Automotive Science and Engineering

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In this paper, the enhancement of vehicle stability and handling is investigated by control of the active geometry suspension system (AGS). This system could be changed through control of suspension mounting point’s position in the perpendicular direction to wishbone therefore the dynamic is alternative and characteristics need to change. For this purpose, suitable controller needs to change mounting point’s position in limit area. Adaptive fuzzy control able to adjust stability and handling characteristics in all conditions. Also, simple controller such as proportional-integral-derivative (PID) versus adaptive fuzzy have been used that submit intelligent controllers. The three of freedom model (3DOF) in vehicle handling is validated with MATLAB and CarSim software. The results show that the steady state response of the adaptive fuzzy controller has been closed to desired yaw and roll angle has been enhanced about %20. In cases of lateral velocity and side slip angle have the same condition that it shows the stability has been improved. The control effort of PID needs to change very high that this response is not good physically, while control effort in adaptive fuzzy is less than 50 mm.

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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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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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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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    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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This paper experimentally investigates the trafficability of a small tracked vehicle on a slope. An increase in the angle of slope inclination may divert the vehicle from its path. In other words, the deviation of the vehicle is due to a sudden increase in the yaw angle. Also, the tip-over occurs at a specific slope angle. The locomotion of the small tracked vehicle on soils with different terramechanics (such as cohesion, internal friction angle, cohesive modulus, and friction modulus) is also simulated to evaluate its slope-traversing performance. Moreover, the impact of velocity and soil type on traversing a slope is measured. The proposed yaw angle control system is modeled for controlling the yaw angle of the tracked vehicle. This controller is designed through co-simulation. It keeps the tracked vehicle at zero yaw angle to achieve straight locomotion on slopes. It is compared to the PI, PID, and fuzzy controllers. The response of this controller is faster than PI and PID controllers. A Comparison between fuzzy and proposed yaw angle controller yields almost similar responses. The mechanism of the proposed yaw angle controller is also easier to understand. The precision of the controller's performance is measured by simulating over different terrains.

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Environmental pollution and reduction of fossil fuel resources can be considered as the most important challenges for human society in the recent years. The results of previous studies show that the main consumer of fossil fuels and, consequently, most of the air pollutants, is related to the transportation industry and especially cars. The increasing growth of vehicles, the increase in traffic and the decrease in the average speed of inner-city vehicles have led to a sharp increase in fuel consumption. To address this problem, automakers have proposed the development and commercialization of hybrid vehicles as an alternative to internal combustion vehicles. In this paper, the design of an energy management system in a fuel-cell hybrid vehicle based on the look-ahead fuzzy control is considered. The preparation of fuzzy rules and the design of membership functions is based on the fuel efficiency curve of the fuel-cell. In look-ahead fuzzy control, the ahead conditions of the vehicle are the basis for decision in terms of slope and speed limit due to path curves as well as battery charge level. The fuzzy controller will determine the on or off status of the fuel-cell, as well as the power required. The motion of the fuel-cell hybrid vehicle on a real road is simulated and the performance of the proposed look-ahead controller is compared with the base controller (thermostatic method). The simulation results show that using the proposed approach can reduce the fuel consumption of the fuel-cell hybrid vehicle as well as travel time.

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This study examines the impact of a fuzzy logic-based control strategy on managing peak power consumption in the auxiliary power unit (APU) of a hybrid electric bus. The APU comprises three components: an air compressor, a power steering system, and an air conditioning system (AC) connected to an electric motor. Initially, these components were simulated in MATLAB-SIMULINK software. While the first two were deemed dependent and independent of vehicle speed, respectively, the stochastic behavior of the steering was emulated using the Monte Carlo method. Subsequently, a fuzzy controller was designed and incorporated into the APU to prevent simultaneous operation of the three accessories as much as possible. The results of repeated simulations demonstrated that the designed fuzzy controller effectively distributed the operation of the accessories throughout the driving cycle, thereby reducing overlaps in auxiliary loads. Consequently, the APU's average and maximum power consumption exhibited significant reductions. Furthermore, through multiple simulations with an upgraded power system model integrating the new APU-controller package, it was established that the proposed strategy for managing auxiliary loads in the bus led to lower fuel consumption and emissions.