Motorcycle's lateral stability issues: Comparison of methods for dynamic modelling of roll angle

Bonci, Andrea; Amicis, Riccardo De; Longhi, Sauro; Lorenzoni, Emanuele; Scala, Giuseppe Antonio

doi:10.1109/icstcc.2016.7790733

Cited by 9 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As an overall result, the effect of the steering error on the trajectory appears negligible and the symbolic model performs the same as the multibody model both under the assumptions made of small angles and beyond them. Similar overperformance in the roll angle was outlined in a previous work [36] related to single track vehicle.…”

Section: A Cornering Comparative Validationsupporting

confidence: 76%

Towards an All-Wheel Drive Motorcycle: Dynamic Modeling and Simulation

2020

Self Cite

View full text Add to dashboard Cite

Modern motorcycles are evolving more and more towards complex systems by the increasing integration of mechanical, electrical and control disciplines. All-wheel drive (AWD) vehicles have proven effective to improve vehicle's performances and rider's safety. Despite this, manufacturers have developed few AWD motorcycles and little research has been devoted to them. Obvious difficulties concern torque distribution to the front wheel because of steering system. Nowadays, the integration of technologies eases the implementation of front wheel drive opening new research perspectives. In this work, the dynamic model of an AWD motorcycle with an attached rider is proposed. It represents the first symbolic analysis investigating the effects of front wheel traction on the dynamics of a motorcycle for supporting the design of AWD motorcycles reducing trials and tests on prototypes. The proposed model is parametric with respect to the motorcycle geometry, and it allows to simulate complex operating modes of the AWD, such as cornering phenomena, taking into account coupling of lateral and longitudinal dynamics and tire-road interactions. Unlike other works, here the authors include a full tire model by exploiting theoretical slips of the brush model for tire's aligning moment too, instead of applying a totally empirical representation less suitable for a complete symbolic description. Besides, to simulate the equations of motion, the benefits and disadvantages of using AWD with torque distribution have been pointed out introducing a new handling ratio. Two verification procedures validate the model: one is performed theoretically, the other carries out a comparison with a multibody software, whose model is more sophisticated, this latter embeds all main motorcycle's dynamics. Although radically different, being the first theoretical and the second numericalcomputational, both methods exhibit consistent behavior between them, and effectiveness of the former is also consistent with the results of a multibody simulator under the assumptions made.

show abstract

Section: A Cornering Comparative Validationsupporting

confidence: 76%

Towards an All-Wheel Drive Motorcycle: Dynamic Modeling and Simulation

2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the automotive sector, even more than in robotics, at least two other aspects have gained relevance, namely communication between real-time systems (e.g., for driver assistance) [59,60] and active vehicle safety systems [61,62] that autonomous driving systems must take into account. The latter aspect is even more critical for two-, three-, or allwheel-drive vehicles that require more complex behavioral models, as discussed in [63][64][65], respectively. Thus, the trend is to require software to have an increasing ability to integrate heterogeneous and real-time systems.…”

Section: Ros2: Other Applicationsmentioning

confidence: 99%

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Bonci,

Gaudeni,

Giannini

et al. 2023

Applied Sciences

Self Cite

View full text Add to dashboard Cite

Future challenges in manufacturing will require automation systems with robots that are increasingly autonomous, flexible, and hopefully equipped with learning capabilities. The flexibility of production processes can be increased by using a combination of a flexible human worker and intelligent automation systems. The adoption of middleware software such as ROS2, the second generation of the Robot Operating System, can enable robots, automation systems, and humans to work together on tasks that require greater autonomy and flexibility. This paper has a twofold objective. Firstly, it provides an extensive review of existing literature on the features and tools currently provided by ROS2 and its main fields of application, in order to highlight the enabling aspects for the implementation of modular architectures to increase autonomy in industrial operations. Secondly, it shows how this is currently potentially feasible in ROS2 by proposing a possible high-level and modular architecture to increase autonomy in industrial operations. A proof of concept is also provided, where the ROS2-based framework is used to enable a cobot equipped with an external depth camera to perform a flexible pick-and-place task.

show abstract

“…The chosen dynamics need to be validated to determine if they are enough to describe three behaviors: the position of the vehicle, the speed of the vehicle and the energetic behavior of the vehicle as a function of the two first aspects and external conditions. This validation will be made using a dynamic model software simulation tool because it already accomplishes with the vehicle market standards (resolution and accuracy) and it lets to change external road characteristics easily [18]. When all relevant dynamics for energetic behavior were identified and modeled, the controller needs to be proposed to reduce the impact of external conditions over the error in maximum efficiency point of work proposed by the inverter.…”

Section: Methodsmentioning

confidence: 99%

“…This dynamic is ignored. In conclusion, the dynamic model required is composed by following states, inputs, and parametric inputs [4], [18]:…”

Section: Mechanical Modellingmentioning

confidence: 99%

Eco-Driving planification profile for electric motorcycles

Ceferino¹

View full text Add to dashboard Cite

Los perfiles de Eco-Driving son algoritmos capaces de utilizar información adicional para crear recomendaciones o limitaciones sobre las capacidades del conductor. Aumentan la autonomía del vehículo, pero actualmente su uso no está relacionado con la autonomía requerida por el conductor. Por esta razón, en este trabajo, el desafío de la conducción ecológica se traduce en un controlador óptimo de dos capas diseñado para vehículos eléctricos puros. Este controlador está orientado a asegurar que la energía disponible sea suficiente para completar un viaje demandado, agregando límites de velocidad para controlar la tasa de consumo de energía. Se exponen y analizan los modelos mecánicos y eléctricos requeridos. La función de costo está optimizada para corresponder a las necesidades de cada viaje de acuerdo con el comportamiento del conductor, el vehículo y la información de la trayectoria. El controlador óptimo propuesto en este trabajo es un controlador predictivo de modelo no lineal (NMPC) asociado a una optimización unidimensional no lineal. La combinación de ambos algoritmos permite aumentar alrededor de un 50% la autonomía con una limitación del 30% de las capacidades de velocidad y aceleración. Además, el algoritmo es capaz de asegurar una autonomía final con un 1,25% de error en presencia de ruido de sensor y actuador.

show abstract

Motorcycle's lateral stability issues: Comparison of methods for dynamic modelling of roll angle

Cited by 9 publications

References 9 publications

Towards an All-Wheel Drive Motorcycle: Dynamic Modeling and Simulation

Towards an All-Wheel Drive Motorcycle: Dynamic Modeling and Simulation

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Eco-Driving planification profile for electric motorcycles

Contact Info

Product

Resources

About