Journal articles on the topic 'Bicycle dynamics'

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1

Paudel, Milan, and Fook Fah Yap. "Development of an improved design methodology and front steering design guideline for small-wheel bicycles for better stability and performance." Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology 234, no. 3 (August 5, 2020): 227–44. http://dx.doi.org/10.1177/1754337120919608.

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The maneuverability and compactness of small-wheel and folding bicycles are greatly appreciated. Nonetheless, the performance of these small-wheel bicycles as compared to the big-wheel bicycles has always been questioned. They are often blamed for being less stable, wobbly, or twitchy. It is still unclear how the performance of the small-wheel bicycle designs can be improved. Both small- and big-wheel bicycles are designed with similar ergonomics; therefore, the focus has been on the front steering design. The steering design parameters of 91 big-wheel and 27 small-wheel bicycles were compared, bearing in mind the available front steering design guidelines to understand: (1) the influence of big-wheel bicycle’s frame design on small-wheel bicycles and (2) most common range of design parameters used in current bicycle designs. The analysis showed a strong influence of current big-wheel bicycle design practice on front frame parameter selection of small-wheel bicycles. Furthermore, the self-stability comparison over the most common design range confirmed the lesser stability in the current small-wheel bicycle designs at normal riding speed. However, it was also found that the lesser stability was not the result of small wheels per se, but rather owing to an inadequacy in the current design approach to addressing the complex influence of reducing wheel size and bicycle frame design on its stability and performance. Therefore, an improved design methodology was adopted by incorporating the bicycle dynamics into the current design approach and the front steering design guidelines for small-wheel bicycles have been developed. The guidelines contradict the current small-wheel bicycle design practice, as they recommend steeper headtube angles for small-wheel bicycles. The guidelines were validated with good agreement between the theoretical and experimental results on two prototype 20-inch-wheel bicycles having counter-intuitive steering geometry.
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2

Guo, Ning, Rui Jiang, SC Wong, Qing-Yi Hao, Shu-Qi Xue, Yao Xiao, and Chao-Yun Wu. "Experimental study on mixed traffic flow of bicycles and pedestrians." Collective Dynamics 5 (August 12, 2020): A108. http://dx.doi.org/10.17815/cd.2020.108.

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The mixed flow of bicycles and pedestrians is frequently observed on bicycle-pedestrian-shared roads. Unfortunately, studies on dynamics of this kind of mixed flow are very limited. This paper reports an experimental study of this kind of mixed traffic flow with equal numbers of pedestrians and cyclists asked to walk/ride in a ring-shaped track. In the uni-/bi-directional flow scenarios, pedestrians and bicycles moved in the same/opposite direction. Under both scenarios, bicycles and pedestrians formed their own lanes. Pedestrians walked in the inner lane and cyclists rode in the outer lane. Widths of both the pedestrian lane and the bicycle lane were more uniform in bidirectional flow. The pedestrian flow rate is larger in the unidirectional flow scenario than in the bidirectional flow scenario. In contrast, at low densities, the bicycle flow rate is essentially the same under the two scenarios. When the density is large, the bicycle flow rate becomes larger in the unidirectional flow scenario. Comparing the two modes, pedestrian flow rate is smaller/larger than bicycle flow rate at small/large densities under both scenarios.
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3

Jia, Cai, Yanyan Chen, Tingzhao Chen, Yanan Li, and Luzhou Lin. "Evolutionary Game Analysis on Sharing Bicycles and Metro Strategies: Impact of Phasing out Subsidies for Bicycle–Metro Integration Model." Sustainability 14, no. 22 (November 21, 2022): 15444. http://dx.doi.org/10.3390/su142215444.

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The rapid development of sharing bicycles has facilitated the last mile of travel and provided new opportunities for the sustainable development of metro transportation. However, there is still insufficient literature on how to promote the bicycle–metro integration mode. This paper designs a bicycle–metro integrated model based on evolutionary game theory and explores the evolutionary mechanism of the sharing of bicycles connection system and metro system under the subsidy phasing out. The conditions for achieving different equilibrium states were discussed based on the replication dynamics equation. In order to prove the evolutionary game analysis, the system dynamics simulation model was used to reveal the effects of the cost factor, subsidy factor, reward, and penalty factors on the equilibrium of the integrated model. Moreover, the values of the influence factors that make the system reach the optimal equilibrium were obtained through sensitivity analysis. The results show that by reasonably adjusting the values of the parameters, sharing bicycles connection systems, metro systems and connection travelers can reach an equilibrium state where they are willing to cooperate. Subsidy phasing-out policies for travelers were key to promoting the equilibrium of the model. The unit price of shared bicycles has a greater impact on users, and the irregular parking ratio changes have a greater impact on the benefits of travelers compared to the benefits of the metro system. In order to promote bicycle–metro integration and enhance the attractiveness of metro transportation, policies designed for participants should be integrated with dynamic evolution.
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He, Qichang, Xiumin Fan, and Dengzhe Ma. "Full Bicycle Dynamic Model for Interactive Bicycle Simulator." Journal of Computing and Information Science in Engineering 5, no. 4 (December 1, 2005): 373–80. http://dx.doi.org/10.1115/1.2121749.

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An interactive bicycle simulator with six degrees of freedom motion system could bring the rider a very realistic riding feeling. An important component of the simulator is the full bicycle dynamic model that simulated the two-wheeled bicycle dynamics. It consists of two slightly coupled submodels: The stability submodel and the vibration submodel. The stability submodel solves the stability of the bicycle under rider’s active maneuvers and the vibration submodel evaluates the vibration response of the bicycle due to uneven road surface. The model was validated by several experiments and successfully applied to the interactive bicycle simulator.
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5

Schwab, A. L., and J. D. G. Kooijman. "58786 Controllability of a bicycle(Vehicle Dynamics & Control including Tire Dynamics)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _58786–1_—_58786–7_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._58786-1_.

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6

Yin, Song, and Yuehong Yin. "Implementation of the Interactive Bicycle Simulator with Its Functional Subsystems." Journal of Computing and Information Science in Engineering 7, no. 2 (November 26, 2006): 160–66. http://dx.doi.org/10.1115/1.2720885.

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When equipped with a handlebar and pedal force display subsystem, motion-generating subsystem, and visual subsystem, the interactive bicycle simulator can bring riders a realistic cycling feeling. In the interactive bicycle simulator, the most important component is the rider-bicycle dynamic model. The Newton-Euler method is adopted to formulate this model. Real-time data gathered by sensors and identified from a terrain database system are used for calculation of the rider-bicycle dynamics. Simple and effective devices are constructed and driven by the outputs of the rider-bicycle dynamic model. These devices are successfully applied to the interactive bicycle simulator.
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7

Meijaard, J. P., and A. L. Schwab. "Bicycle and Motorcycle Dynamics." Vehicle System Dynamics 50, no. 8 (August 2012): 1191. http://dx.doi.org/10.1080/00423114.2012.707636.

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8

Xiong, J., Y. B. Jia, and C. Liu. "Symmetry and Relative Equilibria of a Bicycle System." Nelineinaya Dinamika 17, no. 4 (2021): 391–411. http://dx.doi.org/10.20537/nd210403.

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In this paper, we study the symmetry of a bicycle moving on a flat, level ground. Applying the Gibbs – Appell equations to the bicycle dynamics, we previously observed that the coefficients of these equations appeared to depend on the lean and steer angles only, and in one such equation, a term quadratic in the rear wheel’s angular velocity and a pseudoforce term would always vanish. These properties indeed arise from the symmetry of the bicycle system. From the point of view of the geometric mechanics, the bicycle’s configuration space is a trivial principal fiber bundle whose structure group plays the role of a symmetry group to keep the Lagrangian and constraint distribution invariant. We analyze the dimension relationship between the space of admissible velocities and the tangent space to the group orbit, and then employ the reduced nonholonomic Lagrange – d’Alembert equations to directly prove the previously observed properties of the bicycle dynamics. We then point out that the Gibbs – Appell equations give the local representative of the reduced dynamic system on the reduced constraint space, whose relative equilibria are related to the bicycle’s uniform upright straight or circular motion. Under the full rank condition of a Jacobian matrix, these relative equilibria are not isolated, but form several families of one-parameter solutions. Finally, we prove that these relative equilibria are Lyapunov (but not asymptotically) stable under certain conditions. However, an isolated asymptotically stable equilibrium may be achieved by restricting the system to an invariant manifold, which is the level set of the reduced constrained energy.
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9

Dieltiens, Sien, Carlos Jiménez-Peña, Senne Van Loon, Jordi D’hondt, Kurt Claeys, and Eric Demeester. "Influence of Electrically Powered Pedal Assistance on User-Induced Cycling Loads and Muscle Activity during Cycling." Applied Sciences 11, no. 5 (February 25, 2021): 2032. http://dx.doi.org/10.3390/app11052032.

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Bicycles with electrically powered pedal assistance (PA) show great potential as ecological alternatives for engine-based vehicles. There is plenty of research available about the influence of various bicycle parameters on cycling technique. Though, to the best of the authors’ knowledge, there is none about the influence of PA. In this study, a recreational bicycle is equipped with PA and unique instrumentation to measure the user-induced loads on seat, steer and pedals. Joint loading is derived in the sagittal plane from inverse dynamics and muscle activity of the lower limbs is recorded with an electromyography system integrated in cycling pants. An experiment is set up, in which volunteers cycle on an athletics track, with a varying level of PA and a varying seat height. An ANOVA is conducted to determine significant differences due to the level of PA and seat height and to analyze the interaction effect. No interaction effect was found and only differences due to the level of PA were significant. Knowledge about the influence of PA provides insights into (i) electric bicycle design; (ii) the usage of electric bicycle for physically challenged people; (iii) the usage of electric bicycles as a rehabilitation tool.
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10

IWASA, Takashi, Yoshihiro SUDA, and Yoshiaki TERUMICH. "The study on the stability of bicycles : Simulation of bicycle dynamics." Proceedings of the Transportation and Logistics Conference 2002.11 (2002): 105–8. http://dx.doi.org/10.1299/jsmetld.2002.11.105.

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11

Meijaard, J. P., Jim M. Papadopoulos, Andy Ruina, and A. L. Schwab. "Linearized dynamics equations for the balance and steer of a bicycle: a benchmark and review." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463, no. 2084 (June 11, 2007): 1955–82. http://dx.doi.org/10.1098/rspa.2007.1857.

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We present canonical linearized equations of motion for the Whipple bicycle model consisting of four rigid laterally symmetric ideally hinged parts: two wheels, a frame and a front assembly. The wheels are also axisymmetric and make ideal knife-edge rolling point contact with the ground level. The mass distribution and geometry are otherwise arbitrary. This conservative non-holonomic system has a seven-dimensional accessible configuration space and three velocity degrees of freedom parametrized by rates of frame lean, steer angle and rear wheel rotation. We construct the terms in the governing equations methodically for easy implementation. The equations are suitable for e.g. the study of bicycle self-stability. We derived these equations by hand in two ways and also checked them against two nonlinear dynamics simulations. In the century-old literature, several sets of equations fully agree with those here and several do not. Two benchmarks provide test cases for checking alternative formulations of the equations of motion or alternative numerical solutions. Further, the results here can also serve as a check for general purpose dynamic programs. For the benchmark bicycles, we accurately calculate the eigenvalues (the roots of the characteristic equation) and the speeds at which bicycle lean and steer are self-stable, confirming the century-old result that this conservative system can have asymptotic stability.
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12

Sun, Shouheng. "How Does the Collaborative Economy Advance Better Product Lifetimes? A Case Study of Free-Floating Bike Sharing." Sustainability 13, no. 3 (January 29, 2021): 1434. http://dx.doi.org/10.3390/su13031434.

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The collaborative economy is considered to have great potential in promoting the circular economy. However, there is little empirical research in this field. Taking the Beijing free-floating bike sharing (FFBS) program as an example, this study develops a system dynamics (SD) model based on the product lifetime extension business model (PLEBM) framework, and the business practices of FFBS. Combined with the dynamic evolution process of the FFBS market, the impact of FFBS on bicycle lifetime and the utilization efficiency of the urban bicycle system is explored. The results show that FFBS can reduce the required supply scale of the entire bicycle system by about 21%, and increase the average daily usage of bicycles by about 27%. In addition, FFBS also can increase the average lifecycle trip volume per bike in the entire urban bicycle system from approximately 900 to 1060, an increase of 16%. In particular, this study estimates that the optimal supply scale of the FFBS market in Beijing is about 800,000. It is worth noting that although enhancing the PLE strategy can increase the contribution of FFBS to PLE, it may also deteriorate the profitability of the FFBS platform. The authorities and FFBS operators should work together to continuously improve the profitability of the platform and strengthen its innovation capabilities to promote the healthy and sustainable development of FFBS.
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13

Tan, W. H., M. Ashraf, L. E. Ooi, and J. Niresh. "Static and Dynamics Analysis of Bicycle Frame." Journal of Physics: Conference Series 2051, no. 1 (October 1, 2021): 012032. http://dx.doi.org/10.1088/1742-6596/2051/1/012032.

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Abstract Leisure bike became a trend among the people in Malaysia as their method of exercise. The problem rises as the riders start to complain about their muscle fatigue after long cycling. This study aims to determine how the changing of material of the bicycle frame and the insertion of the suspension system can reduce vibration. This study was conducted using aluminium alloy as the material for bicycle frame to reduce the vibration and the weight of the bike. The suspension system has also been customized into the bicycle frame as the main vibration absorber. The CAD model was developed and been analysed using static and dynamic analysis based on the specific boundary condition. The result showed a small deformation occurs on the frame that causes the frame to deflect from the original shape as depicted in modal analysis. Overall, it is concluded that a suspension system adopted on the bicycle frame can have a significant enhancement in vibration reduction on the rider.
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14

Zhuang, Wei, Gaoming Li, Ruixin Zhang, Xiao Su, and Yonghua Huang. "Dynamical model of a new type of self-balancing tractor-trailer-bicycle." MATEC Web of Conferences 309 (2020): 05002. http://dx.doi.org/10.1051/matecconf/202030905002.

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In this paper, we focused on a Self-Balancing Tractor-Trailer-Bicycle(TTB) and developed an under-actuated dynamical model for the system. The bicycle is characterized with two parts, that is a tractor and a trailer, and considering the nonholonomic constrains from no-slipping contacts of its three wheels and the flat ground, we presented a dynamical model for the bicycle by using Chaplygin equation. The model suggest that the TTB should be an under-actuated system with three DOF (degree of freedom) and there are two driving-torque inputs. An inverse dynamics and a virtual prototype simulations are given to demonstrate the correctness of the proposed dynamical model.
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15

Sharp, R. S. "Optimal stabilization and path-following controls for a bicycle." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 221, no. 4 (April 1, 2007): 415–27. http://dx.doi.org/10.1243/0954406jmes529.

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The article is about stabilizing and path-tracking control of a bicycle by a rider. It is based on previously published work, in which it has been shown how a driver's or rider's preview of the roadway can be combined with the linear dynamics of an appropriate vehicle to yield a problem of discrete-time optimal-linear-control-theory form. In the previous work, it was shown how an optimal ‘driver’ converts path preview sample values, modelled as deriving from a Gaussian white-noise process, into steering control inputs to cause the vehicle to follow the previewed path. The control compromises between precision and ease, to an extent that is controllable through choice of weights in the optimal control calculations. Research into the dynamics of bicycles has yielded a benchmark model, with equations of motion firmly established by extensive cross-checking. Model predictions have been verified for modest speeds by experimental testing. The established optimal linear preview stabilizing and tracking control theory is now brought together with the benchmark bicycle description to yield optimal controls for the bicycle for variations in speed and performance objectives. The resulting controls are installed in the bicycle, giving a virtual rider-controlled system, and frequency responses of the rider-controlled system are calculated to demonstrate tracking capability. Then path-tracking simulations are used to illustrate the behaviour of the controlled system. Tight and loose controls, representing different balances between tracking accuracy and control effort, are calculated and illustrated through the simulations.
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16

Franke, G., W. Suhr, and F. Riess. "An advanced model of bicycle dynamics." European Journal of Physics 11, no. 2 (March 1, 1990): 116–21. http://dx.doi.org/10.1088/0143-0807/11/2/010.

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17

Bermúdez-Hernández, Jonathan, Sebastián Cardona-Acevedo, Alejandro Valencia-Arias, Lucía Palacios-Moya, and Nelly Dioses Lescano. "Behavioural Factors for Users of Bicycles as a Transport Alternative: A Case Study." Sustainability 14, no. 24 (December 15, 2022): 16815. http://dx.doi.org/10.3390/su142416815.

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Recent mobility and transportation dynamics have shaped the main sustainability problems of today, evidencing the need to potentiate alternative, flexible, environmentally friendly transportation means—such as bicycles—that significantly contribute to the health and well-being of users. However, in cities that are just beginning to implement bicycle systems or are seeking to achieve high levels of bicycle use, it is important to know which are the most relevant factors that users consider when using this type of medium. Therefore, the objective of this study was to identify the main behavioural factors among users of the public bicycle programme EnCicla in the city of Medellín, Colombia. Confirmatory factor analysis of responses to a self-administered questionnaire, elaborated based on the Theory of Planned Behaviour, was conducted using the statistical tool Statistical Product and Service Solutions (SPSS). Among the main results, the behavioural factors that further explained behavioural intention were attitude towards behaviour and perceived behavioural control, with values of 0.579 and 0.519, respectively (Cramér coefficient or Cramér’s V). The relevance of these factors lies in the implementation of dynamics that affect a better assessment by users of public bicycles in the EnCicla system, increasing satisfaction with the service and promoting greater adoption in the context of current mobility needs. The practical implications of this study are related to the possibility of designing strategies and public policies to enhance this means of transport in the cities where it is implemented, or to prepare a possible implementation in those that plan to do so.
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Doria, Alberto, Mauro Tognazzo, Gianmaria Cusimano, Vera Bulsink, Adrian Cooke, and Bart Koopman. "Identification of the mechanical properties of bicycle tyres for modelling of bicycle dynamics." Vehicle System Dynamics 51, no. 3 (March 2013): 405–20. http://dx.doi.org/10.1080/00423114.2012.754048.

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19

LIANG, Xiao, Baohua MAO, and Qi XU. "Psychological-Physical Force Model for Bicycle Dynamics." Journal of Transportation Systems Engineering and Information Technology 12, no. 2 (April 2012): 91–97. http://dx.doi.org/10.1016/s1570-6672(11)60197-9.

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20

KAINO, Go, Toshinobu TAKEI, and Takashi TSUBOUCHI. "2A1-C07 3D dynamics simulation for bicycle." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2007 (2007): _2A1—C07_1—_2A1—C07_4. http://dx.doi.org/10.1299/jsmermd.2007._2a1-c07_1.

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21

Xiong, Jiaming, Nannan Wang, and Caishan Liu. "Stability analysis for the Whipple bicycle dynamics." Multibody System Dynamics 48, no. 3 (October 2, 2019): 311–35. http://dx.doi.org/10.1007/s11044-019-09707-y.

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22

Maier, Oliver, Stefan Hillenbrand, Jürgen Wrede, Andreas Freund, and Frank Gauterin. "Vertical and Longitudinal Characteristics of a Bicycle Tire." Tire Science and Technology 46, no. 3 (July 1, 2018): 153–73. http://dx.doi.org/10.2346/tire.18.460301.

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ABSTRACT Electric bicycles have undergone a real boom in recent years and play an important role in the area of sustainable mobility. In addition to assisting the rider while accelerating the bicycle, the available electrical energy also offers the possibility to deploy safety systems to reduce the risk of accidents. For instance, active safety systems could help to avoid two major critical braking situations for single-track vehicles: front wheel lockup and nose-over (i.e., falling over the handlebars). An essential prerequisite for the development of such systems is a thorough understanding of tire effects on bicycle dynamics. To date, there are only very few scientific studies concerning bicycle tire characteristics. Thus, test runs on an inner drum tire test bench have been performed to measure vertical and longitudinal characteristics of a typical trekking bike tire. This article presents the main findings such as vertical stiffness and contact patch geometry depending on wheel load and inflation pressure as well as characteristic curves of the longitudinal force depending on slip with variation in road condition, wheel load, speed, and inflation pressure. Based on these valuable insights, further improvements are proposed, and an outlook on the next research steps is given.
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23

Huang, Yonghua, Qizheng Liao, Lei Guo, and Shimin Wei. "Simple realization of balanced motions under different speeds for a mechanical regulator-free bicycle robot." Robotica 33, no. 9 (May 15, 2014): 1958–72. http://dx.doi.org/10.1017/s026357471400112x.

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SUMMARYMechanical regulator-free bicycle robots have lighter weight and fewer actuators than the traditional regulator-based bicycle robots. In order to deal with the difficulty of maintaining balance for this kind of bicycle robot, we consider a front-wheel drive and mechanical regulator-free bicycle robot. We present the methodologies for realizing the robot's ultra-low-speed track-stand motion, moderate-speed circular motion and high-speed rectilinear motion. A simplified dynamics of the robot is developed using three independent velocities. From the dynamics, we suggest there may be an underactuated rolling angle in the system. Our balancing strategies are inspired by human riders' experience, and our control rules are based on the bicycle system's underactuated dynamics. In the case of track-stand and circular motion, we linearize the frame's rolling angle and configure the robot to maintain balance by the front-wheel's motion with a fixed front-bar turning angle. In the case of the rectilinear motion, we linearize both front-bar steering angle and front-wheel rotating angle, and configure the system to maintain balance by the front-bar's turning with a constant front-wheel rotating rate. Numerical simulations and physical experiments are given together to validate the effectiveness of our control strategies in realizing the robot's proposed three motions.
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Arifin, A., T. M. Tsai, and I. Siswanto. "An Analysis of Vibration Reduction Design on the Bicycle Frame Based on Multi-Body Dynamics Simulation." Journal of Physics: Conference Series 1700, no. 1 (December 1, 2020): 012081. http://dx.doi.org/10.1088/1742-6596/1700/1/012081.

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Abstract In recent years, the awareness of environmental protection has risen, and modern people’s quality of life has improved. Bicycles are no longer just general transportation and carrying tools, but evolved into the need to emphasize comfortable riding, energy-saving and carbon reduction, and physical fitness. In this study, the different vehicle-to-weight ratio and road bumpiness before and after designing the bicycle frame’s damping and stiffness parameters were considered. The simulation results designate that the seat acceleration in both the y and z-axis is adequate constant, and the seat velocity gradually increases, whereas the vertical seat displacement of damped has significantly reduced compared with undamped.
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Schwab, A. L., and J. P. Meijaard. "A review on bicycle dynamics and rider control." Vehicle System Dynamics 51, no. 7 (July 2013): 1059–90. http://dx.doi.org/10.1080/00423114.2013.793365.

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26

Jiang, Rui, Mao-Bin Hu, Qing-Song Wu, and Wei-Guo Song. "Traffic Dynamics of Bicycle Flow: Experiment and Modeling." Transportation Science 51, no. 3 (August 2017): 998–1008. http://dx.doi.org/10.1287/trsc.2016.0690.

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Klug, Silas, Alessandro Moia, Armin Verhagen, Daniel Görges, and Sergio M. Savaresi. "Effectiveness of Actuating on Rectilinear Bicycle Braking Dynamics." IFAC-PapersOnLine 50, no. 1 (July 2017): 972–79. http://dx.doi.org/10.1016/j.ifacol.2017.08.173.

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Wood, Jo, Aidan Slingsby, and Jason Dykes. "Visualizing the Dynamics of London's Bicycle-Hire Scheme." Cartographica: The International Journal for Geographic Information and Geovisualization 46, no. 4 (December 2011): 239–51. http://dx.doi.org/10.3138/carto.46.4.239.

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29

Fregly, Benjamin J., Felix E. Zajac, and Christine A. Dairaghi. "Bicycle Drive System Dynamics: Theory and Experimental Validation." Journal of Biomechanical Engineering 122, no. 4 (March 22, 2000): 446–52. http://dx.doi.org/10.1115/1.1286678.

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Bicycle pedaling has been studied from both a motor control and an equipment setup and design perspective. In both cases, although the dynamics of the bicycle drive system may have an influence on the results, a thorough understanding of the dynamics has not been developed. This study pursued three objectives related to developing such an understanding. The first was to identify the limitations of the inertial/frictional drive system model commonly used in the literature. The second was to investigate the advantages of an inertial/frictional/compliant model. The final objective was to use these models to develop a methodology for configuring a laboratory ergometer to emulate the drive system dynamics of road riding. Experimental data collected from the resulting road-riding emulator and from a standard ergometer confirmed that the inertial/frictional model is adequate for most studies of road-riding mechanics or pedaling coordination. However, the compliant model was needed to reproduce the phase shift in crank angle variations observed experimentally when emulating the high inertia of road riding. This finding may be significant for equipment setup and design studies where crank kinematic variations are important or for motor control studies where fine control issues are of interest. [S0148-0731(00)02004-5]
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Boyer, Frédéric, Mathieu Porez, and Johan Mauny. "Reduced Dynamics of the Non-holonomic Whipple Bicycle." Journal of Nonlinear Science 28, no. 3 (December 27, 2017): 943–83. http://dx.doi.org/10.1007/s00332-017-9434-x.

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31

Zeng, Peng, Ming Wei, and Xiaoyang Liu. "Investigating the Spatiotemporal Dynamics of Urban Vitality Using Bicycle-Sharing Data." Sustainability 12, no. 5 (February 25, 2020): 1714. http://dx.doi.org/10.3390/su12051714.

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In recent decades, the availability of diverse location-based service (LBS) data has largely stimulated the research in individual human mobility. However, less attention has been paid on the intra-city movement of cyclists coupled with their spatiotemporal dynamics. To fill the knowledge gap, drawing on bicycle-sharing data over one week in Shanghai, China, this study investigates the dynamics of bicycle-sharing users at two spatial scales (i.e., city level and subdistrict level) and explores the intra-city spatial interactions by those cyclists. At the city level, by applying the analysis of variance (ANOVA) test and the Wilcoxon signed-rank test, this study examines the temporal variation of cyclists across a seven-day period. At the subdistrict level, we develop a new index to capture the urban vitality using bicycle-sharing data with the consideration of trip flow allied with spatial weights. In terms of the computed urban vitality over the course of a day, 98 subdistricts are partitioned into 7 groups by using K-means clustering. In addition, spatial autocorrelation and hot spot analysis are also applied to examine the spatial features of urban vitality at different periods. Our results reveal that urban vitality has an obvious character of the spatial cluster and this cluster feature varies markedly over the course of a day. By shedding new lights on intra-city movement, we argue our results are important in informing urban planners on how to better allocate public facilities and increase bicycle usage as a way to progress towards more sustainable urban areas.
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BORGNAT, PIERRE, PATRICE ABRY, PATRICK FLANDRIN, CÉLINE ROBARDET, JEAN-BAPTISTE ROUQUIER, and ERIC FLEURY. "SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE." Advances in Complex Systems 14, no. 03 (June 2011): 415–38. http://dx.doi.org/10.1142/s0219525911002950.

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Community shared bicycle systems, such as the Vélo'v program launched in Lyon in May 2005, are public transportation programs that can be studied as a complex system composed of interconnected stations that exchange bicycles. They generate digital footprints that reveal the activity in the city over time and space, making possible a quantitative analysis of movements using bicycles in the city. A careful study relying on nonstationary statistical modeling and data mining allows us to first model the time evolution of the dynamics of movements with Vélo'v, that is mostly cyclostationary over the week with nonstationary evolutions over larger time-scales, and second to disentangle the spatial patterns to understand and visualize the flows of Vélo'v bicycles in the city. This study gives insights on the social behaviors of the users of this intermodal transportation system, the objective being to help in designing and planning policy in urban transportation.
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33

Dialynas, Georgios, Jelle W. de Haan, Alfred C. Schouten, Riender Happee, and Arend L. Schwab. "The dynamic response of the bicycle rider’s body to vertical, fore-and-aft, and lateral perturbations." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 7 (December 20, 2019): 1944–57. http://dx.doi.org/10.1177/0954407019891289.

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The objective of this study was to identify the dynamic response of the bicycle rider’s body during translational perturbations, in an effort to improve two-wheeler safety and comfort. A bicycle mock-up was equipped with sensors measuring three-dimensional seat and trunk accelerations and rider’s force responses at the seat, handlebars, and footpegs. The bicycle mock-up was driven by a hexapod motion platform that generated random noise perturbations in the range of 0–10 Hz. Twenty-four healthy male adults participated in this study. Responses are represented as frequency response functions capturing three-dimensional force interactions of the rider’s body at the seat, handlebars and footpegs in terms of apparent mass, and rider’s trunk motion (one-dimensional) as function of seat motion as seat-to-sternum transmissibility. Results showed that the vertical and longitudinal apparent mass for most of the bicycle interfaces followed the resonance of the seat-to-sternum transmissibility. A twice as high magnitude was observed at the resonance, although a more heavily damped system was apparent in the seat-to-sternum transmissibility. Resonant frequencies were considerably higher in the vertical direction compared to the longitudinal direction. Different dynamics were observed for the lateral measurements, where all magnitudes decreased after the base frequency, and no resonance was observed.
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34

Guo, Ning, Rui Jiang, SC Wong, Qing-Yi Hao, Shu-Qi Xue, and Mao-Bin Hu. "Bicycle flow dynamics on wide roads: Experiments and simulation." Transportation Research Part C: Emerging Technologies 125 (April 2021): 103012. http://dx.doi.org/10.1016/j.trc.2021.103012.

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35

Dao, Trung-Kien, and Chih-Keng Chen. "A study of bicycle dynamics via system identification approaches." Journal of the Chinese Institute of Engineers 35, no. 7 (October 2012): 853–68. http://dx.doi.org/10.1080/02533839.2012.708533.

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36

IWASA, Takashi, Yoshihiro SUDA, and Yoshiaki TERUMICH. "Study on Stability of a Bicycle Using Multibody Dynamics." Proceedings of the JSME annual meeting 2003.7 (2003): 357–58. http://dx.doi.org/10.1299/jsmemecjo.2003.7.0_357.

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37

YOSHIMURA, Hiroaki, Yasushi YAMASHITA, and Yuji YAMADA. "4023 Dynamics of a Bicycle and its Numerical Simulations." Proceedings of the JSME annual meeting 2005.7 (2005): 327–28. http://dx.doi.org/10.1299/jsmemecjo.2005.7.0_327.

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38

Borin, Veniamin A., Christian Wiebeler, and Igor Schapiro. "A QM/MM study of the initial excited state dynamics of green-absorbing proteorhodopsin." Faraday Discussions 207 (2018): 137–52. http://dx.doi.org/10.1039/c7fd00198c.

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39

Mohamed Belrzaeg, Abdussalam Ali Ahmed, Amhimmid Q Almabrouk, Mohamed Mohamed Khaleel, Alforjani Ali Ahmed, and Meshaal Almukhtar. "Vehicle dynamics and tire models: An overview." World Journal of Advanced Research and Reviews 12, no. 1 (October 30, 2021): 331–48. http://dx.doi.org/10.30574/wjarr.2021.12.1.0524.

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Stability control system plays a significant role in vehicle dynamics to improve the vehicle handling and achieve better stability performance. In order to study and evaluate the performance of the vehicles in addition to how to control it, it is necessary to identify obtain some models related to the dynamics of the vehicle as well as the tire models. This paper presents fundamentals of vehicle dynamics by introducing vehicle models and tire model, which have been widely adopted for vehicle motion control. This helps to get a basic idea of what parameters and states of a vehicle are important in vehicle motion control. This work is separated into four sections: vehicle planar model, full vehicle model, two degrees of freedom vehicle model (bicycle model) to design the controller, and wheel dynamic model.
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40

Mohamed, Amr, and Alexander Y. Bigazzi. "Generation of “Biking Schedules” for Bicycle Travel Analysis." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 36 (June 11, 2018): 83–91. http://dx.doi.org/10.1177/0361198118776812.

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With an increasing focus on bicycling as a mode of urban transportation, there is a pressing need for improved tools for bicycle travel analysis and modeling. This paper introduces “biking schedules” to represent archetypal urban cycling dynamics, analogous to driving schedules used in vehicle emissions analysis. Three different methods of constructing biking schedules with both speed and road grade attributes are developed from the driving schedule literature. The methods are applied and compared using a demonstration data set of 55 h of 1-Hz on-road GPS data from three cyclists. Biking schedules are evaluated based on their ability to represent the speed dynamics, power output, and breathing rates of a calibration data set and then validated for different riders. The impact of using coarser 3, 5, and 10 s GPS logging intervals on the accuracy of the schedules is also evaluated. Results indicate that the best biking schedule construction method depends on the volume and resolution of the calibration data set. Overall, the biking schedules successfully represent most of the assessed characteristics of cycling dynamics in the calibration data set (speed, acceleration, grade, power, and breathing) within 5%. Future work will examine the precision of biking schedules constructed from larger data sets in more diverse cycling conditions and explore additional refinements to the construction methods. This research is considered a first step toward adopting biking schedules in bicycle travel analysis and modeling, and potential applications are discussed.
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41

FUKADA, Ryosuke, Akinori TOMODA, and Tetsuya WATANABE. "21406 Dynamics of Human-Bicycle System during Off-Road Cycling." Proceedings of Conference of Kanto Branch 2013.19 (2013): 593–94. http://dx.doi.org/10.1299/jsmekanto.2013.19.593.

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42

Wang, Everett X., Juncheng Zou, Gengping Xue, Yijun Liu, Yang Li, and Qun Fan. "Development of Efficient Nonlinear Benchmark Bicycle Dynamics for Control Applications." IEEE Transactions on Intelligent Transportation Systems 16, no. 4 (August 2015): 2236–46. http://dx.doi.org/10.1109/tits.2015.2404339.

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43

Konishi, Yasuharu, and Kazuo Yoshida. "332 Modeling and Stabilizing Control for Dynamics of a Bicycle." Proceedings of the Symposium on the Motion and Vibration Control 2001.7 (2001): 456–58. http://dx.doi.org/10.1299/jsmemovic.2001.7.456.

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44

Xiong, Jiaming, Nannan Wang, and Caishan Liu. "Bicycle dynamics and its circular solution on a revolution surface." Acta Mechanica Sinica 36, no. 1 (December 14, 2019): 220–33. http://dx.doi.org/10.1007/s10409-019-00914-6.

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45

Trenchard, Hugh, Erick Ratamero, Ashlin Richardson, and Matjaž Perc. "A deceleration model for bicycle peloton dynamics and group sorting." Applied Mathematics and Computation 251 (January 2015): 24–34. http://dx.doi.org/10.1016/j.amc.2014.11.031.

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46

Vanwalleghem, Joachim, Frederik Mortier, Ives De Baere, Mia Loccufier, and Wim Van Paepegem. "Design of an instrumented bicycle for the evaluation of bicycle dynamics and its relation with the cyclist's comfort." Procedia Engineering 34 (2012): 485–90. http://dx.doi.org/10.1016/j.proeng.2012.04.083.

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47

Alves, Alexandre de Castro, Angelo Marcelo Tusset, Jose Manoel Balthazar, Jeferson Jose de Lima, Frederic Conrad Janzen, Rodrigo Tumolin Rocha, and Airton Nabarrete. "SDRE Control Applied to the Wheel Speed of a Compressed Air Engine with Crank-Connecting-Rod Mechanism." Shock and Vibration 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/8340510.

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Renewable energy sources for vehicles have been the motivation of many researches around the world. The reduction of fossil fuels deposits and increase of the pollution in cities bring the need of more efficient and cleaner energy sources. In this way, this work will present the application of a compressed air engine applied to a bicycle. The engine is composed of two pneumatic cylinders connected to the bicycle wheel through a crank-connecting-rod mechanism. In order to control the velocity of the bicycle, a strategy of control composed of two controls was implemented: a feedback and a feedforward control. For feedback control, the State-Dependent Riccati Equation (SDRE) control and also a proportional-derivative (PD) control are considered, considering three cases for velocity bicycle variation: 10 km/h, 20 km/h, and 30 km/h. The equations of motion of the system were obtained through the Lagrangian energy method. Numerical simulations were performed in order to analyze the dynamics of the system and the efficiency of the controllers.
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48

Zhang, Kaiming, Xudong Zheng, Zhang Chen, Bin Liang, Tianshu Wang, and Qi Wang. "Non-smooth dynamic modeling and simulation of an unmanned bicycle on a curved pavement." Applied Mathematics and Mechanics 43, no. 1 (January 2022): 93–112. http://dx.doi.org/10.1007/s10483-022-2811-5.

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AbstractThe non-smooth dynamic model of an unmanned bicycle is established to study the contact-separate and stick-slip non-smooth phenomena between wheels and the ground. According to the Carvallo-Whipple configuration, the unmanned bicycle is reduced to four rigid bodies, namely, rear wheel, rear frame, front fork, and front wheel, which are connected by perfect revolute joints. The interaction between each wheel and the ground is simplified as the normal contact force and the friction force at the contact point, and these forces are described by the Hunt-Crossley contact force model and the LuGre friction force model, respectively. According to the characteristics of flat and curved pavements, calculation methods for contact forces and their generalized forces are presented. The dynamics of the system is modeled by the Lagrange equations of the first kind, a numerical solution algorithm of the dynamic equations is presented, and the Baumgarte stabilization method is used to restrict the drift of the constraints. The correctness of the dynamic model and the numerical algorithm is verified in comparison with the previous studies. The feasibility of the proposed model is demonstrated by simulations under different motion states.
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49

Dębowski, A., J. J. Faryński, and D. P. Żardecki. "The bicycle model of a 4WS car lateral dynamics for lane change controller." IOP Conference Series: Materials Science and Engineering 1247, no. 1 (July 1, 2022): 012021. http://dx.doi.org/10.1088/1757-899x/1247/1/012021.

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Abstract The article shows the validity of four-wheel steering (4WS) bicycle model. At the beginning it is presented in which tasks, connected with 4WS vehicles, the bicycle model is applied. Then the equations in local coordinate system and their forms in global coordinate system are presented. The research tested the response of the model to a lane change manoeuvre, using transfer functions and a “bang-bang” control signal. The transfer functions was connected with static ratio characteristic to construct full four-wheel steering model. A reference signal generator and vehicle model were constructed in analytical form and checked in Matlab&Simulink using sample vehicle’s data from another literature item. One example of simulations was shown. The results presented led to interesting conclusions and indicated directions for further research. This research will include the issue of regulators derivation. This will allow for the construction of a fully functioning control system. The effects of this activities will be tested again in simulation environment.
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Syamsuri, Syamsuri, Hasan Syafik Maulana, and Achmad Syarifuddin. "Numerical Study on the Characteristics of Air Flows through Helmet Bicycle Racing Using the Effect of Variation of Trailing Edge." Journal of Energy Mechanical Material and Manufacturing Engineering 6, no. 1 (May 7, 2021): 53–58. http://dx.doi.org/10.22219/jemmme.v6i1.12573.

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Research on aerodynamics on racing bicycles always develops from time to time. The various geometry of a time-trial helmet produces different characteristics of fluid flow, this is due to the relative movements of air that are in the area throughout the body shape of the helmet. Basically the fluid flow that passes on a racing bicycle helmet will produce a drag force, where this must be minimized in order to hinder the pace of drivers to achieve maximum speed, so drivers should pay attention to how to design the geometry of helmet that should be used. Computational fluid dynamics (CFD) method is used to simulate the case studies in this research. In this study, four kinds of models trailing edge geometry was varied to determine where the most optimal in accepting the drag force. The validation was also conducted to determine the suitability of this study with prior research, where in this validation the results of this study are compared with the research owned (Sims and Jenkins, 2011). The results of this validation show that the resulting drag coefficient has a very small difference of 0.001. The four models are simulated with Reynold number values of 7.14 × 104, 1.00 × 105, and 1.16 × 105. The results of this study indicate that with differences in the geometry of the trailing edge affect the drag force that occurs. From the research result when Reynold 7.0 x 10 ^ 4, the drag force produced by model 3 is bigger than model 1 and 2 which is equal to 0.182 N. Whereas on Reynold which is bigger 1.16 x 10 ^ 5 model 3 receives drag smaller than model 1 and 2 which is equal to 0.283 N. In the world of bicycle racing, the difference in the small drag force affects the speed of the bicycle and affects the resulting victory.
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