Enhanced intelligent control with adaptive system for electrically assisted bicycle

This paper presents an enhanced fuzzy logic control strategy considering the human-bike interaction. A new transmission mechanism and intelligent control system for an electric bicycle are designed and validated through simulations and experimental setup. A load cell-based mini-sensor system is developed to measure the pedal torque. The transfer function of the system is obtained with data-based system identification and the control algorithms are first tested on this model and transferred to the real environment. Since the cycle interval time is important in the success of the control algorithm, the Fuzzy logic rule bases are operated by using the Hash Table method. The PI, PID, Fuzzy PID, and Hybrid Fuzzy algorithms are compared. Fuzzy PID and Hybrid Fuzzy methods are close to each other in terms of time analysis parameters and performance criteria, but more successful than other control strategies. The simulation and experimental results show that the proposed approach is satisfactory in terms of response time and speed control and provides driving comfort and safety. (C) 2021 Karabuk University. Publishing services by Elsevier B.V.

Automated summary

This paper presents an enhanced fuzzy logic control strategy considering the human-bike interaction. A new transmission mechanism and intelligent control system for an electric bicycle are designed and validated. The fuzzy logic rule bases are operated using the Hash Table method and compared with other control strategies. The simulation and experimental results demonstrate that the proposed approach achieves satisfactory response time and speed control, providing driving comfort and safety.