Title :
A fuzzy Q-learning based assisted power management method for comfortable riding of pedelec
Author :
Cheng-Ting Liu ; Hsu, Roy Chaoming
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Chiayi Univ., Chiayi, Taiwan
Abstract :
In this study, a fuzzy logic controller with parameters tuned by Q-learning is proposed for the assisted power management of a pedelec. The pedelec is a human-electric hybrid vehicle driven by mainly the rider´s pedal force with the assisted power from the electric motor. The proposed assisted power management (APM) method adaptively provides an appropriate assisted power (action) according to the environmental changes via the fuzzy inference coordinated Q-learning, i.e. fuzzy Q-learning. Simulations of the proposed method, hereafter abbreviated as FQLAPM, on a pedelec are performed, and the results exhibit better performance in comparing with other existent assisted power methods.
Keywords :
electric motors; electric vehicles; ergonomics; fuzzy control; fuzzy set theory; FQLAPM; assisted power management; comfortable riding; electric motor; fuzzy Q-learning; fuzzy logic controller; human-electric hybrid vehicle; pedelec; Acceleration; Bicycles; Force; Roads; Robot sensing systems; Safety; comfort of riding; fuzzy Q-learning; pedelecs; power management;
Conference_Titel :
Automation, Robotics and Applications (ICARA), 2015 6th International Conference on
Conference_Location :
Queenstown
DOI :
10.1109/ICARA.2015.7081212