Automotive Science and Engineering

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The present paper aims to improve the dynamical balancing of a slider-crank mechanism. This mechanism has been widely used in internal combustion engines, especially vehicle engines; hence, its dynamical balancing is important significantly. To have a full balance mechanism, the shaking forces and shaking moment of foundations should be eliminated completely. However, this elimination is usually impossible. Hence, in the current study, a multi-objective optimization is carried out to maintain the optimal balance of mechanism. The vertical and horizontal components of shaking forces and shaking moment are considered as objective functions. Also, the design variables are included the mass, the moment of inertia and the mass center location of mechanism links. The length of mechanism links is also considered constant for achieving a fixed slider course. The four-objective optimization is applied using a differential evolution algorithm. The optimization results are presented in Pareto diagrams as suitable tools for selecting a mechanism with desired characteristics according to the importance of each objective function. The optimal mechanism is finally introduced by the mapping method. The comparison of optimized mechanisms and the original one indicates a significant reduction of shaking forces and shaking moment as well as the reduction of energy consumption.

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Thin-walled structures play an important role in absorbing the energy in a low impact crash of vehicles up to saving lives from high impact Injury. In this paper, the thin-walled columns by using a hybrid Design of Experiments (DOE) and Ant Colony Algorithm (ACO) has been optimized. The analysis of the behavior of the nonlinear models under bending load is done using finite-element software Abaqus. The objective is to study the performance geometrically parameters of the columns using DOE-ACO approach.
DOE method is being applied to determine the effects of cross-sections, material, and thickness on the energy absorption; and the ACO method is used for finding more accurate thickness on energy absorption. Four types of thin-walled cross-sections, i.e., circle, ellipse, hexagon, and square are used in this study. The optimized results of DOE method show that aluminum alloy (Al-6061) and high strength low alloy steel (HSLA) square columns have a higher energy absorption in comparison with the other cross-sections. However, the amount of absorbed energy in two types of columns is equal but, 50 percent weight reduction may be seen in Al-6061 columns. The columns are re-optimized by ACO to find the best thickness in the last step.
In the following, by topology optimization participation, a new plan is proposed by the same thickness and 50% less weight, that has a higher crashworthiness efficiency by increasing SAE more than 70%. As a result of this plan is bridging the gap between standard topological design and multi-criteria optimization.
 

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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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Application of Mg alloy parts in automotive industry is increasing to reduce weight and fuel consumption. One of the high potential parts for application of Mg alloys is the front seat frame. However, change of material is accompanied by change of manufacturing process and change of design for the seat frame. In the present research while keeping the reference overall ergonomic outline, a new substitute Mg alloy design was proposed, featuring a simple easy to manufacture Z profile. Next, a two-stage optimization technique (size and shape) is proposed for the Mg seat frame based on the stress and displacement criteria of standard test plans. The final optimized design is close to fully-stressed state and is 70% lighter than the reference steel backrest.

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Rollover of sport utility vehicles is a critical challenge for dynamic stability of the vehicle. Due to the high rate of fatalities resulted from the rollover, in order to reduces the injuries, the design of active vehicle controllers has received significant attention among the researchers and car companies. In this article, a multi-criteria optimum method is discussed in order to design a dynamics stabilizing controller via differential braking with an optimum braking torque distribution. To this end, the nonlinear control method on the basis of the sliding mode techniques has been implemented that provides ride comfort, improve safety performance, and maintain maneuverability. To address the trade-off between the conflicting requirements of vehicle dynamic control in terms of maneuverability and rollover prevention capability, we formulate an artificial intelligence-based multi-criteria genetic algorithms. The simulation verification analysis indicates that the utilized optimum distribution braking torques result in the desired enhancement in roll stability of the vehicle.

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A multi-objective optimization and thermal analysis is performed by both experimental and numerical approaches on a Stirling engine cooler and heater. The power generated is measured experimentally by an electrical engine coupled with the crank case, and the friction is estimated by the difference between the necessary power used for rotating the engine at a specific pressure and speed, versus the actual power measured experimentally. In the experimental approach, different conditions were considered; for example, the charge pressure varied from 5-9 bars, and the engine speed varied from 286-1146 rpm. The maximum power generated was 461.3 W and was reported at 9 bars of charge pressure and 1146 rpm engine speed. Numerical approach was carried to simulate thermal balance for investigations on the effect of friction, engine speed and efficiency on generated engine power. Average values of Nusselt number and coefficient of friction were suggested from simulation results.
The multi-objective optimization was held using DOE method for maximizing engine efficiency and power, and also minimizing pressure drop. The top and bottom boundary values for our optimization were 5-9 bars of pressure and 286-1146 rpm of engine speed; for both helium and carbon dioxide. To do so, all three significance factors (engine speed, efficiency and friction) were given different weights, thus different combinations of weight value was investigated
Amongst different interesting findings, results showed that if the efficiency weight factor changed from 1 to 3, for helium in a specific condition, the optimum engine speed would increase by approximately 30.6 %

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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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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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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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Recently, number of Hybrid Electric Vehicles (HEV) is on the rise due to concerns over environmental issues. By combining fuel and electricity as two sources of power, this type of vehicle is capable of bettering fuel economy and lowering emission. In this work, fuel and electrical energy consumption of a parallel hybrid electric vehicle are investigated through TEH-CAR urban drive cycle. For this purpose, a forward looking model is developed in AVL CRUISE M. To ensure adequacy of the model and take engine gas path components’ dynamic interaction into account, a crank based model with individual cylinders is utilized. Furthermore, a throttle filter is presented to slow down engine’s response and also, allow the electric motor to have the larger share of delivering power in transients. Finally, genetic algorithm is used to find optimal values for throttle filter parameter and electric motor load ratio, in order to have minimal overall fuel and electrical energy consumption. The optimization results show 1.2% of fuel and 20.2% of total energy consumption reduction in comparison with conventional torque assist.

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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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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.
 

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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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Portfolio optimization is the process of distributing a specific amount of wealth across various available assets, with the aim of achieving the highest possible returns while minimizing investment risks. There are a large number of studies on portfolio optimization in various cases, covering numerous applications; however, none have focused exclusively on the automotive industry as one of the largest manufacturing sectors in the global economy. Since the economic activity of this industry has a coherent pattern with that of the global economy, the automotive industry is very sensitive to the booms and busts of business cycles. Due to the volatile global economic environment and significant inter-industry implications, providing an appropriate approach to investing in this sector is essential. Thus, this paper aims to provide an appropriate approach to investing in this sector. In this study, an extended Conditional Drawdown at Risk (CDaR) model with cardinality and threshold constraints for portfolio optimization problems is proposed, which is highly beneficial in practical portfolio management. The feature of this risk management technique is that it admits the formulation of a portfolio optimization model as a linear programming problem. The CDaR risk functions family also enables a risk manager to control the worst ( 1-α)×100%  drawdowns. In order to demonstrate the effectiveness of the proposed model, a real-world empirical case study from the annual financial statements of automotive companies and their suppliers in the Tehran Stock Exchange (TSE) database is utilized.

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Fleet routing is one of the basic solutions to meet the good demand of customers in which decisions are made based on the limitations of product supply warehouses, time limits for sending orders, variety of products and the capacity of fleet vehicles. Although valuable efforts have been made so far in modeling and solving the fleet routing problem, there is still a need for new solutions to further make the model more realistic. In most research, the goal is to reach the shortest distance to supply the desired products. Time window restrictions are also applied with the aim of reducing product delivery time. In this paper, issues such as customers' need for multiple products, limited warehouses in terms of the type and number of products that can be offered, and also the uncertainty about handling a customer's request or the possibility of canceling a customer order are considered. We used the random model method to deal with the uncertainty of customer demand. A fuzzy clustering method was also proposed for customer grouping. The final model is an integer linear optimization model that is solved with the powerful tools of Mosek and Yalmip. Based on the simulation results, it was identified to what extent possible and accidental changes in customer behavior could affect shipping costs. It was also determined based on these results that the effective parameters in product distribution, such as vehicle speed, can be effective in the face of uncertainty in customer demand.