An Investigation on the Effects of Input Parameters on the Dynamic and Electric Consumption of Electric Motorcycles

Hieu, Le-Trong; Khoa, Nguyen Xuan

doi:10.3390/su13137285

Cited by 10 publications

(13 citation statements)

References 21 publications

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“…The maximum power determines the top speed of a motorcycle. [ 38 ] The top speed only increases approximately with the cubic root of the power.

P_{\text{max}} = \textrm{ } m \cdot v_{\text{max}} \cdot g \cdot \left(\right. C_{1} + C_{2} \cdot v_{\text{max}}^{2} \left.\right) + ½ \cdot \rho \cdot v_{\text{max}}^{3} \cdot C_{\text{D}} \cdot A \textrm{ }

…”

Section: Resultsmentioning

confidence: 99%

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Comparison of Electric and Internal Combustion Engine SuperSport Bikes

Boretti¹

2023

Energy Tech

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Electric and internal combustion engine super sport bikes are compared for performance, energy efficiency, and range, based on market data and simulations of acceleration and top speed. Electric motorcycles deliver better performances, despite still suffering from a larger weight. They offer a much larger maximum torque, available from zero speed, and a slightly larger maximum power, producing sharper acceleration and higher top speed. Working with a nearly constant torque up to maximum power, they also offer excellent drivability on straight lines. They produce less noise, and no pollutant emissions, and permit better energy economy. They suffer from a reduced range and drivability over corners, for the larger weight and the less favorable mass distribution. Crashworthiness is a major issue of electric motorcycles, as they need to be “written‐off” even after minor crashes since the safety of the battery is difficult to be established. Electric motorcycles are competitive for city driving, where range or long‐time recharge is not an issue, sport driving is impractical, and regenerative braking may further save energy. The introduction of solid‐state batteries may further improve the appeal of electric supersport motorcycles, reducing the weight penalty for acceptable ranges, and providing a more balanced vehicle much easier to handle.

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“…The maximum power determines the top speed of a motorcycle. [ 38 ] The top speed only increases approximately with the cubic root of the power.

P_{\text{max}} = \textrm{ } m \cdot v_{\text{max}} \cdot g \cdot \left(\right. C_{1} + C_{2} \cdot v_{\text{max}}^{2} \left.\right) + ½ \cdot \rho \cdot v_{\text{max}}^{3} \cdot C_{\text{D}} \cdot A \textrm{ }

…”

Section: Resultsmentioning

confidence: 99%

“…The maximum power determines the top speed of a motorcycle. [38] The top speed only increases approximately with the cubic root of the power.…”

Section: Performance Data Of Production Vehicles Are Considered Firstmentioning

confidence: 99%

Comparison of Electric and Internal Combustion Engine SuperSport Bikes

Boretti¹

2023

Energy Tech

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“…The frontal (A(i)) and slope grade (G(i)) are examples of input parameters, with index 'i' standin each individual input parameter. The law of conversation energy states that the total energy intake equals the total energy output plus the total energy loss, which are calculated using Equation (22)…”

Section: Performance Of Esmentioning

confidence: 99%

A Deep Learning Approach to Optimize the Performance and Power Demand of Electric Scooters under the Effect of Operating and Structure Parameters

Hieu,

Lim

2024

Energies

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The purpose of this study was to enhance electric scooter performance utilizing a novel method consisting of an artificial neural network (ANN) and genetic algorithm (GA) to predict power demand, battery voltage, and identify the optimal performance range. For training, validation, and testing, a dataset comprising 1000 data points for each parameter was extracted from a MATLAB-Simulink model. The ANN application was used to identify the battery voltage and power demand, reflecting the simulated results under varying key input parameters. Additionally, the GA was used to identify the optimal performance after the ANN had been trained. The results showed that the ES can achieve a speed of 28.2 km/h while using an optimal power of 553 W, at a wind velocity of 0 m/s, a slope ratio of 0%, and a wheel diameter of 0.37 m. The achieved results show that the ANN-GA method is appropriate for determining the operating and structural parameters for maximizing the performance of electric scooters. To support the simulated results, an experimental study was carried out with an actual road test along the Taehwa river.

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“…When riding posture is closer to upright, the rear tyre gets more load and can provide more longitudinal force for regenerative braking. However, a higher riding posture increases the frontal area and introduces more air resistance at the same time [11]. This paper investigates the electric motorcycle energy economy considering riding posture and regenerative braking with the aim of finding a more efficient riding strategy to improve the electric motorcycle energy economy.…”

Section: Introductionmentioning

confidence: 99%

Impact of Riding Posture and Regenerative Braking on Electric Motorcycle Energy Consumption

Zhou,

Dinh,

Zhu

et al. 2023

2023 IEEE Vehicle Power and Propulsion Conference (VPPC)

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In this paper, the impact of riding posture and regenerative braking on electric motorcycle energy economy is described. The motorcycle longitudinal dynamic model is first built to describe the motorcycle acceleration, tyre load transfer and energy consumption. Through energy consumption analysis based on the world motorcycle test cycle-class 3-2 (WMTC 3-2), the low riding posture can save up to 22.65% of energy consumption than the high riding posture, and regenerative braking can help to save up to 7.65% of energy consumption, which demonstrates the benefit of riding posture control and regenerative braking on energy saving. It is also demonstrated that riding posture has an impact on the rear tyre load and the available rear tyre longitudinal force. At low tyre road friction conditions, higher riding posture can provide more rear tyre longitudinal force for accelerating and regenerative braking, which improves the motorcycle dynamic performance and energy economy.

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An Investigation on the Effects of Input Parameters on the Dynamic and Electric Consumption of Electric Motorcycles

Cited by 10 publications

References 21 publications

Comparison of Electric and Internal Combustion Engine SuperSport Bikes

Comparison of Electric and Internal Combustion Engine SuperSport Bikes

A Deep Learning Approach to Optimize the Performance and Power Demand of Electric Scooters under the Effect of Operating and Structure Parameters

Impact of Riding Posture and Regenerative Braking on Electric Motorcycle Energy Consumption

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