Search Results (36)

The physical roots, interpretation, controversies, and precise meaning of the Landauer principle are surveyed. The Landauer principle is a physical principle defining the lower theoretical limit of energy consumption necessary for computation. It states that an irreversible change in information stored in a computer, such as merging two computational paths, dissipates a minimum amount of heat $k_{B}Tln2$ per a bit of information to its surroundings. The Landauer principle is discussed in the context of fundamental physical limiting principles, such as the Abbe diffraction limit, the Margolus–Levitin limit, and the Bekenstein limit. Synthesis of the Landauer bound with the Abbe, Margolus–Levitin, and Bekenstein limits yields the minimal time of computation, which scales as ${\tau }_{min}~\frac{h}{k_{B}T}$. Decreasing the temperature of a thermal bath will decrease the energy consumption of a single computation, but in parallel, it will slow the computation. The Landauer principle bridges John Archibald Wheeler’s “it from bit” paradigm and thermodynamics. Experimental verifications of the Landauer principle are surveyed. The interrelation between thermodynamic and logical irreversibility is addressed. Generalization of the Landauer principle to quantum and non-equilibrium systems is addressed. The Landauer principle represents the powerful heuristic principle bridging physics, information theory, and computer engineering. Full article

This article presents a model-based approach to assess the battery performance of a two-wheeler EV drive train system for various user driving patterns using the selected urban drive cycles. The battery pack is one of the most expensive parts of an EV, and its life is heavily dependent on its usage pattern. The impact of the user’s driving behaviour on the performance parameters of the EV battery pack needs to be investigated. Thus, a two-wheeler EV drive train model was developed in MATLAB with a 5 kW motor, a 4.32 kWh battery, vehicle dynamics, and the power train control algorithms for in-depth analysis of battery performance. The validity of the developed model was tested against various state-of-the-art drive cycles for a duration of 3600 s. Numerous user driving behaviours, such as aggressive, moderate, and slow driving behaviours, were modelled with modified drive cycles, which were used to assess the two-wheeler battery pack performance. An optimum speed range, which ranges from 21 km/h to 34 km/h for different drive cycles, was identified, and these speed ranges minimised the battery energy consumption for the selected drive cycles with the modified drive cycle models. Full article

Data acquisition from a vehicle operating in real driving conditions is extremely useful for analyzing the real-time behavior of the vehicle and its components. A few studies have measured the real-time data for a four-wheeler electric vehicle. However, no attempts have been reported to measure the real-time data and find the inverter efficiency for a two-wheeler electric vehicle. The present work has accomplished successful real-time data acquisition from a two-wheeler electric vehicle. The real-time current and voltage coming in and going out from the inverter, frequency of the motor operation, power factor, distance covered, and velocity have been measured. The inverter efficiency is found to be over 95% for over 80% of the total drive time, and the power factor for the motor is over 0.8 for almost 50% of the total drive time. A few insights on driver behavior and finally the torque-speed characteristics and two quadrant operation of the motor are discussed. Full article

The primary objective of this study is to investigate the influence of personality traits such as anxiety, sensation seeking, altruism, anger, and normlessness on young powered two-wheeler riders’ risky riding behavior. The theory of planned behavior (TPB) is extended to include personality traits forming an extended TPB (ETPB). The ETPB model is used to examine how personality traits directly influence risky riding behavior and indirectly influence risky riding behavior through latent mediating factors. The secondary objective is to examine the differences in interactions between personality traits, mediating factors, and risky riding behaviors of those who have been and have not been involved in traffic accidents. The study sample included 535 high school students in Phu Yen, Vietnam. The results showed that personality traits, directly and indirectly, influence risky riding behaviors through the mediating construct. Young riders with sensation-seeking, anger, and normlessness have a higher frequency of risky riding behavior than those with anxiety and altruistic personality traits. Sensation seeking, anger, and normlessness indirectly influence risky riding behavior through risk perception and subjective norms. In addition, the results also show a clear difference in the relationship between the personality and behavior of people who have been involved in traffic accidents and those who have never been involved in accidents. Full article

In the context of nature protection, there is an effort to regulate individual car traffic in protected areas. In the framework of the research, a pilot testing of a vehicle detection and identification system in the Krkonoše National Park was carried out using two selected technologies (license plate recognition and Bluetooth token detection). The research was carried out under conditions of poorer availability of mobile signal for transmission of measured data, lack of electrical power supply, and in challenging climatic conditions in the mountains. The main objective was to verify the applicability and limits of the mentioned technologies under these difficult conditions. For this purpose, two test sites were built: a fixed and a mobile point. Testing at both points was carried out using two basic methods, namely online through continuous data collection from the detectors and on-site through a local survey during the summer of 2022. The parameters evaluated were the reliability of the vehicle identification itself and the reliability of the operation of the individual detection subsystems and the tested system as a whole. The results show that the license plate recognition system using two cameras for the checkpoint shows a high recognition reliability, but it is reduced for some types of vehicles (especially motorcycles and four-wheelers). At the same time, this technology is demanding on energy resources. Detection using a Bluetooth scanner has proven to be highly reliable up to 50 km/h. A reliable power supply is necessary to achieve high reliability, which was a problem at the mobile point. Evaluation of images from cameras with motion detection showed the limits of this technology, which increased with increasing vehicle speed. The system can be used to detect traffic in protected areas, taking into account the limits specified in this article. Full article

Outrunner brushless DC motors (BLDC) are a type of permanent magnet synchronous motor (PMSM) widely used in electric micro-mobility vehicles, such as scooters, electric bicycles, wheelchairs, and segways, among others. Those vehicles have many operational constraints because they are driven directly by the user with light protective wearing. Therefore, to improve control strategies to make the drive safer, it is essential to model the traction system over a wide range of operating conditions in a street environment. In this work, we developed an electro-mechanical model based on the Hardware-in-the-Loop (HIL) structure for a two-wheeler electric scooter, using the BLDC motor to explore its response and to test linear controllers for speed and torque management under variable operating conditions. The proposed model includes motor parameters, power electronics component characteristics, mechanical structure, and external operating conditions. Meanwhile the linear controllers will be adjusted or tuned though a heuristic approach based on Genetic Algorithms (GAs) to optimize the system’s response. The HIL scheme will be able to simulate a wide range of conditions such as user weight, slopes, wind speed changes, and combined conditions. The designed model can be used to improve the design of the controller and estimate mechanical and electrical loads. Finally, the results of the controller tests show how the proposed cascade scheme, tuned through the GA, improves the system behavior and reduces the mean square error with respect to a classical tuning approach between 20% and 60%. Full article

Studies have explored the factors influencing the safety of PTWs; however, very little has been carried out to comprehensively investigate the factors influencing fatal PTW crashes while considering the fault status of the rider in crash hotspot areas. This study employs spatio-temporal hotspot analysis and association rule mining techniques to discover hidden associations between crash risk factors that lead to fatal PTW crashes considering the fault status of the rider at statistically significant PTW crash hotspots in South Korea from 2012 to 2017. The results indicate the presence of consecutively fatal PTW crash hotspots concentrated within Korea’s densely populated capital, Seoul, and new hotspots near its periphery. According to the results, violations such as over-speeding and red-light running were critical contributory factors influencing PTW crashes at hotspots during summer and at intersections. Interestingly, while reckless riding was the main traffic violation leading to PTW rider at-fault crashes at hotspots, violations such as improper safety distance and red-light running were strongly associated with PTW rider not-at-fault crashes at hotspots. In addition, while PTW rider at-fault crashes are likely to occur during summer, PTW rider not-at-fault crashes mostly occur during spring. The findings could be used for developing targeted policies for improving PTW safety at hotspots. Full article

This paper proposes a novel torque measurement and control technique for cycling-assisted electric bikes (E-bikes) considering various external load conditions. For assisted E-bikes, the electromagnetic torque from the permanent magnet (PM) motor can be controlled to reduce the pedaling torque generated by the human rider. However, the overall cycling torque is affected by external loads, including the cyclist’s weight, wind resistance, rolling resistance, and the road slope. With knowledge of these external loads, the motor torque can be adaptively controlled for these riding conditions. In this paper, key E-bike riding parameters are analyzed to find a suitable assisted motor torque. Four different motor torque control methods are proposed to improve the E-bike’s dynamic response with minimal variation in acceleration. It is concluded that the wheel acceleration is important to determine the E-bike’s synergetic torque performance. A comprehensive E-bike simulation environment is developed with MATLAB/Simulink to evaluate these adaptive torque control methods. In this paper, an integrated E-bike sensor hardware system is built to verify the proposed adaptive torque control. Full article

Faced with increasing environmental pollution due to traffic concentration in big cities, Vietnam, as well as many countries worldwide, has encouraged its people to use environmentally-friendly vehicles. Because the transport mode is dominated by two-wheelers (i.e., motorcycles and mopeds) (2Ws), electrifying 2Ws has the potential for significant air pollution reductions as an alternative to gasoline-powered vehicles in Vietnam. Therefore, there has recently been an increasing trend of shifting from traditional gasoline two-wheeler vehicles to electric two-wheelers (E2Ws). Depending on different local contexts, some countries/regions quickly adopted the policies/incentives, and new technologies for E2W usage, while others acted more slowly. In order to advance the use of E2Ws in Vietnam, assessing E2W user preferences is essential to classify and prioritize further solutions, which would be instrumental in fulfilling user expectations. However, a few academic works pay attention to this field of the Vietnamese E2W market. In response to this research gap, this paper aims to overview the current status of E2W usage, assess the market development of E2Ws, and evaluate the battery charging business models in Vietnam. The questionnaire survey was carried out to evaluate the preferences of E2W users in the Vietnamese market, while the assessment of E2W development was conducted based on the SWOT (strengths, weaknesses, opportunities, and threats) analysis. The results demonstrated that E2W deployment is still at an exploratory stage in the transportation industry and is growing significantly in Vietnam. This study also revealed significant challenges for E2W adoption, especially the E2W battery charging/swapping system. Thus, it is recommended that incentives for E2W uptake and the battery charging infrastructure system should be improved and implemented. The evaluation of E2W perceptions in the three-city context is realized as exploratory, generating the baseline for further research when the survey can engage more respondents in other places to confirm the current research findings. The study can also assist policymakers and investors in comprehensively assessing the opportunities and challenges and provide recommendations for accelerating the growth of E2Ws in Vietnam for establishing a national e-mobility roadmap and thereby promoting sustainable transport in alignment with the COP26. Full article

The crash safety of lithium-ion traction batteries is a relevant concern for electric vehicles. Current passive safety strategies of traction batteries usually come at the cost of their volumetric or gravimetric energy density. This work analyses the influence of the variables cell selection and orientation within the traction battery on the crash safety of an electric-powered two-wheeler. These two variables do not negatively influence the traction battery’s volumetric or gravimetric energy density in the design process. Metamodels and numerical simulations are used to evaluate the crash safety of an electric-powered two-wheeler’s traction battery in a potentially dangerous crash scenario. The influence of the variable’s cell selection and orientation is evaluated through the internal short circuit risk of the integrated cells. The comparison of the metamodels shows that the cell orientation reduces the internal short circuit risk by up to 51% on average in the analysed crash scenario. The cell selection reduces it only up to 21% on average. The results show that crash safety can be increased in the design process, and a combination with the current protection strategies can increase crash safety further. Full article

The transportation industry is transitioning from conventional Internal Combustion Engine Vehicles (ICVs) to Electric Vehicles (EVs) due to the depletion of fossil fuels and the rise in non-traditional energy sources. EVs are emerging as the new leaders in the industry. Some essential requirements necessary for the widespread adoption of EVs include sufficient charging stations with numerous chargers, less to no wait time before charging, quick charging, and better range. To enable a quicker transition from ICVs to EVs, commercial organizations and governments would have to put in a mammoth effort, given the low number of installed chargers in developing nations such as India. One solution to lower the waiting time is to have multiple vehicles charging simultaneously, which might involve charging two- and four-wheelers simultaneously, even though their battery voltage ratings differ. This paper begins by providing the details of the power sources for EV charging, the charging levels and connector types, along with the specifications of some of the commercial chargers. The necessity of AC-DC converters in EV charging systems is addressed along with the power quality concerns due to the increased penetration of EVs. Next, a review of the existing research and technology of isolated DC-DC converters for simultaneous charging of EV batteries is provided. Further, several potential isolated DC-DC converter topologies for simultaneous charging are described with their design and loss estimation. A summary of the existing products and projects with simultaneous charging features is provided. Finally, insight is given into the future of simultaneous charging. Full article

The dynamic behavior of a Powered Two-Wheeler (PTW) is much more complicated than that of a car, which is due to the strong coupling between the longitudinal and lateral dynamics produced by the large roll angles. This makes the analysis of the dynamics, and therefore the design and synthesis of the controller, particularly complex and difficult. In relation to assistance in dangerous situations, several recent manuscripts have suggested devices with limitations of cornering velocity by proposing restrictive models. However, these models can lead to repulsion by the users of PTW vehicles, significantly limiting vehicle performance. In the present work, the authors developed an Advanced Rider-cornering Assistance System (ARAS) based on the skills learned by riders running across curvilinear trajectories using Artificial Intelligence (AI) and Neural Network (NN) techniques. New algorithms that allow the value of velocity to be estimated by prediction accuracy of up to 99.06% were developed using the K-Nearest Neighbor (KNN) Machine Learning (ML) technique. Full article

Traumatic Brain Injuries (TBIs) are one of the most frequent and severe outcomes of a Powered Two-Wheeler (PTW) crash. Early diagnosis and treatment can greatly reduce permanent consequences. Despite the fact that devices to track head kinematics have been developed for sports applications, they all have limitations, which hamper their use in everyday road applications. In this study, a new technical solution based on accelerometers integrated in a motorcycle helmet is presented, and the related methodology to estimate linear and rotational acceleration of the head with deep Artificial Neural Networks (dANNs) is developed. A finite element model of helmet coupled with a Hybrid III head model was used to generate data needed for the neural network training. Input data to the dANN model were time signals of (virtual) accelerometers placed on the inner surface of the helmet shell, while the output data were the components of linear and rotational head accelerations. The network was capable of estimating, with good accuracy, time patterns of the acceleration components in all impact conditions that require medical treatment. The correlation between the reference and estimated values was high for all parameters and for both linear and rotational acceleration, with coefficients of determination ($R^2$) ranging from 0.91 to 0.97. Full article

The role of powered two-wheeler (PTW) transport from the perspective of a more sustainable mobility system is undermined by the associated high injury risk due to crashes. Motorcycle-based active safety systems promise to avoid or mitigate many of these crashes suffered by PTW riders. Despite this, most systems are still only in the prototype phase and understanding which systems have the greatest chance of reducing crashes is an important step in prioritizing their development. Earlier studies have examined the applicability of these systems to individual crash configurations, e.g., rear-end vs. intersection crashes. However, there may be large regional differences in the distribution of PTW crash configurations, motorcycle types, and road systems, and hence in the priority for the development of systems. The study objective is to compare the applicability of five active safety systems for PTWs in Australia, Italy, and the US using real-world crash data from each region. The analysis found stark differences in the expected applicability of the systems across the three regions. ABS generally resulted in the most applicable system, with estimated applicability in 45–60% of all crashes. In contrast, in 20–30% of the crashes in each country, none of the safety systems analyzed were found to be applicable. This has important implications for manufacturers and researchers, but also for regulators, which may demand country-specific minimum performance requirements for PTW active safety countermeasures. Full article

Energy-environmental planning for road transportation involves a vast investigation of vehicles’ technologies and electricity production. However, in developing countries where the public transportation sector is growing quickly, energy-environmental planning is urgently needed. This paper evaluates the future electricity demand, as well as fuel consumption and CO₂ emissions reduction, due to the operation of an expected increasing number of electric vehicles (EVs) in Pakistan. The planning of EVs up to 2040 is performed with the ePop simulator that calculates the future EVs’ electricity demand, while EnergyPLAN^® assesses the expected new power capacities. Two scenarios are investigated by penetrating 30% and 90% of 2/3 electric wheelers and cars by 2030 and 2040 compared to 2020, respectively. To fulfill the expected energy demand, PV in the daytime and the national electric grid at nighttime are here considered. Finally, a 9 GW of PV capacity is needed to satisfy the EVs’ electricity demand of 14.7 TWh/year, and a 0.7 GW power plants capacity is needed to fulfill 4.7 TWh/year by 2040. Consequently, EVs’ charging scenarios at daytime and nighttime are assessed. Results indicated a total reduction of 10.4 Mtonnes of CO₂ emissions and 9.1 Mtoe of fuel consumption by 2040 in the transportation sector. Full article