Motorcycle Model Research Articles

Influence of the Road Model on the Optimal Maneuver of a Racing Motorcycle

Motorcycle motion is largely influenced by the road geometry, which alters the allowable accelerations in longitudinal and lateral directions and influences the vertical wheel loads. Recently, a method for three-dimensional road reconstruction and its incorporation into transient and quasi-steady-state (QSS) minimum lap time simulations (MLTSs) has been proposed. The main purpose of this work is to demonstrate how significantly different results from a minimum lap time optimal control problem can be obtained when using inappropriate elevation data sources in the track reconstruction problem, and how the road model reconstructed using poor input data can lead to misleading conclusions when analyzing real vehicle and driver performances. Two road models derived from high- and low-resolution digital elevation models (DEMs) are compared and their impact on the optimal maneuver of a racing motorcycle is examined. The essentials of track identification are presented, as well as vehicle positioning on the 3D road and the generalized QSS motorcycle model. Obtained 3D and 2D road models are analyzed in detail, on a case example of the Road Atlanta racetrack, and used in minimum lap time simulations, which are validated by the experimental data recorded on the Supersport motorcycle. The comparative analysis showed that great care should be taken when selecting the elevation dataset in the track reconstruction process, and that the 1 m resolution local DEMs seem to be sufficient to obtain MLTS results close to the measured ones. The example of using the 3D free-trajectory QSS minimum lap time problem to localize the track segments where real driver actions can be improved is also presented. The differences between simulation results on different road models of the same racetrack can be large and influence the interpretation of optimal maneuver.

Digital twin for motorcycle riding profile prediction

The digital twin, with its descriptive and predictive services provides promising prospects in the automotive field. Increased insights in customer behavior and vehicle states through descriptive models enable the predictive services of the digital twin to project these vehicles in the future. Currently, most of the predictive services of the digital twin focus on a singular dimension, the asset itself, without considering the influences of the environment and the driver, which hampers the reliability and accuracy of these models. The present work aims to provide a solution in the form of a holistic digital twin comprising of three descriptive models representing the motorcycle itself, its operating environment, and the motorcycle riding behavior. Based on data gathered during a large-scale measurement campaign, novel insights in the motorcycle riding behavior have enabled its representation into two mathematical formulations. Highlighting the capability of the digital twin to integrate data from heterogeneous sources, the environmental model is generated using geospatial data from a map provider, followed by a novel formulation of a safety driving line. Using a kinematic motorcycle model, the speed and banking angle over the defined route are predicted with high correlation to real-world motorcycle riding behavior. The insights generated by the developed digital twin can be used to enable data-driven development or as an input to provide individualized predictive services during the usage phase.

Power Quality and Break-Even Points in the Use of Electric Motorcycles in the Case of the Thailand Residential Building

The use of electric motorcycles (EMCs) is rapidly increasing because EMCs are comparable in price to internal combustion engine motorcycles (ICE motorcycles), can be charged at home, and do not cause pollution. However, using EMCs in residential electrical systems is still a new issue in Thailand, as the Thai power grid was not originally designed to support electric vehicle charging. Therefore, the effect that may occur on the electrical system of a house should be studied. In this study, the power quality when charging an EMC in a residential electrical system is investigated by considering the circuits of various electrical devices according to their actual consumption behavior. Three electric motorcycles with battery capacities of 20, 30, and 40 Ah were used to investigate the effects of charging these motorcycles through the electrical system of a house. The experiment was conducted in a laboratory that replicated the electrical system of a house, and the conditions and patterns of power consumption were identical in all three cases. The test results were considered in terms of power quality, voltage harmonics, and current power system harmonics to analyze the effects on the electrical system in each circuit and to compare the charging differences of each motorcycle model. Next, it was determined that using an EMC is more cost-effective than using an ICE motorcycle. ICE motorcycles will eventually be completely replaced by EMCs, and our research will enable informed decision-making for electric motorcycle riders, researchers, and automotive corporations.

Prediction of pedestrian injuries in motorcycle-pedestrian crashes using THUMS FE-HBM

This study focuses on the high fatality rates associated with motorcycles as a mode of transport in India, surpassing trucks and cars. Over the last decade, motorcycle-related fatalities have seen a staggering increase of 232%. The Finite Element-Human Body Models (FE-HBM) have been validated for occupants and pedestrians in car crashes. However, the performance against motorcycle impact is lacking in the literature. The primary objective of this research is to evaluate the THUMS model for injury prediction in motorcycle-pedestrian impact scenarios using a finite element motorcycle model of a widely used two wheeler in India. The motorcycle model is initially validated against a rigid wall, after which it is utilised to predict injuries in real-life motorcycle-pedestrian crash scenarios. Through multi-body simulations, crucial pre-crash parameters such as pedestrian orientation, offset and speed are estimated for five actual motorcycle-pedestrian crashes. Subsequently, finite element simulations are conducted to validate the model’s accuracy in predicting pedestrian injuries. The study closely predicts the occurrence and location of fractures in long bones using strain-based criteria in four out of five cases.

Mathematical modelling of gear upshift and downshift schedule for two-wheeler amt transmission

Gear shifting strategy is the key for the successful working of an automated manual transmission (AMT) as it affects the driving experience, fuel economy and dynamic performance of the vehicle. Depending upon the driver’s requirement, AMT can be designed for maximum acceleration performance and fuel efficiency. This project involves generation of gear shift schedule for both the maximum acceleration and fuel economy performance. To generate the gear shift schedule, a mathematical model is developed in MATLAB environment which takes input parameters as: vehicle speed, acceleration and throttle position. For generation of gear upshift schedule for maximum acceleration and fuel economy equation relating acceleration with tractive forces and vehicle’s fuel consumption equation at different throttle position is used respectively. Fuel consumption equation relates to brake specific fuel consumption (BSFC) along with vehicle structure. In order to obtain BSFC data, a GT-SUITE model of motorcycle is developed which incorporates data like gear ratio, power, torque and motorcycle weight. Finally, a buffer zone is applied to generated upshift schedule for both maximum acceleration and fuel economy case to get the downshift schedule. The generated gear shift schedule can be utilized for the development of the retrofit AMT kit on manual transmission motorcycle.

Comparative Life Cycle Assessment (LCA) on battery electric and combustion engine motorcycles in Taiwan

Electric motorcycles are increasingly replacing combustion engine motorcycles, especially in Asia where personal motorcycles represent a significant proportion of the traffic share. Yet, the life cycle environmental performances of electric and combustion driven motorcycles have not yet been established with field data from this region. To enable the clarification of environmental impact from this modal shift, this study conducts a comparative Life Cycle Assessment on the most popular electric and combustion engine motorcycle models in Taiwan in SimaPro using selected impact categories from the ReCiPe impact methodology. This research reveals a burden shifting between impact categories and life-cycle stages. Electric motorcycle achieves lower impacts than combustion engine motorcycle in global warming and fossil resource scarcity, while combustion engine motorcycle outperforms electric motorcycle in freshwater eutrophication and mineral resource scarcity. Electric motorcycles obtained partially better results from the operation stage at a generally higher production impact compared to combustion driven motorcycles. To mitigate the higher impacts in electric motorcycles, increasing the recycling content in raw materials and establishing suitable reuse, repair and recycling system are suggested. A sensitivity analysis revealed significant fluctuations in conventional motorcycles and robust results for the electric motorcycle.

Patterns of Maxillofacial Injures Caused by Motorcycle Accidents.

Introduction Motorcycles are used as a common means of transportation, and motorcycle accidents are responsible for a major portion of trauma injuries. Objectives The purpose of this study was to analyze the patterns of facial injuries in motorcyclists, to evaluate the types of injuries, and to investigate if the accident-related factors had any impact on the characteristics of the injuries. Methods This retrospective observational study included 74 patients with maxillofacial injuries following motorcycle-related accidents. Investigated data were divided into four main categories: sociodemographic, accident-related, injury-related, and treatment-related. Results All the patients were males with a mean age (±SD) of 25.03 (±9.986) years. Most accidents ( n = 44, 59.4%) occurred in the evening. Most of the patients ( n = 40, 54%) were traveling on motorcycle models that had maximum speed of over 120 km/h. Furthermore, 15 patients (18.9%) were under the influence of alcohol during the crashes and only one patient was wearing a helmet. Fractures of the maxillofacial bones were observed in 50 (67.5%) crash victims; 24 of them (48%) had middle third fractures, 11 (22%) had mandibular fractures, and 15 patients (30%) presented with a combination of lower, middle, and upper third fractures. Conclusion Almost all patients were not wearing helmets at the moment of the crash. The most common fractured site was the maxilla. The majority of the patients received surgical treatment. Increased enforcement of safety measures for riders and raising awareness about the dangers of motorcycle crashes are required measures to improve traffic safety and, ultimately, population health.

Identification of lumped stiffness parameters for a motorcycle model in investigating weave and wobble

In motorcycle dynamics, great importance is attributed to the study of the weave and wobble vibration modes and, in particular, to the effects of the flexibility of structural components on their stability. Therefore, appropriate motorcycle models for studying weave and wobble should include flexible elements for describing the flexural behavior of components such as the main frame, front assembly, and rear swingarm. Different approaches are possible for modeling flexibilities: the most common among them are the lumped stiffness and the flexible multibody approaches. While the latter certainly provides higher accuracy, the former has advantages in terms of computational load, but, above all, it makes it easier to understand in the design phase how technical parameters, such as torsional and bending stiffness of a given structural component, can influence the stability of weave and wobble. The accuracy of lumped stiffness models strongly depends on parameter identification. In this study, a general method is proposed to determine appropriate lumped stiffness parameters for any given motorcycle component. The proposed method is tested and validated by comparing the weave and wobble modal behavior with the results of flexible multibody analysis. The lumped stiffness model is then adopted to carry out a sensitivity analysis aimed at identifying the effects on the weave and wobble stability of the torsional and bending stiffness of specific structural components of the motorcycle to optimize their design.

Motorcycle steering torque estimation using a simplified front assembly model: experimental validation and manoeuvrability implications

Steering torque constitutes the primary motorcycle control input for the lateral dynamics; consequently, estimating it is important. Conventionally, this is done with complete motorcycle models, requiring significant identification effort. The simplified models in the literature only describe the steering torque under specific cases. This work defined a steering assembly model with few parameters to estimate the steering torque analytically for stationary and transient manoeuvres. The model equations followed from existing motorcycle models through simplifying hypotheses; transfer functions describing the roll response and the Lane Change Roll Index (LCRI) were obtained from these equations. Measured steering torque signals from different datasets, including diverse motorcycle classes, were used as the reference for validation. A good agreement resulted between the estimated and measured torques, in the time and speed-acceleration domains and in terms of LCRI. When using the roll as the motorcycle response, manoeuvrability was highest at lower frequencies. The scooter was the most manoeuvrable; the sports and touring motorcycles were the least manoeuvrable at low and high frequencies, respectively. Concerning design parameters, the front-wheel spin inertia and front twist stiffness influenced manoeuvrability the most. The model allows recreating the steering torque signal for new and pre-existing datasets using commonly measured signals; the signal can describe the riding style and the effort required. Few parameters are required, facilitating its use and reducing the computational burden, allowing its use for steering assistance systems.

Similarities in steering control between cars and motorcycles: application to a low-complexity riding simulator

Motorcycle simulators are employed for rider training, studying human–machine interaction, and developing assistance systems. However, existing simulators are either too simple and, therefore, unsuitable or significantly complex, with higher hardware costs and familiarisation times. This study aimed to use a tuned single-track car model as the basis of a motorcycle simulator, leading to considerable software simplification while preserving its fidelity. In particular, the approach defined a conversion between motorcycle steering torque and car steering angle. It modified the parameters of the latter to reproduce the response of various motorcycle models in quasi-static and transient conditions for different speeds and radii of curvature. A robust manoeuvrability index was chosen. For the car, it was possible to calculate it from its parameters analytically. Next, the car yaw inertia was tuned to obtain a motorcycle-like steering response. Finally, the calibrated car model was implemented into a low-complexity motorcycle simulator for objective validation. It was verified that an understeering single-track model with high yaw inertia has amplitude and phase responses analogous to a motorcycle. The experimental results of the simulator test confirmed these findings for a diverse set of manoeuvres, validating the method. This straightforward approach allows the development of low-complexity simulators with good steering fidelity, using an objective procedure to reproduce the behaviour of a chosen motorcycle class. In addition, the low computational cost of the model makes it a potential candidate for use in assistance systems.

Optimal brake force distribution in motorcycle for straight-line braking

Commercial motorcycles and scooters incorporate independent mechanisms for brake actuation. But due to the significant contribution of dynamic load transfer in the event of braking, there is a need to distribute brake force and apply this force combined instead of independent actuation. This paper presents an analysis of the available braking options and their effect on the stability of the motorcycle. A simple motorcycle model was developed in Simulink for analyzing the basic phenomenon that occurs during braking and considering the testing requirements as per the standard for straight-line braking. The braking maneuver is analyzed along with its effect on sprung and unsprung mass over the range of possible deceleration rates for independent braking (only front or only rear) and combined braking. Finally, the strategy for optimal distribution of braking force is applied and its effect on the suspension system is analyzed. It is found that with the application of the proposed brake strategy higher braking force and deceleration can be achieved along with reduced suspension travel compared to the independent braking strategy.

Development of Computational Model of Motorcycle and Rider During Collision

The goal of this project is to develop the computational model of motorcycle and rider for deformable body. Also, to identify the response of rider and motorcycle on collision. Computationalmodel is the one method that can replace the actual experiment on crash test. From the simulation can save cost by actual impact crash test. This project begins with design the model of actual motorcycle. Because the model of the project using Honda Wave 100R is to complex and the computer not powerful enough to generate mesh the simplified model is use for the project. Then, the material of this project using ANSI 304 stainless steel. The simulation of the experiment run by the ANSYS software to calculatemathematical model result after impact. Finally, the result of deformation was recorded to compare the result of deformation on actual crash test. The Comparison result of deformation actual and simulation are quietly similar

Balancing control of a motorcycle

Abstract This article deals with balancing an autonomous motorcycle model along a straight line and curve lines. The dynamic model of the motorcycle balancing is described with an inverted physical pendulum loaded with torque. The torque is provided by the inertia of a rotor driven by a direct current motor. The lean angle of the motorcycle is measured by a smart sensor, which is the feedback signal for the linear quadratic regulator control system. The main purpose of this study is to compensate the error of the smart sensor. Controlling the necessary lean angle of the motorcycle during cornering is also addressed.

Numerical simulation on fluid flow and temperature prediction of motorcycles based on CFD

The temperature distributions of solid parts in motorcycle is of significance to give an quantitative cooling performance evaluation for assuring the feasible running of motorcycles. Therefore, the present work mainly tend to systematically investigate the flow velocity distributions and temperature distributions of motorcycle by constructing a fluid-solid coupling analysis model via CFD using commercial software STAR-CCM+. Based on computational fluid dynamics method (CFD), fluid-solid coupling analysis model of motorcycle is realized by integration of porous media model, heat exchanger model and fluid-solid co-simulation module and numerical investigations on fluid flow and temperature distribution characteristics at maximum running speed 120 km/h is conducted. The thermal management experiment test considering three pressure measuring points, fifty-eight temperature measuring points and two flowrate measuring points is investigated to know its cooling performance of motorcycle experimentally and provide experimental data for validation of simulation model. Results show that CFD results are in good agreement with experimental results and the maximum relative error is less than 10%. Thermal management test results show that left and right cylinder temperature, oil temperature are 183 °C, 190 °C, 120 °C, respectively. Air temperature of radiator at inlet side are from 29 °C to 35 °C, Air temperature of radiator at outlet side are from 60 °C to 90 °C, water temperature of radiator inlet and radiator outlet are 96 °C and 89 °C, respectively. The air temperature around left thigh and right thigh are 31 °C and 34 °C, respectively. CFD results show that there is no flow dead-zone and high temperature area in engine main components and muffler front cover. The temperature around motorcycle covering and both two thigh is not high due to the radiation of high-temperature components and the outlet temperature of exhaust muffler is also not high, which will not cause enough heat feelings to the riders for being uncomfortable. From the temperature field analysis results, there is no obvious poor temperature distributions for thermal comfort of this motorcycle. The results of this work can provide simulation data support and theoretical reference for the design and development of motorcycle and its crucial components. Through engineering applications of fluid-solid coupling model in a two-cylinder engine and electric generator, it verifies the universality of fluid-solid coupling model and it can be an effective way for the temperature predictions of industrial products.

Research on the Decision Model of Product Design Based on a Deep Residual Network

An artificial intelligence (AI) design decision model is constructed to improve the efficiency of design decision evaluation and avoid the influence of the decision preference on product design and development. Using the concept of AI, the proposed model is based on a data set of product modeling design schemes, and the data set is marked with product modeling semantics. The deep learning residual network (ResNet) algorithm is used to train the data set to improve the accuracy of design decisions, transform the general design decision problem into the semantic recognition problem of design scheme images, and eliminate the design decision preference to the greatest extent. The validity and the feasibility of the proposed AI design decision-making method based on the ResNet algorithm are verified via an example of motorcycle modeling design decision-making.

Rancang Bangun Ulang Motor Listrik Berbasis Android Dengan Sistem Motor Brushless Direct Current (BLDC) 3 Phase Kapasitas 1000 Watt

Electric vehicles use an electric motor as a driving force where it functions as a converter of electrical energy stored in the battery into mechanical energy to turn the wheels of the vehicle. Electric motors can reduce fuel consumption and air pollution produced by motorized vehicles, so electric vehicles are one of the transportation modes they can use. In this research, the design of a BrushLess Direct Current (BLDC) motor as a motorcycle propulsion was carried out. The BLDC motor has the main components, namely the stator and rotor. This electric motor designed uses a BLDC type E-BIKE with specifications for 1000 Watt power and an input voltage frequency of 60Hz, and a rotating speed of 500Rpm with a 3.75V-25Ah BMS battery in 16 series to 60V-25Ah. This E-BIKE type BLDC electric motorcycle model can be adapted to the shape of a motorcycle drum with a wheel diameter of 17 inches.

Motorcycle antilock braking systems and fatal crash rates: updated results

Objective Antilock braking systems (ABS) prevent wheels from locking during hard braking and have been shown to reduce motorcyclists’ crash risk. ABS has proliferated in the United States fleet, and the objective of the current study was to update the effectiveness estimate for ABS with additional years of data and a broader variety of motorcycle types. Methods Motorcycle drivers involved in fatal crashes per 10,000 registered vehicle years during 2003–19 were examined for 65 motorcycle models offering ABS as an optional feature. Fatal crash rates for motorcycles with ABS were compared with rates for the same models without it. Results ABS was associated with a statistically significant 22% reduction in motorcycle driver fatal crash involvements per 10,000 registered vehicle years. Conclusion This finding adds to the growing literature demonstrating the safety benefits of motorcycle ABS.

Low‐Speed Control Experiment of Motorcycles Using SPACAR Model

The main stream of development of autonomous driving technology (ADT) is for four‐wheel motor vehicles. ADT for motorcycles has received scant attention. The motorcycle stability tends to diminish when being driven at extremely low speed. This study addresses how a motorcycle should be stabilized under low‐speed driving. To obtain a linearized motorcycle model without skidding, we introduce a model based on SPACAR, a finite element method computation program. Moreover, velocity‐dependent gain‐scheduling linear quadratic regulator (LQR) is applied. The experimental results demonstrate stabilized driving responses at 1.5 km/h, which is slower than a person's typical walking speed. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Novel high-fidelity tyre model for motorcycles to be characterised by quasi-static manoeuvres – rationale and numerical validation

Although diverse tyre model formulations exist in the literature, they are suited for characterisation using a dedicated test bench, preventing parameters' estimation in driving conditions. This study defined a novel motorcycle tyre model, characterisable through driving manoeuvres using simple instrumentation consisting in an inertial measurement unit, steering position sensor and wheel speed sensors. Acquired signals were used to estimate instantaneous tyre forces, moments, slip angle and other properties, which were employed to calculate tyre model's parameters. Tyre model development and validation were performed in a simulation environment: we used a Magic Formula tyre-equipped motorcycle model to perform a set of manoeuvres, which were employed to characterise the proposed tyre model. Lastly, a set of quasi-static manoeuvres was conducted using the same motorcycle model equipped with the two tyre models, and results were compared. Comparison results showed a close reproduction of real tyre forces, moments and slips by the proposed tyre model for quasi-static manoeuvres, accurately reproducing motorcycle dynamics. Therefore, steering torque was correctly predicted for different lateral acceleration values. These results show that the proposed tyre model can be characterised, for both longitudinal and lateral dynamics, using this limited set of manoeuvres and simple instrumentation; the correctly predicted steering torque could allow the use of this tyre model for handling description.

Development of Computational Model of Motorcycle and Rider during Collision

The goal of this project is to develop the computational model of motorcycle and rider for deformable body. Also, to identify the response of rider and motorcycle on collision. Computational model is the one method that can replace the actual experiment on crash test. From the simulation can save cost by actual impact crash test. This project begins with design the model of actual motorcycle. Because the model of the project using Honda Wave 100R is to complex and the computer not powerful enough to generate mesh the simplified model is use for the project. Then, the material of this project using ANSI 304 stainless steel. The simulation of the experiment run by the ANSYS software to calculate mathematical model result after impact. Finally, the result of deformation was recorded to compare the result of deformation on actual crash test. The Comparison result of deformation actual and simulation are quietly similar