Automotive Science and Engineering

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In this paper, the development and optimization of Power Distribution Control Strategy (PDCS) have been performed for a Hybrid Energy Storage Systems (HESS) of a Series Hybrid Electric Bus (SHEB). A common PDCS is based on the use of Ultra-Capacitor (UC) pack. A new simple PDCS is developed as a battery based one. For the battery based PDCS, four parameters are introduced for tuning the PDCS performance. The Design of Experiment (DoE) method is utilized to optimize the parameters of the battery based PDCS for the driving cycles and the vehicle controllers. The results show the optimized battery based PDCS performance for some cases are better than the UC based PDCS performance. Vice versa, for some cases the performance of the UC based PDCS is better than the battery based PDCS. Finally, the costs rising from the HESS (about 66%) is reasonable when considering the over double increase in the battery life-time when using an appropriate PDCS.

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In the present paper, the idea of braking energy regeneration and reusing that energy during acceleration for a refuse truck is comprehended. According to their driving cycle, the refuse trucks have a good potential for braking energy regeneration. On the other hand, hydraulic hybrid is a powertrain with high power density which is appropriate for energy regeneration. In the primary stage of this issue, the hydraulic hybrid propulsion system is designed with intention of regenerating the maximum possible kinetic energy during the refuse truck braking mode. At this stage, a non-fuzzy rule-based control strategy is applied to manage the energy flow in the hybrid powertrain. After that, the powertrain of the Axor 1828 truck and the elements of the hydraulic powertrain are modeled in MATLAB/Simulink. The modeling is performed considering the efficiencies of the powertrain elements. In the last part of the paper, a fuzzy control strategy is designed and modeled to improve the fuel consumption of the truck with hybrid powertrain. In order to see the usefulness of the designed hybrid powertrain, several simulations are organized on the vehicle model in Simulink. The driving cycle for refuse truck in Tehran is used for performing the simulations. The results state indicated that using the hydraulic hybrid powertrain decreased the fuel consumption of the refuse truck by 7 percent. In addition, this amount of reduction was improved by implementing the fuzzy control strategy. The decrease in fuel consumption was due to the regenerating of the braking energy up to 50 percent.

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Direct Yaw moment Control systems (DYC) can maintain the vehicle in the driver’s desired path by distributing the asymmetric longitudinal forces and the generation of the Control Yaw Moment (CYM). In order to achieve the superior control performance, intelligent usage of lateral forces is also required. The lateral wheel forces have an indirect effect on the CYM and based upon their directions, increase or decrease the amount of CYM magnitude. In this paper, a systematic and applicable algorithm is proposed to use the lateral force in the process of Yaw controlling optimally. The control systems are designed based on the proposed algorithm. This system includes Yaw rate controller and wheel slip controllers which are installed separately for each wheel. Both of the mentioned control systems are designed on the basis of the Fuzzy logic. Finally, the capabilities of the proposed control systems are evaluated in a four wheel drive vehicle, for which, the traction of each wheel can be controlled individually. It is shown that considering the lateral force effect offers significant improvement of the desired yaw rate tracking

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In this paper, a numerical study is performed to provide the combustion and emission characteristics resulting from fuel-reactivity controlled compression ignition (RCCI) combustion mode in a heavy-duty, single-cylinder diesel engine with gasoline and diesel fuels. In RCCI strategy in-cylinder fuel blending is used to develop fuel reactivity gradients in the combustion chamber that result in a broad combustion event and reduced pressure rise rates (PRR). RCCI has been demonstrated to yield low NOx and soot with high thermal efficiency in light and heavy-duty engines. KIVA-CHEMKIN code with a reduced primary reference fuel (PRF) mechanism are implemented to study injection timings of high reactivity fuel (i.e., diesel) and low reactivity fuel percentages (i.e., gasoline) at a constant engine speed of 1300 rpm and medium load of 9 bar indicated mean effective pressure (IMEP). Significant reduction in nitrogen oxide (NOx), while 49% gross indicated efficiency (GIE) were achieved successfully through the RCCI combustion mode. The parametric study of the RCCI combustion mode revealed that the peak cylinder pressure rise rate (PPRR) of the RCCI combustion mode could be controlled by several physical parameters – PRF number, and start of injection (SOI) timing of directly injected fuel.

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In recent years, need to increase the convenience of trips in railway vehicles causes that train operators and manufacturers focus on reducing the noise level which is sensed by passengers. In this paper, first the state of modeling acoustic noise in cab train is discussed and natural frequencies and acoustic mode shapes are derived and then formulation of acoustic pressure in the cab will be obtained. By utilizing field testing, the noise produced by diesel engine in the cabin of Pardistranset train (source of undesirable noise), has been measured and is used in simulating. In order to reduce the acoustic pressure, a secondary noise source is used which its Stimulation signal is obtained by phased PID controller. Then, active noise control will be investigated in two cases of single-channel and multi-channel. The result of actuating the controller shows that in central frequencies of one octave band, there is a reduction in the sound pressure level, loudness, and sound loudness level.

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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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Nowadays, the use of small vehicles is spreading among urban areas and one sort of these vehicles are three-wheeled vehicles (TWVs) which can be competitive with four-wheeled urban vehicles (FWVs) in aspects such as smallness, simple manufacturing, and low tire rolling resistance, fuel consumption and so on. The most critical instability associated with TWVs is the roll over. In this paper a tilt control mechanism has been modeled which can reduce the danger of roll over by leaning the vehicle towards the turning center in order to decrease the amount of lateral load transfer (LLT), and by doing so, system combines the dynamical abilities of a passenger car with a motorcycle. A 3 degree of freedom vehicle model is simulated at constant speed in MATLAB-Simulink environment and a fuzzy algorithm is developed to control such a non-linear system with appropriate tilting torque. Results are interpreted in presence and absence of controller with different longitudinal speeds and steering inputs the results are also compared to behavior of a similar FWV and this is concluded that the tilt control system could countervail deficiencies of the TWV compared to the FWV.

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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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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.

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In this article, vehicle cornering stability and brake stabilization via bifurcation analysis has been investigated. In order to extract the governing equations of motion, a nonlinear four-wheeled vehicle model with two degrees of freedom has been developed. Using the continuation software package MatCont a stability analysis based on phase plane analysis and bifurcation of equilibrium is performed and an optimal controller has been proposed. Finally, simulation has been done in Matlab-Simulink software considering a sine with dwell steering angle input, and the effectiveness of the proposed controller on the aforementioned model has been validated with Carsim model.

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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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Accurate and correct performance of controller in cruise control systems is important. Hence, in such systems, controller should optimize itself against noise and probable changes in system dynamic. As a matter of fact, in this article three approaches have been conducted to-ward this purpose: MIT, direct estimation and indirect estimation. These approaches are used as controllers to track reference signal. First the performance of each of these three controllers is checked. comparison of performances indicated better behavior for indirect estimation than others. Also, it has less sensitivity against external noise. Finally, by using indirect estimation method as an adaptive control approach, two parallel separate controllers are designed for two inputs, gas and braking, and their performances are compared with recent studies. It shows improvement in performance of adaptive cruise control system to track reference signal.

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The electronic stability control (ESC) system is one of the most important active safety systems in vehicles. Here, we intend to improve the Electronic stability of four in-wheel motor drive electric vehicles. We will design an electronic stability control system based on Type-2 fuzzy logic controller. Since, Type-2 fuzzy controller has uncertainty in input interval furthermore of output fuzziness, it behaves like a robust control, hence it is suitable for control of nonlinear uncertain systems which uncertainty may be due to parameter variation or un-modeled dynamics. The controller output for stabilization of vehicle is corrective yaw moment. Controller output is the torque that distribute by braking and acceleration on both sides of the vehicle. We simulate our designs on MATLAB software. Some drive maneuvers will be carry to validate system performance in vehicle stability maintenance. Simulation results indicate that distributed torque-brake control strategy based on Type-2 fuzzy logic controller can improve the stability and maneuverability of vehicle, significantly in comparison with uncontrolled vehicle and Type-1 fuzzy ESC. Furthermore, we compare the conventional braking ESC with our designed ESC, i.e. distributed exertion of torque ESC and braking ESC in view point of both stabilization and performance. As we will see, proposed ESC can decrease vehicle speed reduction, in addition to better vehicle stability maintenance.

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Hybrid electric vehicles employ a hydraulic braking system and a regenerative braking system together to provide enhanced braking performance and energy regeneration. In this paper an integrated braking system is proposed for an electric hybrid vehicle that include a hydraulic braking system and a regenerative braking system which is functionally connected to an electric traction motor. In the proposed system, four independent anti-lock fuzzy controllers are developed to adjust the hydraulic braking torque in front and rear wheels. Also, an antiskid controller is applied to adjust the regenerative braking torque dynamically.  A supervisory controller, is responsible for the management of this system.  The proposed integrated braking system is simulated in different driving cycles. Fuzzy rules and membership functions are optimized considering the objective functions as SoC and slip coefficient in various road conditions. The simulation results show that the fuel consumption and the energy loss in the braking is reduced. In the other hand, this energy is regenerated and stored in the batteries, especially in the urban cycles with high start/stop frequency. The slip ratio remains close to the desired value and the slip will not occur in the whole driving cycle. Therefore, the proposed integrated braking system can be considered as a safe, anti-lock and regenerative braking system.
 

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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 cruise control systems, the performance of the controller is important. Hence, in order to have accurate results, the nonlinear behavior of a vehicle model should also be considered. In this article, a vehicle with a nonlinear model is controlled by using a nonlinear method. The nonlinear term of the model is the generated torque of engine, which is a polynomial equation. In addition, feedback linearization is used as a nonlinear method in order to design two parallel controllers to control the movement of the vehicle. These two parallel controllers are used to control braking and gas pedals which are in charge of the angular velocity of the wheels. To check the performances of controllers, first, each controller is used separately. Finally, two parallel controllers are used to track the reference signal. Comparison between results shows that the designed controller is able to reduce the convergence time of about 10 seconds. This improvement is near 35% in comparison with near studies. In addition, it can reduce the error between the velocity of the vehicle and the values of the reference signal that results in more safety for passengers.

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    Modeling and identification of the system of Iranian cars is one of the most basic needs of automotive and consumer groups and has a broad role for safe driving. It has happened with speed increasing or changing of shift gear, effects on water temperature or the car's torque has been observed, but how much and how intensely and with what algorithm this effect is identifiable, can be modeled and controlled, because up to now an algorithm that can show these effects during driving has not existed that what reaction should be made by the vehicle when it occurs untimely.
    Identification of each automobile sector lonely has been considered in recent decades, and in some cases, some relationships have been investigated, but from a control point of view, the lack of comprehensive effects of all parts of a car on the other parts is to get an identification algorithm in the automotive industry, and it requires more in-depth studies, because the complexity of the behavior of different parts of the car has made many attempts not fully understandable. Hear it's supposed to control different parameters of Iranian vehicles by using LS estimation and fuzzy logic controller and the simulation is done in Matlab software by storing and validating data of a Dena vehicle through CAN network.

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The control of Antilock Braking Systems (ABS) is a difficult problem, because of their nonlinearities and uncertainties appearing in their dynamics and parameters. To overcome these issues, this paper proposes a new adaptive controller for the next generation of ABS. After considering a complex vehicle dynamic, a triple adaptive fuzzy control system is presented. Important parameters of the vehicle dynamic include two separated brake torques for front ands rear wheels, as well as longitudinal weight transfer which is caused by the acceleration or deceleration. Because of the nonlinearity of the vehicle dynamic model, three fuzzy-estimators have been suggested to eliminate nonlinear terms of the front and rear wheels’ dynamic. Since the vehicle model parameters change due to variations of road conditions, an adaptive law of the controller is derived based on Lyapunov theory to adapt the fuzzy-estimators and stabilize the entire system. The performance of the proposed controller is evaluated by some simulations on the ABS system. The results demonstrate the effectiveness of the proposed method for ABS under different road conditions.

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Due to the increasing level of air pollution and the reduction of fossil fuels, the need for new technologies and alternative fuels is felt more than ever. Proton exchange membrane fuel cells (PEMFCs) are one of these technologies, which have been of great interest to the researchers due to the benefits of non-contamination, high efficiency, fast start-up, and high power density. The proper functioning of the fuel cell requires thermal management and water management within the cells. To this end, in this work, the effect of different parameters on the performance of PEM fuel cell was investigated. The results demonstrated that the performance of the cell increases with increasing the pressure in the low current densities, while in the high current density, performance decreases with increasing the pressure of the cell. Also, the study of the effect of relative humidity shows that increasing the relative humidity of the cathode does not have much effect on the performance of the cell while increasing the relative humidity of the anode improves the performance of the cell.