Automotive Science and Engineering

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In this paper, an adaptive rule based controller for an anti-lock regenerative braking system (ARBS) of a series hybrid electric bus (SHEB) has been proposed. The proposed controller integrates the regenerative braking and wheel anti-lock functions by controlling the electric motor of the hybrid vehicle, without using any conventional mechanical anti-lock braking system. The performance of the proposed system is evaluated by a comprehensive vehicle dynamics model in MATLAB/Simulink. Using the designed ARBS, the braking and regenerative performances of SHEB have significantly improved in slippery roads while the slip ratios are kept between 0.15 and 0.20.

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Hybrid Electric Vehicles (HEVs) are driven by two energy convertors, i.e., an Internal Combustion (IC) engine and an electric machine. To make powertrain of HEV as efficient as possible, proper management of the energy elements is essential. This task is completed by HEV controller, which splits power between the IC engine and Electric Motor (EM). In this paper, a Genetic-Fuzzy control strategy is employed to control the powertrain. Genetic-Fuzzy algorithm is a method in which parameters of a Fuzzy Logic Controller (FLC) are tuned by Genetic algorithm. The main target of control is to minimize two competing objectives, consisting of energy cost and emissions, simultaneously. In addition, a new method to consider variations of Battery State of Charge (SOC) in the optimization algorithm is proposed. The controller performances are verified over Urban Dinamometer Driving Cycle (UDDS) and New Europian Driving Cycle (NEDC). The results demonstrate the effectiveness of the proposed method in reducing energy cost and emissions without sacrificing vehicle performance.

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In the present study, a model of a large Lithium Polymer (Li-Po) battery for use in the simulation of Hybrid Electric Vehicles (HEVs) is developed. To attain this goal, an Equivalent Circuit (EC) consisting of a series resistor and two RC parallel networks is considered. The accuracy and the response time of the model for use in an HEV simulator are studied. The battery parameters identification and model validation tests are performed in low current with a good accuracy. Similar test process is implemented in high current for another cell and the simulation is verified with experimental results. The validation tests confirm the accuracy of the model for use in HEV simulator. Finally, the battery model is used to model a Vehicle, Fuel and Environment Research Institute (VFERI) hybrid electric city bus using ADVISOR software and its compatibility with other components of the vehicle simulator are demonstrated in a drive cycle test.

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Many studies have been done on hybrid vehicles in the past few years. The full hybrid vehicles need a large number of batteries creating up to 300 (V) to meet the required voltage of electric motor. The size and weight of the batteries cause some problems. This research investigates the mild hybrid vehicle. This vehicle includes a small electric motor and a high power internal combustion engine. In most cases the car’s driving force is created by an internal combustion part. A small electric motor, which can operate as engine starter, generator and traction motor, is located between the engine and an automatically shifted multi-gear transmission (gearbox). The clutch is used to disconnect the gearbox from the engine when needed such as during gear shifting and low vehicle speed. The power rating of the electric motor may be in the range of about 15% of the IC engine power rating. The electric motor can be smoothly controlled to operate at any speed and torque, thus, isolation between the electric motor and transmission is not necessary. The present study evaluates the properties of the mild hybrid vehicle, its structure and performance and proposes an energy control model for its optimum operation.

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Electric vehicles (EVs) have gained the attention of many authorities, automakers and researchers due to their considerable energy saving and emission reduction. One of the main issues that must be considered in design of a road vehicle is the calculation of aerodynamic forces. This issue also must be scrutinized in the design of EVs. Installation of rear spoiler is one of the solutions proposed for reduction of aerodynamic drag in racing cars and consequently increasing their maximum speed. This study focuses on the effects of installing a rear spoiler on an EV. The vehicle's drag and lift coefficients are determined by solving a 3D steady-state incompressible solution of Navier-Stokes equations with computational fluid dynamic (CFD) analysis in ANSYS FLUENT. In order to verify the effects of installing a rear spoiler on an EV, all the components were modelled in MATLAB /SIMULINK also, practical tests were performed to confirm and verify the simulation results. The results show that installing a rear spoiler on an EV, not only improves the aerodynamic characteristics of vehicle but also improves operating efficiency of electric motor and some operational aspects of batteries. In addition, it is shown that an EV with a rear spoiler is able to travel more in comparison with an EV without rear spoiler.

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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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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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With respect to the limitations of fossil energy resources, different types of electric vehicles (EVs) are developed as suitable alternatives. Lithium-ion (Li-ion) battery cells play an extremely important role in EVs due to their unique features. But they need a thermal management system (TMS) to maintain their surface temperature uniformity and avoid them from thermal runaways. In the current study a phase change material (PCM) based TMS is introduced and applied to provide a uniform temperature distribution on a Li-ion battery cell surface. This PCM based TMS declines the final maximum temperature difference to (1/5) and (2/3) at 1 C and 2 C discharge rate respectively.
 

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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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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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In this paper an idea for hybridization of conventional vehicles has proposed. The case study performed on one of the common vehicles on country roads i.e. Samand. This vehicle has high production volume but low fuel performance therefore hybridization of it could be attractive for its manufacture. This paper aims that the hybridization idea and its structure to need minimum mechanical modifications. In consequence attractiveness of this idea for industry could be high. A cost optimization has been performed for sizing of additional components such as electric motors and battery modules and the simulation results has been adopted to verify the proposed idea for case study with hybrid simulation of GT-Suit and MATLAB softwares.      

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Nowadays, with increasing environmental pollution and damages that threaten the health of the community, a lot of research is being conducted on reducing the emission from transportation sector as one of the main sources of total worldwide emissions. It is confirmed that one of the ways to reduce emission is to switch from fossil-based fuels to more environmentally benign fuels. Among the options, electric vehicles (EVs) have proven themselves as one of the best options. In this research study, a solar-based EV which is developed and built at University of Tehran is studied.  The environmental impacts assessment along with the energy consumption of this solar-electric vehicle is investigated

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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 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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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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Electric vehicles are attaining significant attention recently and the current legislation is forcing the automotive industry to electrify the productions. Regardless of electric energy accumulation technology, drive technology is one of the vital components of EVs. The motor drive technology has been mainly developed based on the application which required position/velocity control. In automotive application, however, torque control is an important aspect since the drivers have already used to drive the vehicle based on torque control approach in traditional powertrain system. In this article, a model-based approach is employed to develop a controller which can guarantee the precise control of the induction motors torque for a micro electric vehicle (EV) application regardless of operating conditions. The implementation of the control drive was conducted in MATLAB/Simulink environment, followed by Model In the Loop simulation and testing at various test conditions to confirm the robustness of the developed drive. Direct Torque Control (DTC) with optimum voltage vector selection method is employed to control the motor torque that requires fewer power electronics to process its operation and hence lowers the cost of implementation. The result shows the practicality of the designed control system and its ability to track reference torque commands. Vitally, the controlled approach shows fair abilities to control IMs to produce torque at both the motoring and regenerative modes which is a highly important requirement in electrical propulsion powertrains. Furthermore, the controller’s response time was within the industrial standard range which confirms its suitability for industrial implementation at low cost.

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In recent years, the automotive industry has experienced a dramatic mutation in the develop ment of electric vehicles. One of the most important aspects of this type of vehicle is its thermal management. Among the various parts of an electric vehicle that are subjected to thermal management, the battery is of particular importance. Battery cell temperatures may exceed the allowable range due to continuous and high-pressure operation and various weather conditions, and this, in addition to performance, severely affects battery life. Therefore, the appropriate cooling system is essential. In this research, the most common methods of battery cooling are investigated. First, three-dimensional thermal analysis on the battery is performed using the computational fluid dynamics method in transient and steady-state phases.  Then, the effect of changing the cooling flow rate on the maximum temperature of the battery cell as well as the temperature difference of the cells in the battery pack is investigated. The effect of changing inlet coolant temperature change on battery cell temperature distribution is also investigated. The results show that by increasing the flow rate from 0.5 to 1.2 liter per minute, the maximum temperature in the battery pack and the temperature difference between the cells decrease to 44.4 and 2.51 ° C, respectively. Also, by changing the temperature of the inlet coolant from 15 to 30 ° C, the maximum temperature in the battery pack increases up to 42.2 ° C and the temperature difference is negligible.

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The hydrogen fuel cell is one of the latest technologies used in fuel cell electric vehicles (FCEVs), which uses hydrogen gas to supply the electrical energy needed by the electric engines. The proposed topology has boost function and uses a novel diodes and switches network, which leads to the creation of an integrated system with high efficiency and high voltage gain. Other advantages of the proposed converter are small size, low voltage and current stresses on all the components, less component count, continuous input current and light weight; which makes it more efficient compared to existing structures. In this regard, theoretical calculations and steady state analysis for the proposed system have been presented. Also, in order to verify the performance of the proposed converter, it has been simulated in the MATLAB/Simulink software environment at the rated power of 1kW, with an output voltage of 220V and an output current of 4.55A, and the results have been presented in detail. The peak efficiency of the proposed converter reached 97.4% at half power, and the efficiency at rated power was reported 96%. Moreover, in the proposed structure, the voltage stress of capacitors, diodes and switches reaches the maximum value of 63%, 83% and 41% of the output voltage, respectively; which are promising values. Finally, to verify the performance of the proposed converter and the relationships obtained, a 1kW prototype is built in the laboratory to demonstrate the efficiency of the proposed converter.