Vehicles, Volume 2, Issue 3 (September 2020) – 11 articles

In order to improve the test conditions of the tire uniformity test and the effect of the speed and tire pressure on the uniformity parameters, the uniformity test of the tire under different speeds and tire pressure was carried out by a high-speed uniformity test machine, and the experimental data were analyzed and fitted by the regression analysis method. This paper introduces the definition of uniformity and the uniformity parameters of automotive tires; the working principle of a high-speed uniformity testing machine is briefly described, a mathematical model of the uniformity testing machine is established, and the signal acquisition process of the tire uniformity parameters and the calculation method of the uniformity parameters are described. The test result indicates: As the speed increases, the radial force fluctuation, lateral force fluctuation, tangential force fluctuation, and turning torque fluctuation of the tire increase, and the positive torque fluctuation first increases and then decreases; with the increase of tire pressure, the radial force fluctuation and the tangential force fluctuation of the tire increase, and the lateral force fluctuation, the turning torque fluctuation, and the returning moment fluctuation are all reduced. Compared to the low speed uniformity test, the high speed uniformity test can better reflect the uniformity of the tire, reducing the speed of the vehicle can reduce the radial runout and lateral sway of the tire; increasing the tire pressure can reduce the left and right swing of the vehicle. Full article

Often in the area of road transport solutions and intelligent transport systems, two or more alternative solutions or methods compete in terms of energy gains, time efficiency, or other aspects. Measurements collected from field trials are used to make a comparative assessment but are usually limited because of resource constraints. The present paper describes how statistical inference techniques can be used in a systematic way, in order to validate the superior performance of one method over the other. We adopt such an approach to study the performance of two alternative routing methods in terms of achievable energy savings, although the same methodology can be widely applied to other use cases as well. We specifically employ and describe three different techniques to achieve the intended comparison, namely paired sample tests, statistical testing of mean value in a normal population, and two-sample tests in normal populations with unknown yet equal variances. We reach conclusions on whether claims of outperformance of one routing method over the other can be supported by our collected experimental data and to what extent. Full article

The rapidly improving autonomous vehicle (AV) technology will have a significant impact on traffic safety and efficiency. This study introduces a game-theory-based priority control algorithm for autonomous vehicles to improve intersection safety and efficiency with mixed traffic. By using vehicle-to-infrastructure (V2I) communications, this model allows an AV to exchange information with the roadside units (RSU) to support the decision making of whether an ordinary vehicle (OV) or an AV should pass the intersection first. The safety of vehicles is taken in different stages of decisions to assure collision-free intersection operations. Two different mathematical models have been developed, where model one is for an AV/AV situation and model two is when an AV meets an OV. A simulation model was developed to implement the algorithm and compare the performance of each model with the conventional traffic control at a four-legged signalized intersection and at a roundabout. Three levels of traffic volume and speed combinations were tested in the simulation. The results show significant reductions in delay for both cases; for case (I), AV/AV model, a 65% reduction compared to a roundabout and 84% compared to a four-legged signalized intersection, and for case (II), AV/OV model, the reduction is 30% and 89%, respectively. Full article

Transportation systems are central to all cities, and city planners and policy makers take special interest in assuring these systems are efficient, functional, sustainable, and, increasingly, that they have a positive impact on human health. In addition, vehicular emissions are increasingly costly to cities due to congestion and its impact on public health. This study aims to show the associations between the media and environmental variables and associated transit ridership. By tracking media influence, we illustrated how media coverage and attention to an issue over time may impact public opinion and ridership outcomes, especially at the local level where the issues are most salient. The relationship between air quality and transit ridership shown can be generally explained through a combination of infrastructure and human behavior. The media key terms examined in this analysis show that ridership is associated with favorable weather conditions and air quality, suggesting that ridership volume may be influenced by an overall sense of comfort and safety. Based on this analysis, we illustrated the role of media attention in both increased and decreased transit ridership and how such effects are compounded by air quality conditions (e.g., green, yellow, orange, and red air quality days). Full article

Testing of vehicle design properties by car manufacturers is primarily performed on-road and is resource-intensive, involving costly physical prototypes and large time durations between evaluations of alternative designs. In this paper, the applicability of driving simulators for the virtual assessment of ride, steering and handling qualities was studied by manipulating vehicle air suspension ride height (RH) (ground clearance) and simulator motion platform (MP) workspace size. The evaluation was carried out on a high-friction normal road, routinely used for testing vehicle prototypes, modelled in a driving simulator, and using professional drivers. The results showed the differences between the RHs were subjectively distinguishable by the drivers in many of the vehicle attributes. Drivers found standard and low RHs more appropriate for the vehicle in terms of the steering and handling qualities, where their performance was deteriorated, such that the steering control effort was the highest in low RH. This indicated inconsistency between subjective preferences and objective performance and the need for alternative performance metrics to be defined for expert drivers. Moreover, an improvement in drivers’ performance was observed, with a reduction of steering control effort, in larger MP configurations. Full article

Unmanned Aerial Vehicles have generated considerable interest in different research fields. The motion control problem is among the most important issues to be solved since system dynamic stability depends on the robustness of the main controller against endogenous and exogenous disturbances. In spite of different controllers have been introduced in the literature for motion control of fixed and rotary wing vehicles, there are some challenges for improving controller features such as simplicity, robustness, efficiency, adaptability, and stability. This paper outlines a novel approach to deal with the induced effects of external disturbances affecting the flight of a quadrotor unmanned aerial vehicle. The aim of our study is to further extend the current knowledge of quadrotor motion control by using both adaptive and robust control strategies. A new adaptive neural trajectory tracking control strategy based on B-spline artificial neural networks and on-line disturbance estimation for a quadrotor is proposed. A linear extended state observer is used for estimating time-varying disturbances affecting the controlled nonlinear system dynamics. B-spline artificial neural networks are properly synthesized for on-line calculating control gains of an adaptive Proportional Integral Derivative (PID) scheme. Simulation results highlight the implementation of such a controller is able to reject disturbances meanwhile perform proper motion control by exploiting the robustness, disturbance rejection, adaptability, and self-learning capabilities. Full article

The number of connected cars and the massive consumption of digital content on the Internet have increased daily. However, the high mobility of the vehicles, coming from patterns’ variation over time, makes efficient large-scale content distribution quite challenging. In light of this, the emerging Vehicular Named Data Network (VNDN) architecture provides support for content-centric network communications and caching capabilities, which allows reliable and larger-scale content delivery over Vehicular Ad-Hoc Networks (VANETs). This notwithstanding, the high number of interest packets in VNDN tends to introduce broadcast storm occurrences during the cache discovery process. Thus, network performance degradation comes up for the influence of both increased packet loss rates and delays on content recovery during communication between vehicles. This work proposes a new cache discOVEry pRoTocol (OVERT VNDN), which combines the computational geometry and degree centrality concepts to tackle the VNDN performance degradation challenges and issues. The main idea behind OVERT VNDN is to choose the most appropriate relay vehicles to engage interest packets’ delivery within the VNDN, seeking to achieve higher network performance by optimizing broadcast storm incidence. The obtained results suggest that OVERT VNDN outperforms its competitor in the following key performance indicators: (i) improving the cache discovery process by 120.47%; (ii) enhancing the content delivery rate by 43%; and (iii) reducing the number of interest packets by 80.99%. Full article

In recent decades, thin-walled composite components have been widely used in the automotive industry due to their high specific energy absorption. A large number of experimental and numerical studies have been conducted to characterize the energy absorption mechanism and failure criteria for different composite tubes. Their results indicate that the energy absorption characteristics depend highly on the failure modes that occur during the impact. And failure mechanism is dependent on fiber material, matrix material, fiber angle, the layout of the fibers, as well as the geometry of structure and load condition. In this paper, first, the finite element (FE) model of the CFRP tube was developed using the Tsai-Wu failure criterion to model the crush characteristics. The FE results were validated using the published experimental. Then, a series of FE simulations were conducted considering different fiber directions and the number of layers to generate enough data for constructing the GMDH-type neural network. The polynomial expression of the three outputs (energy absorption, maximum force, and critical buckling force) was extracted using the GMDH algorithm and was used to perform the Pareto-based multi-objective optimizations. Finally, the failure mechanism of the optimum design point was simulated in LS-DYNA. The main contribution of this study was to successfully model the CFRP tube and damage mechanism using appropriate material constitutive model’s parameters and present the multi-objective method to find the optimum crashworthy design of the CFRP tube. Full article

For the last two decades, a novel mechanical system has received increasing attention—the inerter. An inerter is a system that can store mechanical energy for a rather short amount of time and behaves analogously to a capacitor in electrical engineering. Until today, only a few inerter applications have been reported. In a vehicle suspension, an inerter can be used to reduce wheel vibrations. This paper demonstrates the application potential of the novel mechanical system and describes the design and dimensioning of an inerter for the reduction of these kind of wheel vibrations for two completely different vehicle concepts. The first application concerns a Formula Student race car in which the main objective represents the maximization of the mechanical grip to improve lap times. For the inerter dimensioning in a racing car, lightweight design is a major issue. The second application is an agricultural tractor in which the focus is on the reduction of the ground pressure to protect the environment as well as on a very robust and compact realization of the inerter. A detailed simulation of both cases allows a qualitative and quantitative assessment of the wheel vibration reduction potential. In both applications, a considerable improvement potential could be identified which amounts, in the case of the race car, to a reduction of wheel oscillation of about 21% and for the tractor to a wheel vibration reduction potential of up to 54%. Full article

The reliability analysis of traction inverters is of great interest due to the use of new semi-conductor devices and inverter topologies in electric vehicles (EVs). Switching devices in the inverter are the most vulnerable component due to the electrical, thermal and mechanical stresses based on various driving conditions. Accurate stress analysis of power module is imperative for development of compact high-performance inverter designs with enhanced reliability. Therefore, this paper presents an inverter reliability estimation approach using an enhanced power loss model developed considering dynamic and transient influence of power semi-conductors. The temperature variation tracking has been improved by incorporating power module component parameters in an LPTN model of the inverter. A 100 kW EV grade traction inverter is used to validate the developed mathematical models towards estimating the inverter performance and subsequently, predicting the remaining useful lifetime of the inverter against two commonly used drive cycles. Full article

Emissions and pollution from the transportation sector due to the consumption of fossil fuels by conventional vehicles have been negatively affecting the global climate and public health. Electric vehicles (EVs) are a cleaner solution to reduce the emission and pollution caused by transportation. Lithium-ion (Li-ion) batteries are the main type of energy storage system used in EVs. The Li-ion battery pack must be considerably large to satisfy the requirement for the vehicle’s range, which also increases the cost of the vehicle. However, considering that most people use their vehicles for short-distance travel during daily commutes, the large pack is expensive, inefficient and unnecessary. In a previous paper, we proposed a novel EV powertrain design that incorporated the use of a zinc–air (Zn–air) battery pack as a range-extender, so that a smaller Li-ion pack could be used to save costs. The design and performance aspects of the powertrain were analyzed. In this study, the environmental and economic benefits of the proposed dual-battery powertrain are investigated. The results from the new powertrain were compared with values from a standard EV powertrain with one large Li-ion pack and a conventional internal combustion engine vehicle (ICEV) powertrain. In addition, an air pollution model is developed to determine the total amount of pollution released by the transportation sector on Highway 401 in Ontario, Canada. The model was then used to determine the effects of mass passenger EV rollout on pollution reduction. Full article