINE

2019 ◽  
pp. 29-35
Author(s):  
Oleksandr Gryshchuk ◽  
Volodymyr Hladchenko ◽  
Uriy Overchenko
Keyword(s):  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Electric Motor ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Environmental Safety ◽  
Environmental Conservation ◽  
Sales Forecasts ◽  
Financial Investments ◽  
Near Future

This article looks at some comparative statistics on the development and use of electric vehicles (hereinafter referred to as EM) as an example of sales and future sales forecasts for EM in countries that focus on environmental conservation. Examples of financial investments already underway and to be made in the near future by the largest automakers in the development and distribution of EM in the world are given. Steps are taken to improve the environmental situation in countries (for example, the prohibition of entry into the city center), the scientific and applied problem of improving the energy efficiency and environmental safety of the operation of wheeled vehicles (hereinafter referred to as the CTE). The basic and more widespread schemes of conversion of the internal combustion engine car (hereinafter -ICE) to the electric motor car (by replacing the gasoline or diesel electric motor), as well as the main requirements that must be observed for the safe use and operation of the electric vehicle. The problem is solved by justifying the feasibility of re-equipment of the KTZ by replacing the internal combustion engine with an electric motor. On the basis of the statistics collected by the State Automobile Transit Research Institute on the number of issued conclusions of scientific and technical expertise regarding the approval of the possibility of conversion of a car with an internal combustion engine (gasoline or diesel) to a car with an electric motor (electric vehicle), the conclusions on the feasibility of such conclusion were made. Keywords: electricvehicles, ecological safety, electricmotor, statistics provided, car, vehicle by replacing.

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