Automotive Science and Engineering

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Improvement in braking performance and vehicle stability can be achieved through the use of braking systems whose brake force distribution is variable. Electronic braking force distribution has an important and serious role in the vehicle stopping distance and stability. In this paper a new approach will be presented to achieve the braking force distribution strategy for articulated vehicles. For this purpose, the mathematical optimization process has been implemented. This strategy, defined as an innovative braking force distribution strategy, is based on the wheel slips. The simulation results illustrate proposed strategy can significantly improve the vehicle stability in curved braking for different levels of vehicle deceleration

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Intake system design as well as inlet ports and valves configuration is of paramount importance in the optimal performance of internal combustion engines. In the present study, the effect of inlet ports design is investigated on OM-457LA diesel engine by using a CFD analysis and the AVL-Fire code as well. A thermodynamic model of the whole engine equipped with a turbocharger and an intercooler is used to obtain the initial and boundary conditions of the inlet and outlet ports of the engine cylinder which are necessary for performing the three dimensional CFD analysis. The intake stroke as well as the compression and power strokes are included in this three dimensional CFD model. As a mean of validation the performance of the engine model with the base configuration of the inlet ports is compared to the experimental data. Two new alternative configurations for the inlet ports are then investigated with respect to the turbulence levels of the in-cylinder flow and the combustion characteristics as well. Finally it is demonstrated that applying the new configurations results in circa 75% reduction in nitric oxide formation besides increase of 32% in the in-cylinder flow swirl.

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Parametric design optimization of an automotive body crashworthiness improvement is presented. The thicknesses of parts are employed as design variables for optimization whose objective is to increase the maximum deceleration value of the vehicle center of gravity during an impact. Using the Taguchi method, this study analyzes the optimum conditions for design objectives and the impact factors and their optimal levels are obtained by a range analysis of the experiment results. A full frontal impact is implemented for the crashworthiness simulation in the nonlinear dynamic code, LS-DYNA. The controllable factors used in this study consist of the six inside foreheads structural parts, while design parameters are relevant thicknesses. The most interestingly the maximum deceleration of the vehicle center of gravity is reduced by 20% during a full frontal impact while several parts experience mass reduction.

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Non-linear characteristic of tire forces is the main cause of vehicle lateral dynamics instability, while direct yaw moment control is an effective method to recover the vehicle stability. In this paper, an optimal linear quadratic regulator (LQR) controller for roll-yaw dynamics to articulated heavy vehicles is developed. For this purpose, the equations of motion obtained by the MATLAB software are coded and then a control law is introduced by minimizing the local differences between the predicted and the desired responses. The influence of some parameters such as the anti roll bar, change the parameters of the suspension system and track wide in articulated heavy vehicles stability has been studied. The simulation results show that the vehicle stability can be remarkably improved when the optimal linear controller is applied

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In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimization of the automotive energy absorbing components. In this paper, axial impact crushing behavior of the aluminum foam-filled thin-walled tubes are studied by the finite element method using commercial software ABAQUS. Comparison of the present simulation results with the results of the experiments reported in the previous works indicated the validity of the numerical analyses. A meta-model based on the feed-forward artificial neural networks are then obtained for modeling of both the absorbed energy (E) and the peak crushing force (Fmax) with respect to design variables using those data obtained from the finite element modeling. Using such obtained neural network models, a modified multi-objective GA is used for the Pareto-based optimization of the aluminum foam-filled thinwalled tubes considering three conflicting objectives such as energy absorption, weight of structure, and peak crushing force.

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In this study the performance and emissions characteristics of a heavy-duty, direct injection, Compression ignition (CI) engine which is specialized in agriculture, have been investigated experimentally. For this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (BSFC), peak pressure (PP), nitrogen oxides (NOx), carbon dioxide (CO2), Carbon monoxide (CO), hydrocarbon (HC) and Soot emissions has been considered. The tests were performed at various injection timings, loads and speeds. It is used artificial neural network (ANN) for predicting and modeling the engine performance and emission. Multi-objective optimization with respect to engine emissions level and engine power was used in order to deter mine the optimum load, speed and injection timing. For this goal, a fast and elitist non-dominated sorting genetic algorithm II (NSGA II) was applied to obtain maximum engine power with minimum total exhaust emissions as a two objective functions.

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In this paper, a method based on binary-coded genetic algorithm is proposed to explore an optimization method, for obtaining an optimal elliptical tank. This optimization method enhances the rollover threshold of a tank vehicle, especially under partial filling conditions. Minimizing the overturning moment imposed on the vehicle due to c.g. height of the liquid load, lateral acceleration and cargo load shift are properly applied. In the process, the width and height of tanker are assumed as constant parameters. Additionally, considering the constant cross-sectional area, an optimum elliptical tanker of each filling condition is presented to provide more roll stability. Moreover, the magnitudes of lateral and vertical translation of the cargo within the proposed optimal cross section under a constant lateral acceleration field are compared with those of conventional elliptical tank to demonstrate the performance potentials of the optimal shapes. Comparing the vehicle rollover threshold of proposed optimal tank with that of currently used elliptical and circular tank reveals that the optimal tank is improved approximately 18% higher than conventional one.

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In this paper, the optimum shape of Tailor-Welded Blanks (TWB) is investigated. The optimization is performed for two different case studies. The first example is deep drawing of a TWB with dissimilar materials and uniform thicknesses and the next example is deep drawing of a TWB with similar materials and non-uniform thicknesses. The effect of blank optimization on the weld line movement is investigated. Also the effect of weld line location on the blank optimization and weld line movement is examined.

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In spark ignition (SI) engines, the accurate control of air fuel ratio (AFR) in the stoichiometric value is required to reduce emission and fuel consumption. The wide operating range, the inherent nonlinearities and the modeling uncertainties of the engine system are the main difficulties arising in the design of AFR controller. In this paper, an optimization-based nonlinear control law is analytically developed for the injected fuel mass flow using the prediction of air fuel ratio response from a mean value engine model. The controller accuracy is more increased without chattering by appending the integral feedback technique to the design method. The simulation studies are carried out by applying severe changes in the throttle body angle to evaluate the performance of the proposed controller with and without integral feedback. The results show that the proposed controller is more effective than the conventional sliding mode controller in regulating the AFR without chattering.

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Robust control design of vehicles addresses the effect of uncertainties on the vehicle’s performance. In present study, the robust optimal multi-objective controller design on a non-linear full vehicle dynamic model with 8-degrees of freedom having parameter with probabilistic uncertainty considering two simultaneous conflicting objective functions has been made to prevent the rollover. The objective functions that have been simultaneously considered in this work are, namely, mean of control effort (MCE) and variance of control effort (VCE).The nonlinear control scheme based on sliding mode has been investigated so that applied braking torques on the four wheels are adopted as actuators. It is tried to achieve optimum and robust design against uncertainties existing in reality with including probabilistic analysis through a Monte Carlo simulation (MCS) approach in multi-objective optimization using the genetic algorithms. Finally, the comparison between the results of deterministic and probabilistic design has been presented. The comparison of the obtained robust results with those of deterministic approach shows the superiority robustness of probabilistic method.

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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.

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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.

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<span style="line-height: 115%; font-size: 10pt; font-style: normal; mso-bidi-font-size: 12.0pt; mso-ascii-font-family: " times="" new="" roman";="" mso-hansi-font-family:="" "times="" mso-bidi-language:="" fa;"="">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.

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The usage of turbochargers in diesel engines has led to the downsizing of the motors as well as usage of the waste gates in turbochargers. Any dimensional reduction in turbochargers and appurtenant leads to an enhancement on the performance of internal combustion engines and in environmental problems in terms of aerodynamic, thermodynamic and mechanical specifications for both engines and turbochargers. For this reason, the efforts need to be focused on the design of turbochargers and their waste gates accurately, in order to maintain its benefits as much as possible. The extent of waste gate opening, from full opened to closed valve, is demonstrated by the limiting compressor boost pressure ratio. Ultimately, an optimum point of limiting compressor boost pressure ratio is obtained then an increase in the values of BMEP and engine power for the same fuel consumption in range of waste gate opening is achieved

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In automotive industry, foam-filled structures have aroused increasing interest because of lightweight and capacity of energy absorption. Two types of foam filled thin walled structures such as the uniform foam filled (UF) and the functionally graded foam (FGF). To improve crashworthiness performance, FGF are used to fill structures, unlike existing uniform foam materials. In addition, by seeking for an optimal design systematically, some computational optimization signifies a more effective tool to find the best crashworthiness design of structures,. This paper will an exhaustive review of the previous studies of simulation-based optimization such as metamodels, objective functions, design variables, design of experiments, optimization techniques of crashworthiness of tubes.

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Due to the extensive use of cars and progresses in the vehicular industries, it has become necessary
to design vehicles with higher levels of safety standards. Development of the computer aided design and
analysis techniques has enabled employing well-developed commercial finite-element-based crash
simulation computer codes, in recent years. The present study is an attempt to optimize behavior of the
structural components of a passenger car in a full-frontal crash through including three types of energy
absorptions: (i) structural damping of the car body, (ii) viscoelastic characteristics of the constituent
materials of the bumper, and (iii) a proposed wide tapered multi-cell energy absorber. The optimization
technique relies on the design of experimental (DOE) method to enables finding the absolute extremum
solution through the response surface method (RSM) in MINITAB software. First, the car is modeled in
PATRAN and meshed in ANSA software. Then, the full-scale car model is analyzed in ABAQUS/CAE
software. The optimization has been accomplished through a multi-objective function to simultaneously,
maximize the observed energy and minimize the passenger’s deceleration. Results are verified by the
experimental results and effects of using non-equal importance coefficients for the absorbed energy and
passenger’s deceleration in the multi-objective function are also evaluated. Influence of the optimized
parameters on the frontal crash behavior of the vehicle body structure and passenger’s deceleration is
investigated, too.

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In this paper a new type of multi-objective differential evolution employing dynamically tunable mutation factor is used to optimally design non-linear vehicle model. In this way, non-dominated sorting algorithm with crowding distance criterion are combined to fuziified mutation differential evolution to construct multi-objective algorithm to solve the problem. In order to achieve fuzzified mutation factor, two inputs as generation number and population diversity and one output as the mutation factor are used in the fuzzy inference system. The objective functions optimized simultaneously are namely, vertical acceleration of sprung mass, relative displacement between sprung mass and unsprung mass and control force. Optimization processes have been done in two bi- and three objective areas. Comparison of the obtained results with those in the literature has shown the superiority of the proposed method of this work. Further, it has been shown that the results of 3-objective optimization include those of bi-objective one, and therefore it gives more optimum options to the designer

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Nowadays, lightweight automotive component design, regarding fuel consumption, environmental pollutants and manufacturing costs, is one of the main issues in the automotive societies. In addition, considering safety reasons, the durability of the automotive components, as one of the most important design requirements should be guaranteed. In this paper, a two-step optimization process including topology and shape optimization of an automotive wheel, as one of the most significant chassis components, is studied. At first, topology optimization method with volume and fatigue life constraints is used to obtain the optimal initial lightweight design, followed by shape optimization technique to improve the fatigue life. The results show 31.841% weight and 33.047% compliance reduction by topology and also 652.33% average minimum fatigue life enhancement, by the shape optimization. Therefore, the proposed two-step optimization method is qualified in designing the lightweight automotive wheel. The method used in this study can be a reference for optimization of other mechanical components.

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In order to lowering level of emissions of internal combustion engines (ICEs), they should be optimally controlled. However, ICEs operate under numerous operating conditions, which in turn makes it difficult to design controller for such nonlinear systems. In this article, a generalized unique controller for idle speed control under whole loading conditions is designed. In the current study, instead of tedious time-consuming trial-and-error based methods, soft computing techniques are employed to tune a proportional-integral-derivative (PID) controller which controls idle speed of engine. Since model based design technique is employed, a mean value model (MVM) is taken advantage due to its evidenced merits. Moreover, a brief introduction to the selected meta-heuristics is given followed by a flowchart to show how the engine model is linked to the optimization algorithms. A set point of 750 rpm is fed to the system, and the weighted sum of the three characteristics of mean squared error, control energy, and percent overshoot of the control system is set to the problem objective function to be minimized. It is evidenced that of all the examined meta-heuristics, Bees Algorithm (BA) converges to a better solution. Finally, to consider the effectiveness of the developed optimal controllers in disturbance rejection, they are implemented to the engine MVM model. The results of the research indicate, all the four optimally designed control systems, albeit the intermediate superiority, are of conspicuous success in compensating for the input disturbances of the load torque.

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In this paper, a new version of multi-objective differential evolution with dynamically adaptable mutation factor is used for Pareto optimization of a 5-degree of freedom vehicle vibration model excited by non-stationary random road profile. In this way, non-dominated sorting algorithm and crowding distance criterion have been combined to differential evolution with fuzzified mutation in order to achieve multi-objective meta-heuristic algorithm. To dynamically tune the mutation factor, two parameters, named, number of generation and population diversity are considered as inputs and, one parameter, named, the mutation factor as output of the fuzzy logic inference system. Conflicting objective functions that have been observed to be optimally designed simultaneously 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. Furthermore, different pairs of these objective functions have also been chosen for bi-objective optimization processes. The comparison of the obtained results with those in the literature unveils the superiority of the results of this work. It is displayed that the results of 5-objective optimization subsume those of bi-objective optimization and, consequently, this achievement can offer more optimal choices to designers.