A smart electric bike for smart cities

TL;DR

This thesis presents a cyberphysical system that augments an electric bike with sensors and control algorithms to help reduce cyclists' inhalation of air pollutants in smart city environments.

Contribution

It introduces a novel system integrating sensors, control algorithms, and human-in-the-loop considerations for pollution-aware assistance on electric bikes.

Findings

Proposed control algorithms effectively regulate cyclist assistance based on air pollution levels.

System design integrates sensors, smartphones, and algorithms for real-time pollution management.

Further validation demonstrated potential for reducing pollutant inhalation during cycling.

Abstract

This is a Masters Thesis completed at University College Dublin, Ireland in 2017 which involved augmenting an off-the-shelf electric bike with sensors to enable new services to be delivered to cyclists in cities. The application of primary interest was to control the cyclist's ventilation rate based on the concentration of local air pollutants. Detailed modelling and system design is presented for our Cyberphysical system which consisted of a modified BTwin e-bike, Cycle Analyst sensors, the cyclist themselves, a Bluetooth connected smartphone and our algorithms. Control algorithms to regulate the proportion of power the cyclist provided as a proxy for their ventilation rate were proposed and validated in a basic way, which were later proven significantly further in Further Work (see IEEE Transactions on Intelligent Transportation Systems paper: https://ieeexplore.ieee.org/abstract/document/8357977). The basic idea was to provide more electrical assistance to cyclists in areas of high air pollution to reduce the cyclist ventilation rate and thereby the amount of air pollutants inhaled. This presents an interesting control challenge due to the human-in-the-loop characteristics and the potential for impactful real life applications. A background literature review is provided on energy as it relates to cycling and some other applications are also discussed. A link to a video which demonstrates the system is provided, and also to a blog published by IBM Research about the system.