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"Motorcycles Performance."
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\"Learn about the motorcycle's beginning, the chopper phenomenon, and motorcycle racing\"--Provided by publisher.
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Comparative Analysis of YOLOv8 and YOLOv10 in Vehicle Detection: Performance Metrics and Model Efficacy
Accurate vehicle detection is crucial for the advancement of intelligent transportation systems, including autonomous driving and traffic monitoring. This paper presents a comparative analysis of two advanced deep learning models—YOLOv8 and YOLOv10—focusing on their efficacy in vehicle detection across multiple classes such as bicycles, buses, cars, motorcycles, and trucks. Using a range of performance metrics, including precision, recall, F1 score, and detailed confusion matrices, we evaluate the performance characteristics of each model.The findings reveal that YOLOv10 generally outperformed YOLOv8, particularly in detecting smaller and more complex vehicles like bicycles and trucks, which can be attributed to its architectural enhancements. Conversely, YOLOv8 showed a slight advantage in car detection, underscoring subtle differences in feature processing between the models. The performance for detecting buses and motorcycles was comparable, indicating robust features in both YOLO versions. This research contributes to the field by delineating the strengths and limitations of these models and providing insights into their practical applications in real-world scenarios. It enhances understanding of how different YOLO architectures can be optimized for specific vehicle detection tasks, thus supporting the development of more efficient and precise detection systems.
Journal Article
Research on simulation of permanent magnet synchronous motor in full speed range
This paper studies the speed regulation simulation of permanent magnet synchronous motor. First, this paper analyzes the mathematical model of permanent magnet synchronous motor, and studies the control strategy of Id = 0, maximum torque-current ratio and weak magnetic leading Angle under synchronous rotation coordinate system. Secondly, the control strategy model is established on MATLAB/SIMULINK platform, including coordinate transformation, space vector pulse width modulation (SVPWM), proportional integration regulator, three-phase inverter, MTPA, weak magnetic core control algorithm module. Meanwhile, an APP for real-time monitoring of motor simulation model operation, control and parameter adjustment is designed by using APP Designer toolbox. Finally, the start and stop, speed increase and decrease, load surge torque and motor high-speed operation of the electric motorcycle PMSM are simulated in the actual operation. The experimental results show that the system has strong response ability and anti-interference ability under the control of current and speed PI regulator. In the motor start-stop state, the MTPA control strategy can distribute large electromagnetic torque during start-up, effectively improve the efficiency of the inverter and save costs. Compared with MTPA and Id = 0 control strategies, weak magnetic control has excellent speed increase effect, up to 6000r/min, and has strong anti-interference ability. Through the control method of the leading Angle, the dynamic switching between MTPA and weak magnetic control strategy is realized, and the running speed range of PMSM is effectively extended.
Journal Article
The Protective Performance of Modern Motorcycle Helmets Under Oblique Impacts
Motorcyclists are at high risk of head injuries, including skull fractures, focal brain injuries, intracranial bleeding and diffuse brain injuries. New helmet technologies have been developed to mitigate head injuries in motorcycle collisions, but there is limited information on their performance under commonly occurring oblique impacts. We used an oblique impact method to assess the performance of seven modern motorcycle helmets at five impact locations. Four helmets were fitted with rotational management technologies: a low friction layer (MIPS), three-layer liner system (Flex) and dampers-connected liner system (ODS). Helmets were dropped onto a 45° anvil at 8 m/s at five locations. We determined peak translational and rotational accelerations (PTA and PRA), peak rotational velocity (PRV) and brain injury criteria (BrIC). In addition, we used a human head finite element model to predict strain distribution across the brain and in corpus callosum and sulci. We found that the impact location affected the injury metrics and brain strain, but this effect was not consistent. The rear impact produced lowest PTAs but highest PRAs. This impact produced highest strain in corpus callosum. The front impact produced the highest PRV and BrIC. The side impact produced the lowest PRV, BrIC and strain across the brain, sulci and corpus callosum. Among helmet technologies, MIPS reduced all injury metrics and brain strain compared with conventional helmets. Flex however was effective in reducing PRA only and ODS was not effective in reducing any injury metrics in comparison with conventional helmets. This study shows the importance of using different impact locations and injury metrics when assessing head protection effects of helmets. It also provides new data on the performance of modern motorcycle helmets. These results can help with improving helmet design and standard and rating test methods.
Journal Article
The Comparison of Electric Motor Performance in Powering Electric Motorcycle
The increase use of vehicles with combustion engine has caused intensive exploration of fossil fuels and severe pollutions. The replacement of this engine with electric motor is expected to solve both problems. For optimal selection of the motor, assessment of its performance is necessary. This may be carried out by comparing the performance of the motors used for powering electric motorcycle. This paper presents the performance comparison of 2 motors powering a modified motorcycle. The engine of the motorcycle was successively replaced with BLDC motor and DC motor and their performances were measured. The motorcycle was loaded with 1 and 2 passengers with the total weight of 59 and 109 Kg, respectively. The motorcycle speed (km/h) was adjusted up to 30 km/h. The results of the test indicate that DC motor requires power of 557.74 Watt at the speed of 317.04 rpm and generates torque of 16.81 Nm with energy consumption of 41.55 km/kWh. For the BLDC motor, it requires power of 526.62 Watt at the speed of 316.78 rpm and generates torque of 15.88 Nm with energy consumption of 50.59 km/kWh. For the same distance, DC Motor enables generates higher torque than BLDC motor. However, BLDC motor may present lower energy consumption per kWh than DC motor.
Journal Article
Predicting the sport level in elite male motorcycle speedway riders based on physical profile and experience
The main objective of this research was to analyze the physical profile and experience of elite male motorcycle speedway riders, in order to develop a mathematical model to predict their level of sport performance. One hundred and eleven male professional motorcycle speedway riders in the top Polish motorcycle speedway league participated in this study (age: 25.04 ± 6.03 years, height: 172.28 ± 4.76 cm, weight: 65.60 ± 4.66 kg). The riders were divided by the k-means clustering method into three groups of sport level: high (n 1 = 31), medium (n 2 = 30), low (n 3 = 50). To define sport level, several parameters were normalized and aggregated into a new conceptual metric of sport level called ‘Indicator of Sport Level’ (ISL). Body composition assessment, Wingate Anaerobic Test on a cycloergometer, and analysis of acute cardiorespiratory and biochemical responses were performed. One-way ANOVA tests were performed for independent samples, and Pearson’s r linear correlation was calculated between clusters of riders. Multiple linear regression (MLR) was performed to predict the ISL. The elite male motorcycle speedway athletes were characterized by average age (25.10 ± 5.80 years) and years of experience (9.16 ± 5.62 years), which made them different from other clusters (p < 0.05). Also, they were 1.99% taller (173.02 ± 4.91 cm) than low sport level riders (p = 0.003). The strongest predictive variable of sport level in the regression model (R 2 = 0.28) was body height (p = 0.043) and sport experience (p < 0.001). The results of this study present the optimal range of physical attributes, body height, sports experience, age, and body surface area of the best motorcycle speedway riders and indicate that body height and experience are the most predictive parameters in the model to estimate the sport level of riders.
Journal Article
Motorcycle Engine Performance Comparison Between Laser Ignition System and Conventional Ignition System Through Simulation
In many countries, motorcycles have become a primary and popular mode of transportation, driven by increasing demand due to their convenience. However, as fossil fuel sources deplete, there's a pressing need to enhance engine performance, efficiency, fuel economy, and reduce emissions. Improving ignition systems is crucial in achieving these goals. This study compares the performance of the Honda Future FI 125cc engine between a laser ignition system (LIS) and a conventional ignition system (CIS) using simulation. CATIA software was utilized to design the engine's intake manifold, ANSYS Fluent software for simulating and determining the optimal swirl and tumble ratio, and Matlab/Simulink for modeling and simulating engine performance with both LIS and CIS. Detailed discussions and comparisons were made on parameters such as cylinder air mass, ignition energy, engine power and torque, specific fuel consumption (SFC), and mass fraction burned (MFB) between LIS and CIS. Overall, LIS demonstrated superior engine performance compared to CIS. This finding is significant for evaluating the advantages of LIS in motorcycles, especially in the Honda Future FI 125cc engine.
Journal Article
Enhancing Engine Performance and Environmental Sustainability Through Innovative Exhaust Design
This research investigates and demonstrates the potential benefits of material innovation and exhaust design in enhancing vehicle performance and being more environmentally friendly. The pursuit of optimal vehicle efficiency has driven the exploration of alternative materials. Galvanized materials have emerged as a significant factor, highlighting the potential for increased agility and fuel efficiency. With this material, the new exhaust design results in an extraordinary weight reduction of 3.2 kg compared to the original exhaust at 6.450 kg. Additionally, the new exhaust design has yielded significant improvements in performance metrics. The peak power output of the original exhaust is 12.4 HP at 7336 RPM, increasing to 13.3 HP at 7695 RPM, showing a power increase of 7%. The maximum torque of the original exhaust is 12.99 N.m at 6186 RPM, increasing to 13.81 N.m at 5501 RPM, showing a torque increase of 6%. The power-to-weight ratio calculation shows a substantial shift in efficiency, with the original exhaust having a value of 0.09 HP/Kg and the new, more efficient exhaust having 0.10 HP/Kg, an efficiency increase of 11%. Furthermore, the noise produced by the original exhaust at a maximum of 8000 RPM is 90.2 dB, while the new exhaust at a maximum of 8000 RPM is 88 dB. From these results, it can be concluded that the new exhaust design enhances motorcycle efficiency and is more environmentally friendly.
Journal Article
Accelerating Electric Motorcycle Adoption: Comparison Between Users and Non-Users Perspectives In Jakarta, Indonesia
The adoption rate of electric motorcycles in Indonesia, including large cities like Jakarta, remains relatively low. This study aims to evaluate both barriers and drivers of electric motorcycle (EM) adoption from the perspectives of users and non-users. The research utilized Importance-Performance Analysis (IPA) to identify areas for improvement, and determine the most important factors to prioritize strategy development. This research has found that the 'driver attributes' for EM adoption have a positive perceived performance according to the IPA mapping. However, the attributes that act as barriers to EM adoption have low performance and need to be prioritized for improvement. A comparison study was conducted between EM users and non-users, revealing several differences in importance and performance assessments. Furthermore, a technical preference analysis was conducted among the community to provide deeper insights from the public's perspective regarding EM. The research implies that a comprehensive strategy is needed to foster the adoption of electric vehicles in urban areas like Jakarta. This strategy aims to overcome high prices, range anxiety, and lack of infrastructure to increase adoption rates and support a sustainable urban transport system.
Journal Article
The Effects of Environmental Policy and the Perception of Electric Motorcycles on the Acceptance of Electric Motorcycles: An Empirical Study in Macau
Air pollution is a serious environmental issue across the world and has drawn attention from researchers with different backgrounds. The carbon exhaust from gasoline vehicles is one cause of air pollution. One solution for reducing carbon emissions is to provide green vehicles, such as electric motorcycles, for drivers and passengers, which can help the sustainable development of the environment in an ecological way. This research discusses the market response to electric motorcycles in Macau by focusing on the effects of environmental policy. An environmental technology acceptance model was developed, based on which 325 valid questionnaires were collected. The research demonstrates the impact on motorcyclists’ acceptance of electric motorcycles by considering their perceptions of environmental policy, pollution reduction, the saving of energy, and driving performance; the results can lead to valuable discussions on the environment–technology–society ecosystem in further studies. The research results could help relevant government bodies to develop appropriate environmental policies to encourage motorcyclists to adopt electric motorcycles. Furthermore, the electric motorcycle industry could identify key success factors for developing or promoting electric motorcycles using the study variables.
Journal Article