Motion Control of an Electric Power-Assisted Bicycle under the Effects of Operating Conditions
Main Article Content
Abstract
The use of electric bicycle (EB) is considered as a useful solution for reducing the exhaust emissions and dependence of fossil fuels. Along with the development of EBs, studies on their motion characteristics have been receiving more attentions. In this paper, the control of the angular speed of the wheel in an electric power-assisted bicycle (EPAB) is discussed, considering external factors such as slope grade and wind speed. One proposed strategy to optimize vehicle speed is the particle swarm optimization (PSO) algorithm. To achieve this, a simulation model was developed to represent the operation of EPAB under rider control. Based on this operating model, mathematical models including a dynamic model of a bicycle under the driver's control, a dynamic model of an electric motor, and a vehicle speed control model using PSO - based Proportional Integral Derivative (PID) controller are established. The simulation demonstrates that the PSO-based PID controller is superior in terms of control compared to using it without PSO and it works quickly in finding Kp, Ki, Kd to control the angular velocity of the wheel when external conditions change. These simulation results can also serve as useful resources for researchers looking to develop electric-assist bicycles.
Keywords
EB, PID, PSO, slope grade, wind speed
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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[9] A. Ambroziak, A. Chojectki, The PID controller optimisation module using fuzzy self - tuning PSO for air handling unit in continuous operation, Engineering Applications of Artificial Intelligence, vol. 117, Jan. 2023, pp. 105485. https://doi.org/10.1016/j.engappai.2022.105485
[10] S. Ahmadi, Sh. Abdi, and M. Kakavand, Maximum power point tracking of a proton exchange membrane fuel cell system using PSO-PID controller, International Journal of Hydrogen Energy, vol. 42, Aug. 2017, pp. 20430 - 20443. https://doi.org/10.1016/j.ijhydene.2017.06.208
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[14] T. J. Su, H. C. Wang, and J. W. Liu, Particle Swarm Optimization for Image Noise Cancellation, Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Kaohsiung, Taiwan, Nov. 26-28, 2007. https://doi.org/10.1109/IIH-MSP.2007.237