Understanding Electric Bicycle Users’ Mode Choice Preference under Uncertainty: A Case Study of Shanghai

The electric bicycle is considered as an environmentally friendly mode, the market share of which is growing fast worldwide. Even in metropolitan areas which have a well-developed public transportation system, the usage of electric bicycles continues to grow. Compared with bicycles, the power transferred from the battery enables users to ride faster and have long-distance trips. However, research on electric bicycle travel behavior is inadequate. This paper proposes a cumulative prospect theory (CPT) framework to describe electric bicycle users’ mode choice behavior. Different from the long-standing use of utility theory, CPT considers travelers’ inconsistent risk attitudes. Six socioeconomic characteristics are chosen to discriminate conservative and adventurous electric bicycle users. Then, a CPT model is established which includes two parts: travel time and travel cost. We calculate the comprehensive cumulative prospect value (CPV) for four transportation modes (electric bicycle, bus, subway and private car) to predict electric bicycle users’ mode choice preference under different travel distance ranges. The model is further validated via survey data.

Design of a hydrogen-powered bicycle for sustainable mobility

Hydrogen-powered vehicles are emerging as a key source for a clean and sustainable mobility scenario. In particular, hydrogen technologies have a great potential for light mobility in urban areas, where traffic congestion may cause very high levels of local pollution. In this context, hybrid fuel cell/battery vehicles represent a promising solution, since they allow for extended driving range and short recharge time, which are two of the major concerns related to electric propulsion, in general. In this work, a new plug-in fuel cell electric bicycle concept is presented, where the on-board energy storage is realized by means of an innovative system integrating a battery pack with a metal hydride hydrogen tank. This solution allows to achieve very high performance in terms of riding range, which are unattainable with traditional battery electric bicycles. In particular, the hybrid energy storage system is conceived to provide an optimal thermal management of the two integrated components. The proposed design is developed on the basis of typical duty cycles acquired during on-road measurements. A prototype of the bicycle is then realized and bench-tested in order to assess design consistency and to evaluate its performances. The results show that the riding range of the new hydrogen-fuelled bicycle is about three times higher than the one for a similar electric bicycle.

Performance analysis of brushless DC motor with optimum magnetic energy for bicycle application

<span lang="EN-US">Brushless DC (BLDC) motor is widely used for various applications such as transportation. BLDC motor has many advantages compared to brush motor such as more compact, high robustness and simplest construction. The maintenance of this motor also low compared to brush motor due to absent of the brush inside the motor. For electric bicycle application, the conventional motor has low electromagnetic torque because not properly designed. It faces low torque density as the motor in full load condition especially during climb uphill. In this research, an optimum magnetic energy is being determine by proper selection of permanent magnet size. In addition, this research also increases the input current in dynamic condition into the designed BLDC motor. Finite element method (FEM) is used to analyze other performance characteristic of improved motor such as back electromotive force (EMF), electromagnetic torque, flux linkage, and stator flux density. Parameter for improve the current motor are selected and varied based on the required specification. In conclusion, the research proposed the new motor specification that has highest electromagnetic torque of brushless DC motor. Finally, this research provides guidelines, suggestions and proposes a better improved structure in optimize the magnetic energy in BLDC motor.</span>

Circular Business Models for Remanufacturing in the Electric Bicycle Industry

The rising popularity and strong increase in the number of electric bicycles make it necessary to consider the built-in resources as well as possible treatments after the use phase. The time lag between the purchase and the occurrence of relevant defects suggests significant increases in defective components. Especially the great dynamics of the market due to regular innovations, product renewals, and the lack of spare parts availability for older models make the long-term use by customers much more difficult than for conventional bicycles. Therefore, it is necessary to analyze circular business models for the electric bicycle market. In this way, the required structures for a sustainable electric bicycle industry can be created so that valuable materials do not go into disposal but undergo a new use phase. Based on the results of “AddRE-Mo–Value Preservation Scenarios for Urban Electromobility of Persons and Loads through Additive Manufacturing and Remanufacturing,” a research project funded by the German Federal Ministry of Education and Research, this paper addresses four circular business models, two sales models, and two service models. The guiding research interest of this paper is the combination of remanufacturing and additive manufacturing from a business model perspective, analyzing the extent to which additive remanufacturing can be considered a solution for electric bicycles' circularity. After describing the approach and methods used to develop these four circular business models the business models are described and analyzed using the Business Model Canvas. Based on this analysis, it is shown that the combination of remanufacturing and additive manufacturing can be applied to the electric bicycle market and be integrated into both sales and service models. The description of these business models will help managers design viable business models in the context of sustainable electric bicycles. It also shows that the individual partners within the value chain must collaborate more closely. In the electric bicycle industry, a single company will probably not be able to close the product cycle completely. Further research is needed to develop concepts of the business models and examine their practical feasibility in technical and organizational operations to achieve a circular economy.

Multi-Variable Multi-Objective Optimization Algorithm for Optimal Design of PMa-SynRM for Electric Bicycle Traction Motor

In this paper, internal division point genetic algorithm (IDP-GA) was proposed to lessen the computational burden of multi-variable multi-objective optimization problem using finite element analysis such as optimal design of electric bicycles. The IDP-GA could consider various objectives with normalized weighted sum method and could reduce the number of function calls with novel crossover strategy and vector-based pattern search method. The superiority of the proposed algorithm was verified by comparing performances with conventional optimization method at two mathematical test functions. Finally, the applicability of the IDP-GA in practical electric machine design was verified by successfully deriving an improved design of electric bicycle propulsion motor.

Electric Bicyclist Injury Severity during Peak Traffic Periods: A Random-Parameters Approach with Heterogeneity in Means and Variances

Accidents involving electric bicycles, a popular means of transportation in China during peak traffic periods, have increased. However, studies have seldom attempted to detect the unique crash consequences during this period. This study aims to explore the factors influencing injury severity in electric bicyclists during peak traffic periods and provide recommendations to help devise specific management strategies. The random-parameters logit or mixed logit model is used to identify the relationship between different factors and injury severity. The injury severity is divided into four categories. The analysis uses automobile and electric bicycle crash data of Xi’an, China, between 2014 and 2019. During the peak traffic periods, the impact of low visibility significantly varies with factors such as areas with traffic control or without streetlights. Furthermore, compared with traveling in a straight line, three different turnings before the crash reduce the likelihood of severe injuries. Roadside protection trees are the most crucial measure guaranteeing riders’ safety during peak traffic periods. This study reveals the direction, magnitude, and randomness of factors that contribute to electric bicycle crashes. The results can help safety authorities devise targeted transportation safety management and planning strategies for peak traffic periods.

Efficiency Evaluation of Electric Bicycle Power Transmission Systems

In this study, a method for estimating the efficiency of electric bicycle power train systems consisting of typical components, such as an electric motor, gears, sprockets, and chains is presented. In order to calculate the efficiency of a power train system, the relationship between the drive motor torque and the road-load that is exerted on the rear wheel was derived, considering kinematic inertia effects and friction losses between power transmission elements. Among the factors that influence efficiency, it was found that friction losses play a dominant role, while the effects of inertia are insignificant. The factors that influence the efficiency of electric bicycles due to friction losses, such as the transmission efficiency of the chain system and the bearing in the sprocket and wheel, were quantified. To validate the proposed efficiency calculation procedure, an experimental electric bicycle was used, in which the driving torque and road-load could be quantitatively assessed, and the actual efficiency was measured on a chassis dynamometer. It is shown that for a given motor torque, a measured and estimated dynamometer torque obtained by the proposed method exhibits a good correlation, and the transmission efficiency of each component was quantified. This method provides a practical and accurate means to calculate the drive train efficiency of electric bicycles at the design stage to improve the efficiency of electric bicycles.