Electric Bicycle Research Articles

Do shared E-bikes reduce urban carbon emissions?

Under the threat of climate change, many global cities nowadays are promoting shared commuting modes to reduce greenhouse gas emissions. Shared electric bikes (e-bikes) are emerging modes that compete with bikes, cars, or public transit. However, there is a lack of empirical evidence for the net effect of shared e-bikes on carbon emissions, as shared e-bikes can substitute for both higher carbon emissions modes and cleaner commuting modes. Using a large collection of spatio-temporal trajectory data of shared e-bike trips in two provincial cities (Chengdu and Kunming) in China, this study develops a travel mode substitution model to identify the changes in travel modes due to the introduction of shared e-bike systems and to quantify the corresponding impact on net carbon emissions. We find that, on average, shared e-bikes decrease carbon emissions by 108–120 g per kilometre. More interestingly, the reduction effect is much stronger in underdeveloped non-central areas with lower density, less diversified land use, lower accessibility, and lower economic level. Although the actual carbon reduction benefits of shared e-bike schemes are far from clear, this study bears important policy implications for exploring this emerging micro-mobility mode to achieve carbon reduction impacts.

Research on the Rapid Recognition Method of Electric Bicycles in Elevators Based on Machine Vision

People are gradually coming around to the idea of living a low-carbon lifestyle and using green transportation, and given the severe urban traffic congestion, electric bicycle commuting has taken over as the preferred mode of short-distance transportation for many. Since batteries are used to power electric bicycles, there are no greenhouse gas emissions while they are in use, which is more in line with the requirement for sustainable development around the world. The public has been increasingly concerned about the safety issues brought on by electric bicycles as a result of the industry’s quick development and the rapid increase in the number of electric bicycles worldwide. The unsafe operation of the elevator and the safety of the building have been seriously compromised by the unauthorized admission of electric bicycles into the elevator. To meet the need for fast detection and identification of electric bicycles in elevators, we designed a modified YOLOv5-based identification approach in this study. We propose the use of the EIoU loss function to address the occlusion problem in electric bicycle recognition. By considering the interaction ratio and overlap loss of the target frames, we are able to enhance localization accuracy and reduce the missed detection rate of occluded targets. Additionally, we introduce the CBAM attention mechanism in both the backbone and head of YOLOv5 to improve the expressive power of feature maps. This allows the model to prioritize important regions of the target object, leading to improved detection accuracy. Furthermore, we utilize the CARAFE operator during upsampling instead of the nearest operator in the original model. This enables our model to recover details and side information more accurately, resulting in finer sampling results. The experimental results demonstrate that our improved model achieves an mAP of 86.35 percent, a recall of 81.8 percent, and an accuracy of 88.0 percent. When compared to the original model under the same conditions, our improved YOLOv5 model shows an average detection accuracy increase of 3.49 percent, a recall increase of 5.6 percent, and an accuracy increase of 3.5 percent. Tests in application scenarios demonstrate that after putting the model on the hardware platform Jeston TX2 NX, stable and effective identification of electric bicycles can be accomplished.

Resonance Characteristics of the LLC Resonant Half-Bridge Converter for the Rapid Charging of Personal Mobility Device Smart Batteries

This study discusses the resonance characteristics of the LLC resonant half-bridge converter and smart battery charging for the fast charging of personal mobility devices (e.g., electric kickboards, segways, hoverboards, electric bicycles, and electric motorcycles), whose use is rapidly increasing. Through the analysis of resonance characteristics, this study aims to validate that fS > f0 is the most appropriate correlation in the relationship between resonant frequency (f0) and switching frequency (fS) that is suitable for the rapid charging of batteries of personal mobility devices. Additionally, the proposed half-bridge converter does not charge the battery from discharge or misconnection based on the detection of the battery voltage for the batteries of personal mobility devices. Therefore, the proposed converter suggests a charging system based on battery state detection that stably performs rapid charging of the batteries of personal mobility devices by equalizing the battery voltage and the charger voltage through a pre-charge operation.

O.5.1-8 Modal shift towards the e-bike: preliminary results from a systematic review on factors influencing the use of e-bikes

Abstract Background In the last decade, the use of electric bikes (e-bikes) has become increasingly common due to rapid advances in technology. This has led to an increased number of publications aimed at investigating individual factors and beliefs that influence a modal shift towards e-bikes. To our knowledge, there is currently no review summarizing the evidence on individual motivations, facilitators, and barriers for e-bike use. This review aims at providing an overview of the current state of the art regarding individual choices and intrinsic factors to change from other modes of transport to e-bikes. Methods Searching for the term e-bike its synonyms and permutations on the databases SCOPUS, PubMed, Web of Science, and PsychINFO resulted in a total of 3,317 hits after removing duplicates. Screening of title/abstract and full-text screening is currently being conducted independently by three researchers using Covidence. Studies reporting on personal decision-making factors and reasons for a modal shift to a private e-bike are considered eligible for inclusion in this study. Studies focusing on public e-bike services are excluded. Studies will be analyzed regarding (a) research quality, (b) factors and reasons for model shift, and (c) information about the investigated populations. Results Preliminary results show a substantial increase in scientific studies related to e-bikes. After the title and abstract screening, 121 studies were included for full-text screening. Preliminary results allow assumptions about two different aspects: (a) Most studies connected the modal shift to e-bikes to facilitators rather than to barriers. Financial, temporal and social factors, along with enjoyment, health and ease of commuting seem to be among the motivators to change to an e-bike as a means of transportation, (b) the majority of studies focused on middle-aged and older populations. Conclusion The identified articles and their summary show the increased relevance of e-bikes in current research and public health. Our results may contribute to understanding the subjective reasons why people change their mode of transport to the e-bike. This knowledge may be useful for implementing public health interventions, infrastructure developments, and policies. More research is needed to better understand these factors and their impact.

Mobility Energy Productivity and Equity: E-Bike Impacts for Low-Income Essential Workers in Denver

New mobility technologies such as electrified and shared mobility, combined with polices and incentive programs, are emerging to help address sustainability and equity issues in transportation planning. However, it can be difficult to understand the impacts of novel mobility trends and emerging modes on energy-efficient access. This is owing to a lack of (1) open-source tools enabling rapid data collection, and (2) open-source metrics that consider multimodal, multiactivity access and mobility within the contexts of sustainability and equity. This paper addresses the topic of improving evaluation of transportation modes and incentive programs by integrating an open-source platform for tracking human travel data—the Open Platform for Agile Trip Heuristics (OpenPATH)—with a mobility metric that quantifies the efficiency of a region’s transportation system: Mobility Energy Productivity (MEP). Integration is demonstrated in the context of pilot programs in Colorado, where low-income essential workers were provided with electric bikes (e-bikes). OpenPATH-informed MEP calculations showed that several locations in downtown Denver provided comparable time-, cost-, and energy-efficient access to opportunities using e-bikes compared with driving. Additionally, providing e-bikes to low-income essential workers was found to be meaningful, as they utilized e-bikes the most to commute, despite driving still being their most utilized mode and the mode with highest MEP scores in Denver. We show how data collected from open-source tools coupled with robust metrics such as MEP can help evaluate the impacts of emerging mobility options. This could support developing policies to incentivize novel modes to achieve greater levels of sustainable, equitable, and efficient access.

DETERMINATION OF LOGISTICS PARAMETERS OF E-CARGO BIKES FOR SUSTAINABLE DELIVERY OF POSTAL CARGO IN CITIES

The article is devoted to formation of parameters of logistics system of cargo transportation using «green technologies». The feasibility of using a distribution center with certain parameters of the supply chain is assessed. The solution of the problem of choosing the location of the logistics center was solved simultaneously with solving the problem of routing and choosing the carrying capacity of the vehicle. The number and configuration of transportation routes depends on the volume of cargo delivery, the location of the consignor and consignees, as well as on the carrying capacity of vehicles. Each location of the distribution center determines the number of routes, the distance of transportation, the volume of traffic on each section of the routes. As a result, it was proposed to use the value of the transport work of rolling stock as an indicator that takes into account these components. The initial data for determining the effective location of the distribution center is the volume of traffic for each sender and the location of consumers. In connection with the current trends in the development of "green technologies" in urban logistics, the question of the feasibility of using freight electric bicycles at the proposed location of the city logistics center was considered. When using green technology, electric cargo bicycles were considered as vehicles. The solution to the problem of determining the most efficient distribution center was carried out taking into account the possible carrying capacity of electric bicycles. A number of bicycles with different carrying capacities that can be used to transport mail cargo were selected. It was revealed that the rational location of the distribution center ensures minimal transport work during the transportation of goods to any carrying capacity of the bicycle. To assess the effectiveness of an electric cargo bike, the amount of transport work performed using a battery capacity unit was used as a criterion. The value of this criterion is determined by the technical characteristics of the bike, namely carrying capacity, mileage on a single battery charge and battery capacity. The value of the efficiency criterion determined the ranks of bicycles taking into account technological parameters. Keywords: logistics center, electric bike, distribution center, efficiency, supply, green technology.

Detection of Electric Bicycle Indoor Charging for Electrical Safety: A NILM Approach

The increasing fire accidents caused by electric bicycle (EB) indoor charging have raised great concerns. To ensure residential electrical safety, EB is prohibited from charging indoors by regulations, but efficient monitoring of EB indoor charging behaviour in pratice still remains as a challenging problem. From the perspective of non-intrusive load monitoring (NILM), this paper proposes a holistic approach to detect the EB indoor charging behaviour. Our approach utilizes four key elements: (i) a multi-window based cumulative sum algorithm to capture the turning-on event from aggregate power; (ii) a twostage feature selection method to determine the optimal features to form an effective appliance signature for load identification; (iii) a one-class support vector machine classifier to identify whether the turned-on appliance is EB or other appliances in a semi-supervised way; (iv) a Raspberry-Pi based edge device to implement the overall NILM algorithm. The experiment results verify the effectiveness of our NILM based approach, which can obtain a high detection performance with a lowdimensional feature space, thus providing a cost-effective and high-performance solution for EB indoor charging detection.

Design and Optimization of Axial Flux Permanent Magnet Alternator for Onboard Power Generation in Two-Wheeler Applications

The Main motive of this work is to develop an Axial flux Permanent magnet alternator for on board power generation source for an electric bike. An average electric bike having a range of 40KM to 60KM per full charge will take an average of 3 hours to charge. In the present work, an onboard power generator is modeled for an electric bike which has its very own power generation system. An axial flux permanent magnet alternator is coupled to pedal and whenever the pedaling action is performed, the alternator produces power to recharge battery or also run the hub motor of the electric bike depending upon the required output voltage with the help of relay Switch. The mathematical modelling and design of the axial flux permanent magnet alternator is done using Matlab and Solidworks. Axial flux alternators are increasingly being used for large-and small-scale applications because of innovation, new material research, and manufacturing techniques that save time. Depending on the needed output power, the axial flux alternator can be built with or without an iron core and with “n” numbers of stator and rotor. The surface mounted permanent magnet technique and several one side and both side topologies with and without iron cores were designed in this work. Small-scale E-bikes employ the AFPM alternator to generate power onboard. Depending on the application, the power generated may be supplied back to a BLDC motor or used to recharge batteries. The respective results were discussed in this paper.

Phone call while riding among delivery workers: The Application of the Theory of Planned Behavior

With the rapid growth of online food delivery services, the population of delivery workers has reached 13 million in China. Most of them use electric bicycles (e-bikes) as their primary transportation tool. On the other hand, mobile phone call (MPC), as the primary and most effective communication method for delivery workers, induces distracted riding and threatens traffic safety. Although MPC has been extensively investigated in driving-related research, MPC among delivery workers has not yet been investigated. In this study, a questionnaire based on the theory of planned behavior has been designed to investigate social-psychological factors leading to MPC among delivery workers. 150 delivery workers participated in this study. The structural equation model method was adopted to analyze the data. The results show that injunctive norm is positively associated with MPC behaviors; but descriptive norm is negatively associated with MPC behaviors, potentially because of the selective perception phenomenon.

Development of Modular Wheel for Bicycle Electricfication

Our entire world is in the future. Technology has made our lives better throughout time. They use electric bicycles. Cycling is always more environmentally friendly than driving, but the E-bike has seen the most widespread adoption of green transportation during the decade. Just picture an electric bike replacing gasoline-powered scooters rather than a traditional bicycle. The paper focuses on the complete design of modular wheel for bicycle, which includes a hub motor, a customized battery pack, electrical components, and the structural elements. The entire assembly will be contained within a wheel, and wireless communication is used to transmit the throttling signal to the controller. To keep the battery pack and control circuit module to be static while the wheel is spinning was one of the main challenges we faced. The battery pack is mounted to the stator core for non-rotary operation and planetary gear setup is used to generate rotational motion. The design of a proposed modular wheel has been developed using the software tools Solid works, Ansys-Work Bench and Arduino IDE.

Challenging hegemonic velocipedic modality in the great outdoors: The seemingly inexorable rise of the electric mountain bike

Challenging hegemonic velocipedic modality in the great outdoors: The seemingly inexorable rise of the electric mountain bike

HYBRID PARTICLE SWARM OPTIMIZATION AND GREY WOLF OPTIMIZER FOR SETTING PID PARAMETERS OF BLDC MOTORS

BLDC (Brushless DC) motors have advantages over asynchronous motors and dc motors in various aspects. Particularly in electric bicycles and flying cars, BLDC motors are utilized widely. Electric bicycles and flying cars are becoming increasingly popular, and as a result, the significance of BLDC motors and their cost-effective and efficient utilization has been growing rapidly. PID (Proportional Integral Derivative) controllers are generally used in motor control because they are cheap and perform well. Many methods have been used to adjust PID parameters. Although methods such as Ziegler-Nichols, Cohen-Coon etc. are widely used, there are also new methods such as optimization algorithms PSO (Particle Swarm Optimization), Whale Optimization Technique, Gray Wolf Optimization technique etc. The hybrid method: HPSOGWO (Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer) is a combination of PSO and GWO (Grey Wolf Optimizer) techniques, and it can be used for tuning PID parameters. As associated with this, the aim of this study is to show the superiority of HPSOGWO algorithm in optimizing the PID parameters. In the content of this study, the essentials regarding the optimization background, and details of the BLDC motor modeling was explained first. After that, the methodology of the hybrid solution was expressed and then the application phase was explained in detail, by including the results generally. In the context of the intelligent optimization approach of this study, the results were obtained in the MATLAB Simulink environment. The application of the used solution method revealed its superiority over the study conducted solely with GWO in various parameters.

Dynamic Investigation of Electric Vehicle Suspension System Using Solid Works and ANSYS Software

Abstract: The suspension system affects ride comfort, handling, and safety. Optimizing suspension systems to improve rider experience and boost electric car and bike adoption is crucial as their popularity grows. ANSYS Finite Element Analysis (FEA) can analyze and optimize suspension designs for electric automobiles and bikes. FEA with ANSYS suspension system analysis and optimization is covered in this study. Electric vehicles' lower centre of gravity and variable load distribution make suspension analysis unusual, as the introduction states. Stress distribution, deformation, natural frequencies, and mode shapes analysis are described in FEA for suspension behavior. Performance, weight reduction, resource efficiency, quicker development cycles, and cost reductions are further highlighted by suspension design improvement. The paper examines multiobjective optimization, computational resource constraints, model complexity, and real-world variability as optimization difficulties. The effects of suspension system design and optimization on future electric cars and bikes are examined, highlighting the relevance of optimized suspensions in improving driving experiences and promoting electric vehicles as ecofriendly transportation solutions

Pengaruh Brand Image, Kualitas Produk Dan After Sales Service Terhadap Keputusan Pembelian

This study aims to determine the effect of brand image, product quality and after-sales service on purchasing decisions at U Winfly Malang electric bike. This study used a quantitative approach, totaling 60 consumers on U Winfly Malang electric bike who were selected by total sampling and saturated sample techniques as research subjects. The statistical analysis used in this study is with the help of the SmartPLS version 3.9 computer program. The results showed that brand image had a significant positive effect on purchasing decisions, product quality had a significant positive effect on purchasing decisions, After sales service had no significant positive effect on purchasing decisions at U Winfly electric bicycles Malang

A retrospective comparative study of maxillofacial injury patterns caused by electric scooters and bicycles.

The emergence of shared stand-up electric scooters has led to an increase in their usage and, subsequently, an increase in the incidence of maxillofacial trauma. This study aimed to investigate the trauma pattern associated with the use of stand-up electric scooters compared with that related to the use of bicycles, which was a popular mode of personal mobility before the emergence of stand-up electric scooters. This study investigated the medical records of patients who visited Wonju Christian Hospital for maxillofacial trauma due to the use of stand-up electric scooter and bicycles between November 1, 2017 and October 31, 2022. Maxillofacial trauma was analyzed based on medical records, including those in the evaluation results of teeth, maxillofacial bones, and soft tissues. Crown fractures and tooth avulsions were observed more frequently with the use of stand-up electric scooters than with the use of bicycles. In contrast, crown-root fractures, tooth subluxation, and extrusive luxation were more commonly observed in bicycle riders. Additionally, the proportion of root fractures was similar between the two groups. However, no vertical root fractures were observed in patients who rode bicycles. The maxillofacial bone fracture rates between the two groups were similar, although the fracture patterns were different. The number of patients using stand-up electric scooters is increasing, and they are likely to have a worse prognosis compared with those using existing personal mobility devices.

A bike trips survey as an impetus for the transition to sustainable cities and societies

This study aims to analyse the factors and strategies that condition the bicycle's use and highlight various unknown facts about the electric bicycle. To identify the brakes (examples: road safety, urban culture or social norms) on the use of the bicycle and the possibilities of modal shift, a survey was carried out within three main campuses at the University of Liege (ULg) in Belgium. A brief presentation of the main routes and the description of the route most taken (based on cartographic identification, a field visit and interviews) complete the survey results. During this study, 29,000 people (students, doctoral students, and staff members) were contacted to participate in the survey. The results of this work show that despite the topographical conditions of the city studied, a priori unfavourable, and some major obstacles, such as the lack of cycle paths and road insecurity, or the price in the case of the electric bicycle, the potential for a modal shift towards cycling, and particularly towards electric bicycles, is great. 70 % of respondents live less than 12 km from the University, a distance considered the limit for travelling by electric bike. Mitigating these brakes is a priority to stimulate modal shifts. The study of the image of the bicycle and the perception of the brakes shows that better communication could avoid erroneous evaluations as to the possibility of travelling by bicycle. Analysis of the profile of respondents reveals that contrary to the data in the literature, students represent the public least attracted to cycling. Initiating a modal shift to obtain a mass effect is therefore essential. One of the most important factors in pursuing a modal balance is the development of safe cycle paths, where a potential increase in bicycle use is recognized by 62 % of car users, 82 % of bus, 62 % of staff and 74 % of students. Finally, some paths are suggested to improve the downtown-rural cycle route and promote the use of bicycles in the university community.

Towards niche market for shared mobility: Identifying heterogeneity of potential early adopters to use shared electric bikes in a Chinese mega city

Shared mobility endures the pandemic, legislative upheaval, and points to a sizable potential market with wider range of shared services. As the shared mobility segment worldwide continually increases, a noticeable trend towards segmentation of shared mobility services, namely, the niche market, is gaining attention. However, the majority of scholarship has mainly focused on early adopters’ transition from conventional transportation modes to shared mobility, with little attention given to the shift towards specialized and niche shared mobility services. To address such gap, this study aims to explore the heterogeneous characteristics of potential early adopters of shared electric bikes among different transportation groups in the existing market. The questionnaire targets 1,034 citizens living in Shenzhen, a mega city in China, from March to April in 2020, before the official launch of the shared electric bikes scheme in the city. Both binary logistic models and text sentiment analysis have been conducted to present a comprehensive analytical framework to understand the group-sensitive identification of potential early adopters. Results reveal that age, car ownership, commute time, and confidence level on the potential scheme are four significant variables to explain all respondents’ willingness to adopt shared electric bikes, regardless of their existing dominant transport mode. However, when it comes to subgroups with different travel preferences, the profile of potential early adopters vary distinctly. Specifically, younger public transport users are interested in adopting shared electric bikes but have price concerns; gender is the most significant variable to predict private vehicle user’s adopt willingness, and female user show strong concerns on safety issue; users who primarily walk or cycle can benefit from shared electric bikes to travel longer distances, and lastly, there are no significant variables to predict electric bike users’ intention to switch from self-owned bikes to shared programmes. Overall, an analytical framework is presented in the study to comprehend the diverse features of prospective early adopters who may utilize shared electric bikes from different transportation groups, and a collection of development strategies for operators is proposed.

Examining the determinants of electric bike riders’ attitudes towards traffic safety and risky driving behaviours amongst high-school students in Vietnam

This study explored the influencing factors of attitudes towards traffic safety and risky driving behaviours amongst a sample of 594 e-bike riders who are high-school students in Vietnam. By using structural equation modelling, this research confirmed the significant association between traffic safety attitudes and the behaviours as well as the significant influence of traffic risk perception and safety knowledge on the traffic safety attitudes. In addition, e-bike riders’ behaviours were also significantly affected by descriptive norm. Furthermore, considering the specific characteristics of e-bike riders who are high-school students, this study found that either higher level of perceived family’s commitment to traffic safety or lower level of perceived privilege of e-bike riders who are high-school students significantly associated to both safer traffic safety attitudes and less risky driving behaviours.

Exploration of Social-Psychological Factors Leading to Distracted e-Bike Riding Among Delivery Workers in China

With the fast development of the online-to-offline market, there are over 13 million delivery workers in China, of which the primary transportation tool is electric bicycles (i.e., e-bikes). Because of the difficulty in executing enforced regulations, delivery workers usually engage in non-riding-related tasks (NRRTs) while riding e-bikes, leading to distracted riding, which can threaten traffic safety. Although distraction engagement in vehicle driving and motorcycle/bicycle riding has been extensively investigated, the prevalence of and the factors leading to distracted riding among delivery workers have not yet been explored. In this study, a survey has been designed to explore the social-psychological factors leading to NRRT engagement among delivery workers. The factors were chosen based on the theory of planned behavior (TPB) framework. We have also assessed workers’ awareness of the regulation in the survey. A total of 150 delivery workers (146 males and 4 females, mean age: 27.25) participated in the study. Results show that delivery workers tended to engage more in technology-based NRRTs, and “manually operating the phone” was the most prevalent. Compared to older peers, younger workers held more positive attitudes toward engaging in NRRTs and perceived engaging in NRRTs as more prevalent among their colleagues. TPB-related factors (i.e., attitudes, descriptive norms, injunctive norms, and perceived behavior control) were found to be correlated with self-reported NRRT engagement. The awareness of the regulations, however, had limited effects in explaining NRRT engagement. This research can provide insights into the design of countermeasures aiming at reducing the prevalence of NRRT engagement among delivery workers.

Examining the Factors Influencing the Intention to Use Electric Bikes by Young Adults: Using Extended Theory of Planned Behavior Model

The study aims to examine the factors impelling young adults’ intention to use electric bikes (EB) to promote sustainable transportation in India. In this research, the theory of planned behavior (TPB) model is extended with environmental knowledge (EKL), environmental concern (ECN), and government policy support (GPS) to understand the intention to use (ITU) of young adults on electric bikes. Using a stratified random sampling technique, the survey was conducted among 354 electric bike users across major cities from Tamil Nadu, India. The PLS-SEM was used to analyze the conceptual model of the research. The findings of the research support that ECN, EKL, and GPS have a significant positive direct influence on young adults’ attitude (ATT) and an indirect effect on the intention to use (ITU) e-bikes. Among the three mediating variables, ATT and SJN mediate the relationship between ECN, EKL, and GPS on ATT and ITU of e-bikes. The study offered insightful recommendations to broaden the scope of research on electric bike sellers and manufacturers to plan sales and marketing strategies, for the government to make policy decisions, and ultimately to increase consumer interest in sustainable transportation.