Hybrid Electric Vehicle Modelling And Fuel Economy Regression Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F22%3A00010187" target="_blank" >RIV/46747885:24220/22:00010187 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/46747885:24620/22:00010187

Výsledek na webu

<a href="https://www.actapress.com/PaperInfo.aspx?paperId=55234" target="_blank" >https://www.actapress.com/PaperInfo.aspx?paperId=55234</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2316/J.2022.201-0297" target="_blank" >10.2316/J.2022.201-0297</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hybrid Electric Vehicle Modelling And Fuel Economy Regression Analysis

Popis výsledku v původním jazyce

This paper starts with reviewing of recent developments and studies on hybrid electric vehicle (HEV) modelling, control, and fuel economy management. Then, the paper presents and guides modelling of HEVs on Matlab 2021b Simulink with powertrain, internal combustion engine, battery, converter, starter/generator motor, vehicle dynamics, control system, and the whole integrated HEV model. Latest hybrid electrical models are simulated on standard driving cycles of Extra-Urban Driving Cycle, New York City Cycle, Federal Test Procedure 75, and Highway Fuel Economy Test. Data on fuel consumption are collected and processed in Matlab to set up different fuel consumption regression models. The best fit regression model for HEV fuel consumption estimation is found with the determination coefficient R square more than 99.14%. The best HEV selected fuel regression model is then simulated and compared to the normal HEVs with the same sizes on different driving cycles to prove the optimal performances of the selected HEVs on fuel economy consumptions.

Název v anglickém jazyce

Hybrid Electric Vehicle Modelling And Fuel Economy Regression Analysis

Popis výsledku anglicky

This paper starts with reviewing of recent developments and studies on hybrid electric vehicle (HEV) modelling, control, and fuel economy management. Then, the paper presents and guides modelling of HEVs on Matlab 2021b Simulink with powertrain, internal combustion engine, battery, converter, starter/generator motor, vehicle dynamics, control system, and the whole integrated HEV model. Latest hybrid electrical models are simulated on standard driving cycles of Extra-Urban Driving Cycle, New York City Cycle, Federal Test Procedure 75, and Highway Fuel Economy Test. Data on fuel consumption are collected and processed in Matlab to set up different fuel consumption regression models. The best fit regression model for HEV fuel consumption estimation is found with the determination coefficient R square more than 99.14%. The best HEV selected fuel regression model is then simulated and compared to the normal HEVs with the same sizes on different driving cycles to prove the optimal performances of the selected HEVs on fuel economy consumptions.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/EF16_025%2F0007293" target="_blank" >EF16_025/0007293: Modulární platforma pro autonomní podvozky specializovaných elektrovozidel pro dopravu nákladu a zařízení</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Mechatronic systems and control

ISSN

2561-1771

e-ISSN

—

Svazek periodika

50

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CA - Kanada

Počet stran výsledku

10

Strana od-do

171-181

Kód UT WoS článku

000908367300001

EID výsledku v databázi Scopus

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