An investigation on the effective performance area of the electric bicycle with variable key input parameters

Hieu, Le Trong; Khoa, Nguyen Xuan; Lim, Ock Teack

doi:10.1016/j.jclepro.2021.128862

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Additionally, the real-time voltage of the LIB was monitored using an NI-9221 module with an 800 kS/s sample rate. The LabVIEW program was used to monitor and record all the aforementioned signals after they had been transferred to the computer via a USB cable [20].…”

Section: Methodsmentioning

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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Section: Methodsmentioning

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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“…Figure 1 presents the components of the ES experimental setup. In order to collect and store experimental data, a LabVIEW program was installed on a local PC [26]. The ES energy was supplied through a Li-ion battery 36 V, 9 Ah to the dc motor and, in order to measure the ES's velocity and travel distance, an electric control unit (ECU) was installed on the ES frame, which read the signals from a photosensor.…”

Section: Methodology 21 Experimental Setupmentioning

confidence: 99%

Effects of the Structure and Operating Parameters on the Performance of an Electric Scooter

Hieu

2023

Sustainability

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The research objective is to approach the dynamic and consumed electrical energy of an electric scooter by varying the key input parameters, including rider mass, electric scooter mass, wind speed, wheel radius, and slope grade. A simulation model of an electric scooter was applied in a MATLAB-Simulink environment to investigate the scooter velocity, required power, battery voltage, and propulsion torque of the e-scooter. It was established by employing mathematical equations during the of electric scooters. The study found that the scooter velocity and electricity consumption were optimized by 3.9% and 0.08%, respectively, when the scooter weight decreased from 26 to 10 kg. The scooter velocity, electricity consumption, and required power decreased by 23.2%, 0.55%, and 8.56%, respectively, when the slope grade decreased from 1.15% to 0%. Following a wind speed reduction from 4 to 0 m/s, the consumed electricity and required power were optimized by 0.2% and 5.5%, respectively. The consumed electricity increased by 0.2% and the scooter velocity and required power significantly increased by 36.5% and 34.3% when the wheel radius increased from 0.105 to 0.185 m. Furthermore, the e-scooter could achieve an effective performance with a weight of 10 kg, wheel radius of 0.185 m, wind speed of 0 km/h, slope grade of 0%, and minimal rider weight. The simulation results showed that the scooter’s effective performance range and consumed electrical energy could be optimized by suitably adjusting the key structures and operating parameters. To support this research, a concurrent experiment investigated the dynamic characteristics and electricity consumption of the electric scooter during operation. The experimental and simulated results had the same patterns in similar initial conditions.

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A deep learning approach for optimize dynamic and required power in electric assisted bicycle under a structure and operating parameters

Hieu

2023

Applied Energy

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An investigation on the effective performance area of the electric bicycle with variable key input parameters

Cited by 4 publications

References 18 publications

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

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

Effects of the Structure and Operating Parameters on the Performance of an Electric Scooter

A deep learning approach for optimize dynamic and required power in electric assisted bicycle under a structure and operating parameters

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