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.

Analysis of Energy Consumption for electric motorcycles depending on vehicle configuration and driving cycles / Niccolai, A; Berzi, L; Barone, F; Baldanzini, N. - ELETTRONICO. - 1306:(2024), pp. 0-0. (Intervento presentato al convegno 52° Conference on Engineering Mechanical Design and Stress Analysis (AIAS 2023) tenutosi a Genova nel 06-09/09/2023) [10.1088/1757-899x/1306/1/012032].

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

Niccolai, A
Writing – Original Draft Preparation
;
Berzi, L
Resources
;
Baldanzini, N
Supervision
2024

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.
2024
IOP Conference Series: Materials Science and Engineering, Volume 1306, 52° Conference on Engineering Mechanical Design and Stress Analysis (AIAS 2023) 06/09/2023 - 09/09/2023 Genova, Italy
52° Conference on Engineering Mechanical Design and Stress Analysis (AIAS 2023)
Genova
06-09/09/2023
Goal 12: Responsible consumption and production
Goal 11: Sustainable cities and communities
Goal 9: Industry, Innovation, and Infrastructure
Niccolai, A; Berzi, L; Barone, F; Baldanzini, N
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1367672
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