Analysis of Energy Consumption for electric motorcycles depending on vehicle configuration and driving cycles

Abstract This article presents an analysis of energy consumption for battery electric motorcycles (BEM) based on vehicle configuration and driving cycles. The study investigates the impact of two architectures: rear-wheel regenerative (RWR), and two-wheel regenerative (2WR) on consumption. For the a...

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Published inIOP conference series. Materials Science and Engineering Vol. 1306; no. 1; pp. 12032 - 12041
Main Authors Niccolai, A, Berzi, L, Barone, F, Baldanzini, N
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.05.2024
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Abstract Abstract This article presents an analysis of energy consumption for battery electric motorcycles (BEM) based on vehicle configuration and driving cycles. The study investigates the impact of two architectures: rear-wheel regenerative (RWR), and two-wheel regenerative (2WR) on consumption. For the analysis, the study considered the effect of various parameters on the longitudinal vehicle dynamics such as speed profiles (WMTC, real-world profile), longitudinal road slope (from -5° to 5° with 0.5° step increment), and 5 different brake distributions. The research employs simulation techniques using the Matlab/Simulink environment to develop a simplified longitudinal vehicle dynamics model (1 DOF) and for the implementation of a serial brake-blending control strategy. The results of the analysis provide energy potential regeneration and insight into the sensitivity of energy consumption to road slope variations, powertrain working points, and potential energy harvesting. The findings contribute to a valuation of the factors that influence energy consumption in electric motorcycles and have implications for the development of vehicle architectures through accurate range assessment on real-world riding conditions and provide valuable information for powertrain components right-sizing.
AbstractList Abstract This article presents an analysis of energy consumption for battery electric motorcycles (BEM) based on vehicle configuration and driving cycles. The study investigates the impact of two architectures: rear-wheel regenerative (RWR), and two-wheel regenerative (2WR) on consumption. For the analysis, the study considered the effect of various parameters on the longitudinal vehicle dynamics such as speed profiles (WMTC, real-world profile), longitudinal road slope (from -5° to 5° with 0.5° step increment), and 5 different brake distributions. The research employs simulation techniques using the Matlab/Simulink environment to develop a simplified longitudinal vehicle dynamics model (1 DOF) and for the implementation of a serial brake-blending control strategy. The results of the analysis provide energy potential regeneration and insight into the sensitivity of energy consumption to road slope variations, powertrain working points, and potential energy harvesting. The findings contribute to a valuation of the factors that influence energy consumption in electric motorcycles and have implications for the development of vehicle architectures through accurate range assessment on real-world riding conditions and provide valuable information for powertrain components right-sizing.
This article presents an analysis of energy consumption for battery electric motorcycles (BEM) based on vehicle configuration and driving cycles. The study investigates the impact of two architectures: rear-wheel regenerative (RWR), and two-wheel regenerative (2WR) on consumption. For the analysis, the study considered the effect of various parameters on the longitudinal vehicle dynamics such as speed profiles (WMTC, real-world profile), longitudinal road slope (from -5° to 5° with 0.5° step increment), and 5 different brake distributions. The research employs simulation techniques using the Matlab/Simulink environment to develop a simplified longitudinal vehicle dynamics model (1 DOF) and for the implementation of a serial brake-blending control strategy. The results of the analysis provide energy potential regeneration and insight into the sensitivity of energy consumption to road slope variations, powertrain working points, and potential energy harvesting. The findings contribute to a valuation of the factors that influence energy consumption in electric motorcycles and have implications for the development of vehicle architectures through accurate range assessment on real-world riding conditions and provide valuable information for powertrain components right-sizing.
Author Berzi, L
Baldanzini, N
Niccolai, A
Barone, F
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Cites_doi 10.1109/EVER.2017.7935895
10.1016/j.apenergy.2016.01.051
10.1109/TVT.2018.2872030
10.1177/0020294013506825
10.1016/j.energy.2018.02.046
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European Commission (MSE_1306_1_012032bib6) 2019
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Spichartz (MSE_1306_1_012032bib5) 2017
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Oleksowicz (MSE_1306_1_012032bib4) 2013; 46
Weiss (MSE_1306_1_012032bib3)
Björnsson (MSE_1306_1_012032bib9) 2016
Yuan (MSE_1306_1_012032bib8) 2018; 67
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  ident: MSE_1306_1_012032bib5
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  article-title: Regulation No 134 of the Economic Commission for Europe of the United Nations (UN/ECE) — Uniform provisions concerning the approval of motor vehicles and their components with regard to the safety-related performance of hydrogen-fuelled vehicles (HFCV) [2019/795]
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  doi: 10.1016/j.energy.2018.02.046
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Snippet Abstract This article presents an analysis of energy consumption for battery electric motorcycles (BEM) based on vehicle configuration and driving cycles. The...
This article presents an analysis of energy consumption for battery electric motorcycles (BEM) based on vehicle configuration and driving cycles. The study...
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StartPage 12032
SubjectTerms Brakes
Configurations
Electric motorcycles
Electric vehicles
Energy consumption
Energy harvesting
Motorcycles
Potential energy
Power consumption
Powertrain
Roads
Traffic speed
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Title Analysis of Energy Consumption for electric motorcycles depending on vehicle configuration and driving cycles
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