Automotive Science and Engineering

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One of the most significant issues of recent decades is pollution and dangers that may threat the environment. Different approaches were presented to protect the environment and target various sources of pollution. Old vehicles are one of the major sources of pollution in megacities as they consume and emit a lot of emissions. Therefore governments in different countries try to levy tax on pollution to motivate people to drive environment friendly and more efficient vehicles.
Tehran is one of the cities suffering rigorously from poor air quality. As a result, approximately 44 days in each year the air quality reckons as unhealthy for all residents. One of the suggested solutions is replacing conventional taxis across the city with hybrid electric vehicles. In this article this solution for the city of Tehran, Iran will be discussed and its feasibility will be evaluated using life cycle assessment.  
In order to conduct this, first data associated with air quality, pollution and taxis distribution in the city were presented. Then different designated vehicles were evaluated based on their technical performance and the emission they generate in different stages. Using the proposed model a comprehensive cost is defined and different vehicles were compared and the most viable choices by various considerations is introduced.

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In this experimental study, heat transfer and pressure drop, ΔP, of a coolant nanofluid, obtained by adding alumina nanoparticles to Ethylene Glycol-water mixture (60:40 by mass), in a automotive radiator have been investigated. For this purpose, an experimental setup has been designed and constructed. The experiments have been performed for base fluid and nanofluid with different volume fractions of 0.003, 0.006, 0.009 and 0.012 and under laminar regime with various coolant flow rates of 9, 11 and 13 lit/min and two air velocities of 3.75 and 2.85 m/s. The thermophysical properties have been calculated using the recently presented temperature dependent models. According to the results, the heat transfer and ΔP increase with increasing the coolant flow and nanoparticles volume fraction. Increasing the air velocity causes enhancement of heat transfer. Although Nusselt number decreases when nanofluid is utilized, it enhances as the nanoparticles volume fraction increases. The performance evaluation using nanofluid in the car radiator shows remarkable enhancement in radiator thermal efficiency. However, the ratio of heat transfer rate to the needed pumping power (Merit parameter) decreases.

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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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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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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 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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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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Today, a large part of a vehicle's performance depends on its suspension. These expectations are addressed in this paper, including ride comfort, road-holding, and lateral stability. Due to the high statistics of lateral overturning, preventing lateral overturning and providing lateral stability of the vehicle is one of the most important goals of this paper. In this paper, a new type of suspension based on the Series Active Variable-Geometry is used by designing a simple Sliding Mode Controller (SMC) to improve vehicle dynamics. On the contrary previous studies in this field, asymmetric distribution of control command has been used to increase the usefulness of suspension in standard road roughness and during longitudinal and transverse maneuvers. In this paper, by simulating crosswind and double lane change maneuvers, several ideas have been used to command the suspension links, and a 25% to 30% improvement in vehicle dynamic performance parameters has been achieved.

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In this paper, analysis and control of the chaotic vibrations in bounce dynamic of vehicle have been studied according to the comparison of controller based on the nonlinear control and chaos controller on the basis of the chaotic system properties. After modeling the vehicle dynamic, the chaotic behavior of the uncontrolled system was determined using combination of the numerical analysis including bifurcation diagrams and max Lyapunov exponent. The system parameters values were then identified in the quasi-periodic and chaotic behavior system. In order to eliminate the chaotic vibrations, the control signal was first developed using a nonlinear fast-terminal sliding mode control algorithm that its control gains are estimated online by fuzzy logic which was designed for vehicle vertical dynamics. Then the delayed feedback control was designed based on the development of Pyragas algorithm to control the system based on the properties of the chaotic system and generation of a small control signal. Comparison of the feedback system depicts priority of the Fuzzy-Pyragas controller in less energy consumption and better behavior.

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Background: Hydroforming is employed in the manufacture of hollow monolithic products to reduce the number of joints. This method can reduce the weight and enhance the quality of fluid transfer parts in a vehicle’s hydraulic system. Hydroforming is a process in which parts are formed into the shape of a mold using fluid pressure. An important issue in this process is adopting an optimal loading path. Methods: In the present research, a drop hammer was used to implement the dynamic loading path in the tests. Accordingly, a single energy source was used simultaneously to provide axial feeding and internal pressure. To this end, designing a mold suitable for the dynamic loading path was necessary. Results: This numerical study investigates tubes’ deformation based on the applied impact and the amount of fluid in the mold. Moreover, axial feeding was provided with the help of different punches on the sides of the tube. Hence, the kinetic energy, amount of fluid, sealing, lubrication, and the material and thickness of the tube must be proportional for the correct forming of the tube. From the smoothed-particle hydrodynamics perspective, it is a meshless method based on interpolation that uses a particle system to examine the system state and predict fields such as displacement, stress, and pressure. Conclusions: One of the main observations of this research is that selecting side punches with a smaller central hole radius is proportional to the kinetic energy and the amount of fluid. that is effective in achieving the optimal loading path.
 

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Due to the complex geometry and thermos-mechanical loading, cylinder heads are the most challenging parts among all parts engines. They must endure cyclic thermal and mechanical loading throughout their lifetime. Cast aluminum alloys are normally quenched after solution treatment process to improve aging responses. Rapid quenching can lead to high residual stress. Residual stress is one of the main reasons for failure of cylinder heads. The effect of residual stress on the thermal stress and low cycle fatigue life (LCF) of cylinder heads was studied. For this goal, Solidworks software was used to model the cylinder heads. Then the thermo-mechanical analysis was performed to determine the temperature and stress field in ANSYS software.  Finally, the fatigue life analysis that considers residual stress effect was done. The results of finite element analysis (FEA) proved that the effect of residual stress in LCF is significant which is not negligible. Thus, residual stress must be considered in the thermo-mechanical fatigue analysis of the engines cylinder heads. The numerical results showed that the area where the maximum temperature and stress is occurred is where the least LCF is predicted.

 

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The braking system has always been considered one of the most significant vehicle subsystems since it plays a key role in safety issues. To design such a complex system, modeling can be a helpful tool for designers to save time and costs. In this paper, the hydraulic braking system of a B-Class vehicle was modeled by simulating the relationship between brake components such as pedals, boosters, main cylinders, and wheel cylinders, with the vehicle dynamics by using the existing models of the tire and their dynamic relationships. The performed modeling was compared with the results of a concerning vehicle's direct movement. The results of this comparison showed that our modeling is very close to the experimental data. The braking distance parameter was selected to examine the effects of each braking component on the vehicle dynamics. The results of investigating the effect of different parameters of the braking system on the dynamic behavior of the vehicle indicated that the main cylinder diameter, the diameter of the front and rear wheels’ brake cylinders, the effective diameter of the front disk, and the diameter of the rear drum are the most effective design parameters in vehicle's braking system and optimal results are obtained by applying changes to these parameters.

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In this study, feedback neural networks namely Elman and Jordan are used for prediction of exhaust valve temperature for air cooled engines. Input-output data are extracted from an experimental setup including the valve mechanism of an air cooled engine. Inverse heat transfer problem applying the Adjoint problem is used to address the thermal flux through exhaust valve and seat. Elman and Jordan neural networks are used to predict the transient valve temperature using the experimental data. The results show that Elman and Jordan neural networks predicts well the transient exhaust valve temperature. However, Jordan neural network with training algorithm of Gradient Descent with Adaptive Learning Rate performs better with RMSE error of 16.3 for prediction of exhaust valve temperature.
 

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In this research, the effect of using three Nano fluids contains graphene oxide (GO), titanium oxide (TiO2) and aluminum oxide (Al2 O3) was analyzed on the heat transfer of the car radiator by experiment in physical conditions on the car engine. Distilled water and ethylene glycol (60:40) as the base fluid was companied with three nanoparticles contain graphene oxide, titanium oxide and aluminum oxide that each one separately with 0.1, 0.2 and 0.3 weight percent and flow rates of 10, 20, 32 and 40 liters per minute were used at normal engine temperature. After the temperature of the radiator cooling fluid reached 90 degrees Celsius and the fan was turned on for one minute, the results showed that increasing the weight percentage of nanoparticles to the base fluid increases the displacement heat transfer coefficient and most increase in the coefficient of heat transfer at 0.3 weight percent to an approximate value of 5.2% in aluminum oxide, 11.9% for titanium oxide and 28.7% for graphene oxide compared to the base fluid was received. With the increase in weight percentage, the pressure drop and Nusselt number increased.  The highest percentage increase in the radiator pressure drop for all three Nano fluids with 0.3 weight percentage and 2.2% for   aluminum oxide, 3.5% for Titanium oxide and 5.24% for graphene oxide were received.

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Harnessing nanomaterials and the piezo-phototronic effect, we engineered a high-performance ultraviolet (UV) photodetector (PD), unveiling a new frontier in optoelectronics. This novel device seamlessly integrates zinc oxide nanorods (ZnO NRs) onto a flexible polyethylene terephthalate- indium tin oxide (PET-ITO) substrate through a straightforward and efficient hydrothermal process. This unique nanostructure design outshines its competitors, producing significantly higher current under UV illumination despite a comparable detection area. The plot thickens with the intriguing "piezo-phototronic effect," where applying pressure under UV light amplifies the current and overall device efficiency. This groundbreaking discovery paves the way for cutting-edge optoelectronic applications, where nanomaterials and the piezo-phototronic effect join forces to redefine performance.
 

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Fueled by their potential for energy harvesting, ZnO nanorods (NRs) have sparked considerable enthusiasm in the development of piezoelectric nanogenerators in the last decade. This is attributed to their exceptional piezoelectric properties, semiconducting nature, cost-effectiveness, abundance, chemical stability in the presence of air, and, the availability of diverse and straightforward crystal growth technologies. This study explores and compares the piezoelectric properties of two promising nanostructured ZnO architectures: thin films deposited via radiofrequency (RF) magnetron sputtering and well-aligned nanorod arrays grown using a hydrothermal process. Both structures are fabricated on flexible polyethylene terephthalate (PET) with an indium tin oxide (ITO) electrode (PET-ITO substrate), presenting valuable options for flexible piezoelectric devices. By directly comparing these distinct morphologies, we provide insights into their respective advantages and limitations for energy harvesting and sensor applications. The investigation into the piezoelectric properties of ZnO NRs involved the construction of an actual piezoelectric nanogenerator. This device demonstrated a direct correlation between applied mechanical forces and the resultant voltage outputs. It was observed that when the same external force was applied to both devices, the ZnO NRs-based piezoelectric nanogenerator (PENG) exhibited a higher output voltage compared to the other device.

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A novel liquid cooling system for pouch-type lithium-ion batteries (LIBs) is proposed by focousing on uniform temperatue disturbution and effective heat dissipation. The system utilizes a michrochannel cold plate with an innovative coolant disturbution design. This study proposes a novel microchannel disturbution path design with each microchannel dimensioning 1 mm² and embeded in the battery's ciritical region to enhance the thermal contact among the LIB and the microchannels. This study aims to simulate and evaluate the performance of cooling system under varius Iranian environmental conditions (Tehran, Shiraz, Isfahan, and Bandar Abbas) and operational parametrs (channel pattern, flow rate) to achieve optimal battery temperature and reduce energy consumption.

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The transition from traditional internal combustion engine vehicles to electric vehicles is in progress. With their high energy density, low self-discharge rates, long cycle life, and absence of memory effects, lithium-ion batteries have become the primary power source for alternative vehicles. Throughout the battery's lifespan, its performance or health gradually deteriorates due to irreversible physical and chemical changes. Depending on the specific aging mechanisms, a battery may lose capacity or face increased internal resistance. Growing awareness of the importance of environmental protection and the potential implications associated with products and services has spurred interest in developing methods to better understand and address these impacts. Life cycle assessment is a method used to examine the environmental effects associated with all stages of product production. This study compares the operational conditions of an electric vehicle equipped with both new and old battery packs. The performance difference indicates that the vehicle with the aged battery has 17% less capacity, operates over 20% weaker in range, and its ohmic resistance increases by up to 150%. From a well-to-wheel perspective, using an electric vehicle with an old battery could result in a 2% increase in carbon dioxide emissions, reaching 56.638 g CO₂ equivalent per kilometer.