Automotive Science and Engineering

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This study uses real driving cycles of a city bus and a standard driving cycle “WLTP” to implement a full comparison for energy demand and fuel consumption for different propulsion systems (i.e., Diesel ICE, Fuel cell and Electric engines). To better understand the comparison, a life cycle assessment is conducted using “GREET” and “GHGenius” software, which represents a clear demonstration of side effects and emissions of each engine on the environment. The results show that for “WLTP” cycle the bus needs 2423kJ energy for traveling each kilometer while the averaged amount of energy for traveling one kilometer of real driving cycle reaches to 1708kJ. By computing total energy use of  an electric bus we conclude, electric buses use almost 58% of electric energy for driving and the rest is lost. Then fuel cell and internal combustion engine buses have energy efficiency of 36% and 24% respectively. Concerning LCA analysis, it becomes apparent that unlike efficiency, electric buses are not environmentally benign as fuel cell buses. LCA analysis showed that fuel cell buses that use steam reforming hydrogen production process are a cleaner option than electric buses. Finally, since diesel buses produce the most emission, especially CO2, and consume the most energy in the total life cycle, they have no advantage for public transportation fleet.

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Traffic control is a major and common problem in large-scale urban decision-making, particularly in metropolises. Several models of intelligent highways have been proposed to tackle the issue, and the longitudinal speed control of vehicles remains a key issue in the field of intelligent highways. Many researchers have been investigating the longitudinal speed control of vehicles. However, their proposed models disregard important and influential presumptions. In the present study, the longitudinal dynamics control of vehicles in the presence of nonlinear factors, such as air resistance, rolling resistance, a not ideal gearbox, an internal combustion engine and a torque converter, is investigated. Moreover, considering the presented model and using model reference adaptive control, a proper controller is designed to control the longitudinal speed of intelligent vehicles. The results of the proposed model, which is validated by commercial software, are in good agreement with real-world situations. Hence, a positive step is taken for controlling longitudinal speed of intelligent vehicles on an intelligent highway platform.

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A comparative full life cycle assessment of a gasoline vehicle and a fuel cell vehicle (FCV) with five different fuel cycles including steam methane reforming (SMR), coal gasification, photovoltaic (PV), solar thermal, and grid-based electrolysis is presented in this paper. The results show that the total greenhouse gas emissions (GHG) are mainly found in the materials production and the component manufacturing stages of the FCV. Among various hydrogen production methods, the FCV with PV electrolysis has the lowest GHG emissions of 0.13 kg CO₂ eq./km. The total GHG emissions of the gasoline vehicle are estimated as 0.30 kg CO₂ eq./km mainly from the operation stage. An uncertainty analysis is carried out to assess the effects of variations of different input parameters on the total emissions. With a 95% level of confidence, the total emissions of the FCV with PV electrolysis is 0.18±0.05 kg CO₂ eq./km. The component manufacturing and assembly stage drives the total GHG emissions uncertainty the most.

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Braking test is one of the most important tests of a mechanized technical inspection line. In this study, the effect of tire pressure changes on the accuracy of the braking test results is investigated at technical inspection centers. This study is conducted in three stages. In the first step, the braking efficiency at different tire pressures is examined using a roller brake tester. In the second step, the tests at different pressures and velocities on the road are done. These tests are carried out in terms of stopping distance, to ensure the accuracy and reliability of the first step test results. The results of the first and second steps showed that the effect of tire pressure changes on the braking efficiency is significant. In the third step, the braking test results of a thousand vehicles that received technical inspection certificate are studied. Analysis of these results, considering the results of the first and second steps cleared that about 16% of vehicles that received technical inspection certificate have lower braking efficiency than the minimum acceptable efficiency. The obtained results specified the necessity of adjusting the pressure of tires before the braking test at vehicle technical inspection centers in Iran.
 

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The primary objective of a brake disc is to absorb frictional heat during braking and dissipated it immediately by convection and radiation. However, during hard and repetitive brakings, thermal coning on brake disc generates surface hot spots which are responsible for the undesired accumulation of compressive stresses on the surface of the brake disc. These stresses would lead to disc cracking and finally failure of it. In the current paper, a coupled transient thermo-mechanical FE analysis of a heavy vehicle braking system is carried out in a way that thermal coning of the disc and surface hot spots and bands are recognizable. Braking condition is chosen from a standard for hard braking in trucks. Moreover, five additional braking actions with different severities are investigated to study the effects of braking severity on thermo-mechanical instability of brake discs. Comparison of numerical results of transient temperature during braking and cooling phases with experiment reveal a high accuracy of thermal prediction of this model. Also, the results show that thermal coning of brake disc is varied between 0.05 to 0.7 mm depending on braking severity and tangential location of the disc. Additionally, surface hot spots experience higher temperature gradients in higher decelerations. Finally, results show that circumferential compressive stresses during braking are the major component of thermal stresses and should be taken into account for life estimation analysis.

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Global restrictions on the use of fossil fuels in the transportation sector and the commitment to rapid response to the climate change have created a strong incentive to develop fuel-efficient and low-emission vehicle systems. Hydraulic hybrid power train technology is one of the temporary solutions introduced to optimize internal combustion engine (ICE) operation and regenerate braking energy. The hydraulic hybrid power train system (HHPS) has a higher power density than the electric one. So, it is used in heavy vehicles, agricultural and construction machinery that need a high-power density to accelerate or recover the braking energy.  In some trucks, such as refuses collection trucks, fire trucks and delivery trucks, a high percentage of the ICE energy is consumed by the auxiliary systems. In this type of trucks, the hydraulic hybrid power train systems are not very efficient. This paper introduces a hydraulic hybrid auxiliary system (HHAS) concept to manage the energy consumed by the auxiliary system in refuse collection trucks. In the first part of the paper, the configurations and operating modes of series, parallel and hydro-mechanical HHPS are discussed and compared with the HHAS concept. In the following, the conventional refuse collection truck model and refuse truck equipped with HHAS model was developed in MATLAB/SINMULINK and simulated in Tehran refuse collection truck driving cycle. The simulation results show that by using the ​​HHAS concept, the fuel consumption is reduced by 15 percent.

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In this paper, an optimized insulator for sound packaging of the vehicle dash panel is proposed. The combination of the micro perforated panel and porous layers has been selected to insulate the dash panel of a vehicle.  The main advantages of the mentioned combination are light weight and various tunable parameters in comparison with other insulators. These provide significant flexibility to achieve an optimal performance for the noise attenuation of the vehicle cabin. Therefore, the parameters of the selected sound package have been optimized in order to achieve suitable sound absorption in a selected frequency range. Furthermore, the Genetic Algorithm (GA) is used to optimize the parameters. It can achieve more reliable and more accurate outcomes compared to the conventional method.  Full vehicle SEA (Statistical Energy Analysis) simulations are used to evaluate the optimized sound package. The results indicate that the optimized concept has maximum sound absorption capability.  Consequently, the proposed sound package improves the vehicle's engine noise reduction by 5 dB in comparison with un-optimized sample in mid and high frequency ranges.

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This paper introduces a new configuration of ladder chassis containing a set of linear wave springs to improve the lateral stability of road vehicles. The governing equations for lateral stability of the ladder frame equipped with linear wave springs were derived. In order to investigate this new system a unit base of the ladder frame equipped with linear wave springs and a typical ladder frame were modeled using FEM methods (ABAQUS) with the same size conditions. This comparative study is utilized to validate the derived equations and also to compare the effectiveness of the new designed system with typical ladder frames. Results indicate that the new system has considerably improved the lateral stability of the vehicle during road transportation and also noticeably decreased the stress on the side and cross members.

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In this study, a new micro gas turbine engine is presented. The effect of inlet air cooling on the performance of the micro gas turbine engine by changing the parameters such as the temperature difference between the inlet air temperature (IAT) based on ISA (International Society of Automation) standard and turbine inlet temperature (TIT) has been investigated. then, an Optimization is done base on the Genetic Algorithm with two separate objectives, SNOx minimization, and Thermal efficiency maximization, separately. The thermal efficiency and specific consumption of the optimized cycle based on the thermal efficiency are compared with the XU7/L3 internal combustion engine to produce the output power of 64.57 KW. Results show by adding a cooling system to the micro gas turbines to cool the inlet air with the coefficient performance of 2 and 4 increased the thermal efficiency by about 11.37% rather than base mrio gas turbine engine Eventually, the proposed micro gas turbine engine is more efficient than the XU7/L3 internal combustion engine. so It can be understood that micro  GT is one of the best substitutes for the internal combustion engine in the new vehicle age just by adding the cooling system.

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In this study, the driver airbag geometry and internal pressure were considered as the main parameters to investigate the head injury severity in a frontal crash. The total energy absorption of an airbag was investigated in a drop test simulation and its rate was discussed by the depression distance parameter. On the other hand, the maximum deceleration of the impactor was determined to represent the airbag stiffness by a defined deceleration peak parameter. Thus, the depression distance and the deceleration peak were the objective functions for an isolated airbag under a lumped-mass impact simulation. Furthermore, an optimal matrix was generated using the design method of experiments (DOE) and yielded the airbag parameters as outputs. After the evaluation of the design parameters by the Taguchi method, the ANOVA method was used to predict the most effective parameters. Finally, a sled test with the 50% HYBRID III dummy and the defined airbag was simulated. An experimental crash was selected as the reference point to verify the simulation and to be used to compare the outcomes. Even though the objective function of depression distance showed contradictory effects to reduce the head injury severity, the results showed a %16.4 reduction in the driver head injury in a full-frontal crash.

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This paper considers the asymptotic zero tracking error as well as string stability of large-scale automated vehicle convoys (LAVC). Both centralized and decentralized bi-directional network topologies are investigated. A double integrator dynamical equation is defined to describe the 1-D dynamics of automated vehicles (AV). A centralized / decentralized controller which employs the relative displacement and velocity compared with the backward and forward AVs is defined for all following AVs. Since the dynamical equation of LAVC is hard to be analyzed for internal stability, a PDE-based approach is introduced to decouple and reduce the closed-loop dynamical equation.  According to this approach, we will be able to decouple the dynamical equation of all AVs individually based on the error dynamics. After simplifying the dynamical equation of LAVC, the conditions satisfying the internal stability of centralized and decentralized networks are obtained. After that, algebraic analyses in frequency domain will able us to find the constraints on control gains guaranteeing the string stability. Simulation and experimental results are available to describe the merits of this algorithm.

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In this study, a multi-objective differential evolution with fuzzy inference-based dynamic adaptable mutation factor with hybrid usage of non-dominated sorting and crowding distance (MODE-FM) is utilized for Pareto optimization of a 5-degree of freedom nonlinear vehicle vibration model considering the five conflicting functions simultaneously, under different road inputs. The significant conflicting objective functions that have been observed here are, namely, vertical seat acceleration, vertical forward tire velocity, vertical rear tire velocity, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Different road inputs are, namely, double-bump, stationary random road and non-stationary random road. It is exhibited that the optimum solutions of 5-objective optimization contain those of 2-objective optimization and, as a result, this important matter creates more options for optimal design of nonlinear vehicle vibration model.

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This paper experimentally investigates the trafficability of a small tracked vehicle on a slope. An increase in the angle of slope inclination may divert the vehicle from its path. In other words, the deviation of the vehicle is due to a sudden increase in the yaw angle. Also, the tip-over occurs at a specific slope angle. The locomotion of the small tracked vehicle on soils with different terramechanics (such as cohesion, internal friction angle, cohesive modulus, and friction modulus) is also simulated to evaluate its slope-traversing performance. Moreover, the impact of velocity and soil type on traversing a slope is measured. The proposed yaw angle control system is modeled for controlling the yaw angle of the tracked vehicle. This controller is designed through co-simulation. It keeps the tracked vehicle at zero yaw angle to achieve straight locomotion on slopes. It is compared to the PI, PID, and fuzzy controllers. The response of this controller is faster than PI and PID controllers. A Comparison between fuzzy and proposed yaw angle controller yields almost similar responses. The mechanism of the proposed yaw angle controller is also easier to understand. The precision of the controller's performance is measured by simulating over different terrains.

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In this paper, firstly chaotic behavior of the lateral dynamics of vehicle is investigated by the use of numerical tools including Lyapunov exponent and bifurcation diagrams. To this end rout to chaos along with period doubling and quasi-periodic responses are demonstrated in terms of bifurcation diagrams. After chaos analysis, a novel controller commensurate with the chaotic characteristics of the system, in conformity with Poincaré map is represented to suppress the chaotic behavior of lateral movement. The Poincaré map of the system is derived by means of a neuro fuzzy network. A robust Fuzzy system on the basis of nonlinear Ott-Grebogi-Yorke (OGY) method forms the control system. Closed-loop results of the system shows effectiveness of the chaos controller in extreme conditions.

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Environmental pollution and reduction of fossil fuel resources can be considered as the most important challenges for human society in the recent years. The results of previous studies show that the main consumer of fossil fuels and, consequently, most of the air pollutants, is related to the transportation industry and especially cars. The increasing growth of vehicles, the increase in traffic and the decrease in the average speed of inner-city vehicles have led to a sharp increase in fuel consumption. To address this problem, automakers have proposed the development and commercialization of hybrid vehicles as an alternative to internal combustion vehicles. In this paper, the design of an energy management system in a fuel-cell hybrid vehicle based on the look-ahead fuzzy control is considered. The preparation of fuzzy rules and the design of membership functions is based on the fuel efficiency curve of the fuel-cell. In look-ahead fuzzy control, the ahead conditions of the vehicle are the basis for decision in terms of slope and speed limit due to path curves as well as battery charge level. The fuzzy controller will determine the on or off status of the fuel-cell, as well as the power required. The motion of the fuel-cell hybrid vehicle on a real road is simulated and the performance of the proposed look-ahead controller is compared with the base controller (thermostatic method). The simulation results show that using the proposed approach can reduce the fuel consumption of the fuel-cell hybrid vehicle as well as travel time.

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In this paper, the optimization of the suspension system’s parameters is performed using a combined Taguchi and TOPSIS method, in order to improve the car handling and ride comfort. The car handling and ride comfort are two contradictory dynamic indices; therefore, to improve both car handling and ride comfort, there is a need for compromising between these two indices. For this purpose, the criteria affecting these two are first identified. The lateral acceleration and the body roll angle were used to evaluate the handling, and the RMS of vertical acceleration of the vehicle body was used to evaluate the ride comfort. The design factors including stiffness of springs and damping coefficient of dampers in the front and rear suspension system were also taken into account. On this basis, the results obtained from the vehicle’s motion in the DLC test were evaluated in the CarSim software. Then, the ideal tests were identified using the combined entropy and TOPSIS technique; this method has been proposed for managing the handling and ride comfort criteria. Finally, the optimal level of the suspension system’s factors was extracted using Taguchi method. It is evident from the results that, for different speeds, the body roll angle was improved up to 6.5%, and the RMS of the vertical acceleration of the vehicle body was optimized up to 4% to 7%.

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This paper introduces a trajectory planning algorithm for long-term freeway driving for autonomous vehicles including different modes of motion. In the autonomous driving in a freeway, different maneuvers are needed, including free flow, distance adaption, speed adaption, lane change and overtaking. This paper introduces an algorithm that provides all of these driving scenarios in the trajectory planning for an autonomous vehicle. All maneuvers are classified and proper formulation for each driving mode formulated. Then, an algorithm is introduced to show the procedure of decision making and switching between all driving modes. The relative distances and velocities of the other peripheral and front vehicle from autonomous vehicle are considered as the main factors for decision making during the travelling in the freeway. By the developed simulation programming, validity and effectiveness of the algorithm are verified, and pseudo code and flowchart for the simulation programming are introduced. Later in two simulation studies, different driving conditions are generated and results have been discussed and analyzed by detail.

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The adaptive size-independent consensus problem of uni-directional (UD) and bi-directional (BD) decentralized large-scale vehicle convoys with uncertain dynamics has been investigated in this research work. The constant distance plan (CDP) is employed to adjust the distances between successive vehicles. We assume that only relative displacement information between adjacent vehicles is accessible (partial measurement) and other information such as relative velocity and acceleration are not provided. The stability of the convoy can be performed by the analysis of each couple of consecutive vehicles. The main objective is to design an adaptive size-independent control protocol maintaining internal and string stability based on CDP with only partial measurement. Appropriate adaptive rules are derived to estimate the uncertain dynamics by utilizing only relative displacement. It will be proved that the presented adaptive protocol assures both internal stability (asymptotic stability of closed-loop convoy) and string stability (tracking error attenuation) of large-scale decentralized UD and BD convoys under the CDP. Simulations demonstrate the efficiency of the presented control framework.

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The development and adoption of electric vehicles (EVs) appears to be an excellent way to mitigate environmental problems such as climate change and global warming exacerbated by the transportation sector. However, it faces numerous challenges, such as optimal locations for EV charging stations and underdeveloped EVCS infrastructure, among the major obstacles. The present study is based on the location planning of charging stations in real cases of central and densely populated districts of Tehran, the capital of Iran. In order to achieve this goal, this paper attempts to validate the results of a previous study in another country. Secondly, by employing preceding principals in accordance with relevant information collected from the car park and petrol stations in the regions of study, a five-integer linear program is proposed based on a weighted set coverage model considering EV users' convenience, daily life conditions, and investment costs, and finally optimally solved by genetic algorithm under various distribution conditions; normal, uniform, Poisson and exponential, to specify the location and number of EV charging stations in such a way that EV drivers can have access to chargers, within an acceptable driving range.

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Connecting point of the longitudinal veins and cross-veins in wing is called Joint.  In some insect wing joints, there is a type of rubber-like protein called Resilin. Due to the low Young's modulus of this protein, its presence in the wing can help to change the shape of the wing during flight. Today, using composite structures in flying vehicles in order to achieve the desired shape of wing is considered. The purpose of this study is the multi-objective optimization of artificial wing by arranging Resilin joints in the artificial wing of Micro air vehicles (MAVs). The amount of torsion and bending of the flapping robot wings is considered as the objective function to improve the flight performance of robots. Two types of artificial wings have been investigated, and considering pareto points, the optimal arrangement of Resilin joints has been achieved.  The result of this study shows that in both wings, with the presence of Resilin in the joints, the amount of torsion has increased to 38.65 degrees.