R. Kazemi, M. Abdollahzade,
Volume 5, Issue 1 (3-2015)
Abstract
Car following process is time-varying in essence, due to the involvement of human actions. This paper develops an adaptive technique for car following modeling in a traffic flow. The proposed technique includes an online fuzzy neural network (OFNN) which is able to adapt its rule-consequent parameters to the time-varying processes. The proposed OFNN is first trained by an growing binary tree learning algorithm in offline mode, which produces favorable extrapolation performance, and then, is adapted to the stream of car following data, e.g. velocity and acceleration of the target vehicle, using an adaptive least squares estimation. The proposed approach is validated by means of real-world car following data sets. Simulation results confirm the satisfactory performance of the OFNN for adaptive car following modeling application.
A. Khalkhali, M. J. Saranjam,
Volume 5, Issue 1 (3-2015)
Abstract
7000 series Aluminum alloys are widely used in the automotive industries for structural lightweight components due to their exceptional high strength to weight ratio. However, this class of aluminum alloy is difficult to join by conventional fusion welding techniques so Friction stir welding (FSW) widely is used for welding this alloys. The process has been demonstrated to be effective and is currently industrially utilized for materials difficult to be welded or “un weldable”, especially aluminum and magnesium alloys. In this paper in order to predict the average grain size occurring in FSW of AA7050 plates due to the dynamic recrystallization (DRX) phenomena due to the welding process, a microstructure evolution model have been implemented in 3D fully coupled thermo-mechanical FEM in which the tool – work piece interaction in FSW of butt joint was investigated.
A. Zandi, S. Sohrabi, M. Shams,
Volume 5, Issue 1 (3-2015)
Abstract
Cavitation and turbulence in a diesel injector nozzle has a great effect on the development and primary breakup of spray. However, the mechanism of the cavitation flow inside the nozzle and its influence on spray characteristics have not been clearly known yet because of the internal nozzle flow complexities. In this paper, a comprehensive numerical simulation is carried out to study the internal flow of nozzle and the cavitation phenomenon. The internal cavitation flow of the nozzle is simulated using the Eulerian-Eulerian two-fluid model. In this approach, the diesel liquid and the diesel vapor are considered as two continuous phases, and the governing equations of each phase are solved separately. Simulation method is validated by comparing the numerical results with experimental data and good correspondence is achieved. The effective parameters on the nozzle flow are investigated, including injection pressure, back pressure, inlet curvature radius of orifice, orifice iconicity and its length. Results clearly show the importance of nozzle geometrical characteristics and dynamic parameters on the internal nozzle flow. Discharge coefficient of nozzle and cavitation distribution in the nozzle are extremely dependent on these parameters, so the effect of cavitation on the primary breakup is not negligible.
H. Saeidi Googarchin, S. M. Hossein Sharifi ,
Volume 5, Issue 1 (3-2015)
Abstract
The reason of this study is low cycle failure of cast iron cylinder head during the E5 standard durability test. The goal of the present investigation is durability test simulation and low cycle fatigue life evaluation of cast iron cylinder head. With uncouple structural analysis, preloads, thermal and mechanical load and boundary conditions are prescribed to finite element model of the cylinder head. To cover the durability test, the analysis steps repeated at five crack speed, 750, 1650, 2075, 2350 and 2600 rpm. The cylinder head is subjected to cyclic multi-axial non-proportional variable amplitude loads. In fatigue analysis, critical plane model with cumulative damage theory is applied to predict fatigue life. A general scripting is developed and validated to calculate fatigue life. The results show that the failure of critical cylinder head is the type of low cycle fatigue. The valve bridge region, where high temperature exists during operation of the engine, is the critical area in cast iron cylinder head in fatigue analysis approach. The simulation results are in accordance with the results of durability test.
Z. Baniamerian,
Volume 5, Issue 1 (3-2015)
Abstract
Continuous radiation ovens are of widely used apparatuses in paint cure and coating industries. The most important issue that guarantee the quality of paint curing is suitable thermal condition. Designing of these ovens for curing paint on bodies of complex geometries has become a challenge for many years. In the present study a new designing approach is introduced and advised because of its acceptable capabilities as well as its high speed. This approach is based on cure window criterion and applies gradient optimization technique. The present work can be divided into two parts: first, geometric and thermal simulation of the curing body and second, preparing the design tool.Since a significant part of designing procedure usually devotes the iterations of optimization procedure, defining a proper objective function efficiently reduces the time consumed for designing procedure. Procedure of finding an appropriate objective function has been comprehensively discussed in the present article. In this regard a new approach, called Hybrid method, applying an objective function based on few number of elements on the curing body is introduced. That is more fast and capable relative to other methods addressed in this study. Capability of the proposed methods is then evaluated for a typical complicated geometry.
S. Jafarmadar,
Volume 5, Issue 2 (6-2015)
Abstract
A. Khodayari,
Volume 5, Issue 2 (6-2015)
Abstract
Due to the increasing demand for traveling in public transportation systems and increasing traffic of vehicles, nowadays vehicles are getting to be intelligent to increase safety, reduce the probability of accident and also financial costs. Therefore, today, most vehicles are equipped with multiple safety control and vehicle navigation systems. In the process of developing such systems, simulation has become a cost-effective chance for the fast evolution of computational modeling techniques. The most popular microscopic traffic flow model is car following models which are increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. The control of car following is essential to its safety and its operational efficiency. This paper presents a car-following control system that was developed using a fuzzy model predictive control (FMPC). This system was used to simulate and predict the future behavior of a Driver-Vehicle-Unit (DVU) and was developed based on a new idea to calculate and estimate the instantaneous reaction of a DVU. At the end, for experimental evaluation, the FMPC system was used along with a human driver in a driving simulator. The results showed that the FMPC has better performance in keeping the safe distance in comparison with real data of human drivers behaviors. The proposed model can be recruited in driver assistant devices, safe distance keeping observers, collision prevention systems and other ITS applications.
J. Marzbanrad, I. Tahbaz-Zadeh Moghaddam,
Volume 5, Issue 2 (6-2015)
Abstract
Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption. Although there have been many attempts to model stop and go maneuver via traffic models, but predicting the future vehicle's acceleration in steps ahead has not been studied much in this models. The main contribution of this paper is in designing integrated genetic algorithm-artificial neural network (GA-ANN) which is a soft computing method to simulate and predict the future acceleration of the stop and go maneuver for different steps ahead based on US federal highway administration’s NGSIM dataset in real traffic flow. The results of this study are compared with two methods, back propagation based artificial neural network model (BP-ANN) and standard time series forecasting approach called ARX model. The mean absolute percentage error (MAPE), root mean square error (RMSE) and coefficient of determination or R-squared (R2) are utilized as three criteria for evaluating predictions accuracy. The results showed the effectiveness of the proposed approach for prediction of driving acceleration time series. The proposed model can be employed in intelligent transportation systems (ITS), collision prevention systems (CPS) and driver assistant systems (DAS) such as adaptive cruise control (ACC) and etc. The outcomes of this study can be used for the automotive industries who have been seeking accurate and inexpensive tools capable of predicting vehicle speeds up to a given point ahead of time, known as prediction horizon, which can be used for designing efficient predictive controllers based on human behaviors.
H. Golbakhshi, M. Namjoo,
Volume 5, Issue 2 (6-2015)
Abstract
The viscoelastic effect of rubber material on creation of rolling resistance is responsible for 10-33% dissipation of supplied power at the tire/road interaction surface. So, evaluating this kind of loss is very essential in any analysis concerned with energy saving. The transient dynamic analysis for including the rolling effects of the tire requires long CPU time and the obtained results are prone to considerable numerical oscillations. By adding the equivalent loads to static interaction of tire with the road, an efficient 3D FE analysis is presented for evaluating the dissipated energy of a rolling tire. The results closely match the related experimental and numerical investigations.
M. Masih-Tehrani, V. Esfahanian, M. Esfahanian, H. Nehzati, M.j. Esfandiary,
Volume 5, Issue 2 (6-2015)
Abstract
The Energy Storage System (ESS) is an expensive component of an E-bike. The idea of Hybrid Energy Storage System (HESS), a combination between battery and Ultra-Capacitor (UC), can moderate the cost of E-bike ESS. In this paper, a cost function is developed to use for optimal sizing of a HESS. This cost function is consisted of the HESS (battery, UC and DC/DC converter) cost and the cost of battery replacements during 10 years. The battery lifetime and riding pattern limit the life span of ESS. The “Portuguese standard NP EN 1986-1” riding pattern is used in this research. The Genetic Algorithm (GA) is used to solve the optimization problem. The results show that the cost and weight of HESS are clearly better than optimally sized battery ESS.
H. Ashuri,
Volume 5, Issue 2 (6-2015)
Abstract
Loading conditions and complex geometry have led the cylinder heads to become the most challenging parts of diesel engines. One of the most important durability problems in diesel engines is due to the cracks valves bridge area. The purpose of this study is a thermo-mechanical analysis of cylinder heads of diesel engines using a two-layer viscoelasticity model. The results of the thermo-mechanical analysis indicated that the maximum temperature and stress occurred in the valves bridge. The results of the finite element analysis correspond with the experimental tests, carried out by researchers, and illustrated the cylinder heads cracked in this region. The results of the thermo-mechanical analysis showed that when the engine is running the stress in the region is compressive caused by the thermal loading and combustion pressure. When the engine shut off the compressive stress turned into the tensile stress because of assembly loads. The valves bridge was under the cyclic tensile and compressive stress and then is under low cycle fatigue. After several cycles the fatigue cracks will appear in this region. The lifetime of this part can be determined through finite element analysis instead of experimental tests. Viscous strain was more than the plastic strain which is not negligible.
M. Heidari, H. Homaei, H. Golestanian, A. Heidari,
Volume 5, Issue 2 (6-2015)
Abstract
A new method based on principal component analysis (PCA) and artificial neural networks (ANN) is proposed for fault diagnosis of gearboxes. Firstly the six different base wavelets are considered, in which three are from real valued and other three from complex valued. Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction next, the continuous wavelet coefficients (CWC) are evaluated for some different scales. As a new method, the optimal range of wavelet scales is selected based on the maximum energy to Shannon entropy ratio criteria and consequently feature vectors are reduced. In addition, energy and Shannon entropy of the wavelet coefficients are used as two new features along with other statistical parameters as input of the classifier. To prevent the curse of dimensionality problem, the principal component analysis applies to this set of features. Finally, the gearbox faults are classified using these statistical features as input to machine learning techniques. Four artificial neural networks are used for faults classifications. The test result showed that the MLP identified the fault categories of gearbox more accurately for both real wavelet and complex wavelet and has a better diagnosis performance as compared to the RBF, LVQ and SOM.
R. Mehdipour, Z. Baniamerian, S. Sattar,
Volume 5, Issue 3 (9-2015)
Abstract
Paint cure oven is one of the most important parts of automobile production line. The cure speed and the magnitude of energy consumption are significant in auto manufacturing industry. The radiation oven has been of the interest by cure industry due to the reduction in energy consumption and appropriate cure. The design process of these ovens is really complex specially for bodies with complex geometry and bodies which especially delicate to specific temperature condition. According to the progress of computation equipment abilities and design algorithms, the utilization of these ovens has gained considerable attention from auto manufacturing industry in recent years. This study considers the benefits and defects of the radiation oven and shows that replacement of the convection ovens with radiation ovens in Iran Auto manufacturing industry would lead to 32% energy saving. The design process of convection continuous ovens is easier than radiation ovens but the associated numerical modeling is complicated and computationally intensive. In this study, the moving boundary method and its application to convection continuous ovens are discussed. The numerical results based on the moving boundary method are compared with the experimental results.
S. Mohammadi, H. Rabbani, S. Jalali Honarmand3,
Volume 5, Issue 3 (9-2015)
Abstract
Among human activities, motor vehicles play the most important role in air pollution. Air pollution has negative impacts on people and on the environment. In this paper the effect of oxygen-enriched air (20.8%, 21.8%, 22.8%, 23.8% and 24.8%) and different bioethanol-gasoline blends (zero, 5%, 10%, 15%, 20% and 25%) in different engine speeds (1000 rpm, 2000 rpm and 3000 rpm) on the amount of pollutants, particles, and fuel consumption were studied. To do so, a four-cylinder, four-stroke gasoline engine with Siemens fueling system was used. The results showed that when oxygen percentage in the inlet increased from 20.8% to 24.8%, the average amount of UHC, CO, fuel consumption and the number of fine and coarse particles decreased 126.75%, 11.25%, 17.02%, 77.37% and 243.25%, respectively, while the amount of CO2 and NOX increased 5.36% and 113.27%, respectively. Also the results showed that when bioethanol percentage in the mixture increased from zero to 25%, the average amount of UHC, CO2, CO and the number of fine and coarse particles decreased 104.53%, 3.45%, 34.57%, 41.42% and 96.09%, respectively, while the amount of NOX and fuel consumption increased 163.41% and 15.75%, respectively.
H. R. Zarei,
Volume 5, Issue 3 (9-2015)
Abstract
This research deals with axial and oblique impact crash tests on simple and hybrid composite tubes. Axial and oblique impact tests have been generated on simple and hybrid composite tubes with one, two and three layers. A drop test rig was used to conduct the experiments. Furthermore, in order to gain more detailed knowledge about the crash process, finite element simulations of the experiments have been performed. The explicit finite element code LS-DYNA was used. The simple tube and the composite hybrid tubes are modeled with thin layer shell elements. The elastic-plastic material model was used for the aluminum tube and the Chang-Chang failure model was implemented for the composite layers. In terms of finding more efficient (higher energy absorption) and lighter crash absorbers particularly, the absorbed energy and specific energy absorption are considered in this research. E SAE
H. Shojaeefard, M. Hakimollahi,
Volume 5, Issue 3 (9-2015)
Abstract
The new product development (NPD) is the process by which a new product idea is conceived, investigated, taken through the design process, manufactured, marketed and serviced. In Automotive Engineering these related to the product realization process (PRP) which consists of five phases: "Plan and Define Program", "Product Design and Development", "Process Design and Development", "Product and Process Validation", and "Production Launch, Feedback Assessment and Corrective Action". This paper proposes a process-based management concept focusing on controlling and measuring for their effective management including literature review of NPD performance measurement. Integrating the process-based management concept with the proper performance measure can initiate new knowledge which will contribute to the improvement of the automotive industry.
Gaurav, R. Kumar,
Volume 5, Issue 3 (9-2015)
Abstract
Air conditioning refrigerant R134a has value of global warming potential (GWP) 1300, which is much higher than MAC Directive (GWP below 150) passed in July 2006. This prompted a search for alternative refrigerant with GWP value less than 150. R1234yf is a new refrigerant which has lower GWP value of 4. Effect of blower speed has been compared and flammability issue of R1234yf has been addressed. Cooling time and relative humidity of car air -conditioning system using refrigerant R134a and R1234yf has also been discussed. The paper discusses various aspects for the replacement of R134a and provides a long term sustainable substitute of presently used refrigerant R134a in automobile air-conditioning.
M.h. Shojaeefard, G.r. Molaeimanesh, N. Aghamirzaei, S. Ghezelbiglo, B. Zeinolabedini,
Volume 5, Issue 4 (12-2015)
Abstract
Due to the increasing development in various branches of the automotive industry, the need for a comfort climate in the cabin is more sensible. However, to achieve climate comfort, HVAC system consumes a considerable amount of engine power. Hence, improving HVAC system performance leads to more energy saving of the vehicle which is a critical factor for nowadays automotive. Besides, one crucial task of HVAC system is defrosting/defogging of windshield which is considered as a mandatory requirement in most countries. In the current study, the defrosting/defogging performance of HVAC system in the main product of national vehicle platform is numerically evaluated based on the ECE-78-715 legal requirement. For this purpose, after validation and mesh independency study, the transient air flow in three-dimensional cabin geometry is simulated by SSTk-ω turbulence model via ANSYS Fluent software and the windshield thermal condition is reported during defrosting/defogging. Besides, two national HVAC standards of AERC-10-01 and AERC-10-02 are also checked. The results demonstrate that HVAC system of the main product of the national vehicle platform can satisfactorily fulfill ECE-78-715, AERC-10-01 and AERC-10-02.
M. Heidari, H. Homaei, H. Golestanian, ,
Volume 5, Issue 4 (12-2015)
Abstract
This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method consists of three steps, firstly the six different base wavelets are considered. Out of these six wavelets, the base wavelet is selected based on wavelet selection criterion to extract statistical features from wavelet coefficients of raw vibration signals. Based on wavelet selection criterion, Daubechies wavelet and Meyer are selected as the best base wavelet among the other wavelets considered from the Maximum Relative Energy and Maximum Energy to Shannon Entropy criteria respectively. Finally, the gearbox faults are classified using these statistical features as input to LSSVM technique. The optimal decomposition level of wavelet is selected based on the Maximum Energy to Shannon Entropy ratio criteria. In addition to this, Energy and Shannon Entropy of the wavelet coefficients are used as two new features along with other statistical parameters as input of the classifier. Some kernel functions and multi kernel function as a new method are used with three strategies for multi classification of gearboxes. The results of fault classification demonstrate that the LSSVM identified the fault categories of gearbox more accurately with multi kernel and OAOT strategy.
R. Hosseini, M. Azadi, , , ,
Volume 5, Issue 4 (12-2015)
Abstract
In the present paper, the modal analysis on a full finite element model of an off-road vehicle. This vehicle was modeled in the CATIA software and then meshed in the HYPERMESH software. The free vibration analysis was conducted by the ABAQUS software. By applying an external displacement, the forced vibration analysis was also performed. As a result, natural frequencies and shape modes were extracted to detect critical regions. Then, some improvements were suggested to have better vibration behavior of the vehicle.
