A Power Assistant Algorithm Based on Human–Robot Interaction Analysis for Improving System Efficiency and Riding Experience of E-Bikes

Abstract

As robots are becoming more accessible in our daily lives, the interest in physical human–robot interaction (HRI) is rapidly increasing. An electric bicycle (E-bike) is one of the best examples of HRI, because a rider simultaneously actuates the rear wheel of the E-bike in close proximity. Most commercially available E-bikes employ a control methodology known as a power assistant system (PAS). However, this type of system cannot offer fully efficient power assistance for E-bikes since it does not account for the biomechanics of riders. In order to address this issue, we propose a control algorithm to increase the efficiency and enhance the riding experience of E-bikes by implementing the control parameters acquired from analyses of human leg kinematics and muscular dynamics. To validate the proposed algorithm, we have evaluated and compared the performance of E-bikes in three different conditions: (1) without power assistance, (2) assistance with a PAS algorithm, and (3) assistance with the proposed algorithm. Our algorithm required 5.09% less human energy consumption than the PAS algorithm and 11.01% less energy consumption than a bicycle operated without power assistance. Our algorithm also increased velocity stability by 11.89% and acceleration stability by 27.28%, and decreased jerk by 12.36% in comparison to the PAS algorithm.

Enhancing Urban Mobility with Self-Tuning Fuzzy Logic Controllers for Power-Assisted Bicycles in Smart Cities

“…The rule base completes the fuzzy inference, and then, the degree of membership of the output is converted into the magnitude of the motor power via defuzzification. The velocity error, v err , is shown in (7).…”

“…In recent studies, there has been a focus on power-assisted control for E-bikes. Kim et al [ 7 ] discussed the limitations of the commonly used power assistant system (PAS) in commercial E-bikes, highlighting its inefficiency stemming from a lack of consideration for riders’ biomechanics. To address this issue, they proposed a new control algorithm that incorporates parameters derived from analyzing human leg kinematics and muscular dynamics, aiming to improve efficiency and enhance the overall riding experience of E-bikes.…”

Bicycle Traffic Model for Sustainable Urban Mobility Planning

“…Furthermore, research shows a decrease in VKT per e-bike user of 20-28% [65,66], and a decrease in the distance travelled by car as a total modal share of around 10% [67]. Current developments in urban cycling include the introduction of adaptive systems for electric bikes to increase the number of users [68,69]. Such enhancements can improve cycling comfort through the use of innovative technologies that are usually found in individual motorised transport.…”

Design of HMI Based Digital Electric Bike Using DC/AC Power Converter with Regenerative Feature

“…[9]. Latest human robot interaction algorithm is proposed for effective power assistant bike control system which improves the system efficiency [10]. The paper [11] introduce the dynamic control algorithm for charging level of EV battery.…”