Abstract

The aim of this study was to check whether the data recorded by a bicycle computer paired with typical measurement sensors can be useful for a scientific evaluation of the cyclist–bicycle anthropotechnical system, including electric bicycles. The problem arose when the authors searched for methods to assess the energy efficiency of electric bicycles and intelligent power management systems provided by the assistance system, in accordance with the current needs of the bicycle user. This can be of great importance in the efficient use of electric bicycles and their batteries, in the event that they are rented in public access systems. This article focuses primarily on data on bicycle speed, calculated by the GPS module or obtained from speed sensors, as well as data from the cadence sensor, power measurement, pedaling technique and heart rate. An attempt was made to evaluate the correctness and consistency of the data recorded by the computer through various types of comparatives analyses. The conducted research used data recorded when traveling the same route with various bikes, including electric ones, with and without assistance. This is the second part of the research. The first part focusing on data obtained by a computer from a GPS system and a barometric altimeter was published in an earlier article. In both parts, the authors presented some advantages and disadvantages of using bicycle computers as tools for measuring and acquiring data. In general, it seems that the existing technology used by bicycle computers and the measurement sensors that cooperate with it can be used in the development of a system that optimizes energy consumption.

Highlights

  • More details on the bikes used, the measuring sensors and the test route can be found in the first part of the article [7], in which the quality of the trajectory, distance and slope data was evaluated. This part of the article focuses on velocity, cadence and power data

  • A method of calculating speed based on the delay of satellite signals, due to the Doppler effect, is being developed. Research shows that this method of determining speed is much more accurate [8]. Perhaps soon this method will be implemented in bicycle computers

  • The same applies to the speed signal that the computer calculates from the GPS data

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Summary

Introduction

Classic bicycles were one of the main means of transport used in shared mobility systems. The shared mobility market has been increasingly filled with electric scooters [1]. Classic bikes used in shared mobility systems have been dominated by scooters, which can be found on every street in larger cities. An alternative to scooters has become bicycles with electric assistance. In 2019, the market for electric bicycles in shared mobility systems was estimated to be 28%, and in 2020, it was already 44%. It is expected that in the coming years, the share of electric bicycles in vehicle sharing systems will continue to grow [5]; electric bikes will undoubtedly replace traditional bicycles in public bicycle rental systems

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