Automotive Science and Engineering

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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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Thermal modeling of an automotive cabin was performed in this paper to predict the inside cabin air temperature. To implement this task, thermal and ventilation loads were estimated and the mass and energy balance conservation equations for dry air and water vapor with considering a new parameter (air circulation ratio) as well as the balance equations of internal components of a cabin were derived and solved simultaneously. The performance of the proposed thermal modeling of a cabin was compared with the data collected from hot room experimental tests. These tests were run for various design parameters such as evaporating cooling load and cabin size (air volume inside cabin). The comparison of experimental and numerical results showed a good agreement. Parametric analysis with three parameters namely, vehicle speed, number of passengers, and A/C air mass flow rate was performed to investigate the effects of these parameters on cabin air temperature.

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In this paper, mini-channel type evaporator which is new in mobile air conditioning (MAC) or automotive air conditioning (AAC) systems is thermally modeled. The performance of mini-channel evaporator is also compared with the laminated evaporator which is being currently used in automotive industries. The mini-channel evaporator was constructed of two rows of parallel flow mini-channel tubes with inlet and outlet headers. The numerical results of modeling the laminated and mini-channel evaporators validated with the corresponding experimental data which was obtained from experiments performed on mobile air conditioning system in calorimeter test bench. The comparison of modeling results of two evaporators showed good agreement with experimental data. The performance of laminated and mini-channel evaporators were also compared under various operating conditions. The mini-channel evaporator had higher cooling capacity (7.2%) and higher refrigerant pressure drop (45%) in comparison with the corresponding values in laminated evaporator assuming the same external geometry. The outlet air temperature and enthalpy of minichannel evaporator was also lower, 11% and 8% respectively, than that for laminated evaporator. This cause to reduce the time period as well as power/fuel consumption for reaching the comfortable cabin temperature.

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In this paper, the acoustic environment in a vehicle cabin under the influence of highfrequencies aerodynamic sources has been studied. Some panels on the windshield, the roof, the doors, the front pillars, and the floor of a vehicle simulated as input source of noise when the car is moving at high speed, i.e. 112 km/h. The status of vehicle cabin in each of these modes has been studied and compared to each other. There are some methods to simulate acoustic behavior of a vehicle cavity such as Finite Elements or Statistical Energy Analysis methods. A brief overview for Statistical Energy Analysis (SAE) is stated. In this study, the statistical energy method is used for determination of acoustic analysis. Auto SEA software is used to simulate and estimate the amount of sound pressure level. In addition, sound pressure formulation presented and used for comparison in vehicle cabin points and with experimental results for validation. Also, considering viscoelastic materials, a common form of material nonbinding panel has determined. The result shows that the roof is the most important panel in acoustic analysis under influence of aerodynamic sources. Accordingly, this panel has more effectiveness in optimization to control sound pressure level in a vehicle cabin. In addition, the amount of reduction in sound pressure level (SPL) in the cabin with viscoelastic material is presented as it could diminish the vibration of plates. In addition, the effect of using acoustic glasses is presented. Finally, the SPL effect of passenger position including front and rear is investigated and compared

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In this paper, numerical simulation of FRP composite cylinder tubes progressive crushing processes is conducted using LS-Dyna. Details on the numerical modeling strategy are given and discussed. It is found that triggers introduced in the numerical simulation can effectively model the bevel trigger at the end of the tubular specimens. It is also found that two-layer finite element model based on the TsaiWu failure criteria is effective in representing the crushing failure mode of the tubular composite specimens and energy absorption characteristics. Employing GEvoM software, two meta-models are then obtained for modeling of both the absorbed energy (E) and the peak crushing force (Fmax) with respect to geometrical design variables using input output data obtained from the finite element modeling. Comparison between obtained meta-models and numerical results in both of training and testing sets show good approximation by using obtained polynomial models.

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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.

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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.

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In this paper, a two-surfaces sliding mode controller (TSSMC) is proposed for the voltage tracking control of a two input DC-DC converter in application of electric vehicles (EVs). The imperialist competitive algorithm (ICA) is used for tuning TSSMC parameters. The proposed controller significantly improves the transient response and disturbance rejection of the two input converters while preserving the closed-loop stability. The combination of the proposed controller and ICA, realizes a fast transient response over a wide transient load changes and input voltage disturbances. For modeling the equations governing the system, state-space average modeling technique is used. In order to analyzing the results, the two input converter equipped with the proposed controller, was modeled in MATLAB/SIMULINK environment. Simulation results are reported to validate the theoretical predictions and to confirm the superior performance of the proposed nonlinear controller when it is compared with a conventional pure SMC.

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The designing of advanced driver assistance systems and autonomous vehicles needs measurement of dynamical variations of vehicle, such as acceleration, velocity and yaw rate. Designed adaptive controllers to control lateral and longitudinal vehicle dynamics are based on the measured variables. Inertial MEMS-based sensors have some benefits including low price and low consumption that make them suitable choices to use in vehicle navigation problems. However, these sensors have some deterministic and stochastic error sources. These errors could diverge sensor outputs from the real values. Therefore, calibration of the inertial sensors is one of the most important processes that should be done in order to have the exact model of dynamical behaviors of the vehicle. In this paper, a new method, based on artificial neural network, is presented for the calibration of an inertial accelerometer applied in the vehicle navigation. Levenberg-Marquardt algorithm is used to train the designed neural network. This method has been tested in real driving scenarios and results show that the presented method reduces the root mean square error of the measured acceleration up to 96%. The presented method can be used in managing the traffic flow and designing collision avoidance systems.

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Recent evolutions in World Trade Organization (WTO) and other international trading agreements have made industries all around the world face a new era of intense global competition. Simultaneously with increased competitive pressure, permanent development and innovation comprise building blocks of firm excellence. In a dynamic environment, failure to innovate ends up with business stagnation and getting out of the competition ring.
Technological innovation capability is a complex, elusive and uncertain concept, which have made it difficult to characterize. Measuring technological innovation capability requires considering numerous qualitative and quantitative criteria at the same time. One of the main factors hindering the success of adopting technological innovation to attain competitive advantage by firms in developing countries is lack of awareness about and recognition of the level of firm technological capabilities and how to use them to acquire relative advantages. Evaluation of technological capability serves as a tool for identifying the required capabilities to implement the firm technological priorities.
Based on a wide spectrum of available literature, the present paper attempts to extract criteria related to technological innovation capabilities in the field of turbocharging technology. These criteria were then provided to a group of experts in automotive industry, so as to identify the desired level of technology for turbocharging technology in automotive industry. On the other hand, by restricting items of the questionnaire based on the experts’ opinions, the current state of turbocharging technology capabilities was identified, based on which technological gap in each criterion under study was determined. On the other hand, once the technological gap was identified, improvement projects were defined to either suppress or eliminate the gap.

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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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In order to achieve a successful new product, and certainly the successful implementation of a new product into a company, it is necessary to have a structured and documented approach to New Product Development (NPD), therefore providing a clear roadmap for the development of new products.New product development is a multi-stage process. Many different models with a varying number of stages have been proposed in the literature which in this paper are briefing them. This review highlights the NPD Models and process, from concept to consumer, and aim to find the consist gap of different NPD’s models in order for a company to succeed and use New products as a source for Competitive advantage.

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This paper mainly discusses the thermal behavior and performance of Lithium-ion batteries utilized in hybrid electric vehicles (HEVs), battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) based on numerical simulations. In this work, the battery’s thermal behavior is investigated at different C-rates and also contour plots of phase potential for both tabs and volume-monitored plot of maximum temperature inside the computational domain is illustrated. The numerical simulation is done via ANSYS Fluent traditional software package which utilizes the dual potential multi-scale multi-dimensional (MSMD) battery model to analyze the cell discharge behavior and investigate the thermal performance and potential variation(s). The results show that the maximum temperature of battery surface is proportional to the battery discharge rate, i.e., the higher the C-rate, the greater cell surface temperature. Moreover, an increasing symmetric pattern is noticed for volume monitor of maximum temperature over the simulation period. Finally, it is worth noting that the battery tab potential varies more quickly if the C-rate becomes greater. In fact, the lowest and highest rate of changes are observed for 1C and 4C, respectively.

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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.

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Adjustable throat-area expansion valves (ATAEV) are functioned as area regulator control units. In literatures, there are many expansion valves normally used in automotive air-conditioning systems, as regulator and electrical type valves. Nevertheless, a review study for such issue has not been introduced, according to the best of author knowledge. The present paper presents a review study for expansion valves used in air conditioning of automobiles. Different types of expansion valves are discussed including the working principles and the limitation of their working conditions.

 

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Hardware implementation of the Plug-in hybrid electric vehicles (PHEVs) control strategy is an important stage of the development of the vehicle electric control unit (ECU). This paper introduces Model-Based Design (MBD) approach for implementation of PHEV energy management. Based on this approach, implementation of the control algorithm on an electronic hardware is performed using automatic code generation. The advantages of the MBD in comparison with the traditional methods are the capability of eliminating the manual coding complexities as well as compiling problems and reducing the test duration. In this study, hardware implementation of a PHEV rule-based control strategy is accomplished using MBD method. Also, in order to increase the accuracy of the results of the implementation, the data packing method is used. In this method, by controlling the primer and end data of the data packet transferred between the electronic board and the computer system, the noisy data is prevented from entering. In addition, to verify the performance of the implemented control strategy, hardware-in-the-loop (HIL) simulation is used with the two frequency rates. The results show the effectiveness of the proposed approach in correct and rapid implantation procedure.

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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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As an effective means of displacing fossil fuel consumption and reducing greenhouse gas emissions, plug-in electric vehicles (PEVs) and plug-in hybrid electric vehicles (PHEVs) have attracted more and more attentions. From the power grid perspective, PHEVs and PEVs equipped with batteries can also be used as energy storage facilities, due to the fact that, these vehicles are parked most of the time. Since, the temperature has a strong influence on the battery life-time and also the inherent characteristics of PHEV/PEV energy storage systems limit their use as appropriate resources for energy tuning, this paper, at first, presents a detailed model for energy storage systems of PEVs considering the cooling system and set temperature, and then, it proposes a reliable energy management method for scheduling of PEVs in the multi-microgrid (MMG) systems for both faulted and normal operations using parametric multi-objective function. The simulation results indicate that, considering proper energy management of energy storage systems of PEVs has significant influence on energy scheduling of MMG systems. For this investigation, all data analysis and simulations were done and implemented in MATLAB/Simulink environment.

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Reactivity control compression ignition (RCCI) engines have demonstrated high-efficient and clean combustion but still suffer from ringing operation at upper load and production of unburned hydrocarbon (uHC) and carbon monoxide (CO) emissions at lower load. In this study, statistical analysis and experimental testing were conducted to consider the effects of input parameters such as intake temperature (T_in), equivalent ratio (Φ) and engine speed on emissions, combustion noise and performance of a 0.5 liter RCCI engine using response surface method (RSM) with the aim to minimize emissions and combustion noise and to maximize parameters of performance. The developed models for measured responses like uHC, CO, nitrogen oxides (NOx) and calculated responses such as indicated mean effective pressure (IMEP) and combustion noise level (CNL) were statistically considered to be significant by analysis of variance (ANOVA). Interactive effects between Tin, Φ and engine speed for all operating points were analyzed by 3-D response surface plots. The results from this study indicated that at optimum input parameters, the values of uHC, CO, NOx, IMEP and CNL were found to be 90.3 (ppm), 106.8 (ppm), 248.2 (ppm), 11.7 (bar) and 87 (db), respectively. The models were validated by confirmatory tests, indicating the error in prediction less than 5%.