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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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.

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This research proposes a robust fuzzy adaptive fractional-order proportional-integral-derivative (PID) controller for an active suspension system of a quarter-car model. For this, the research first designed the PID controller using chassis acceleration and relative displacement. Next, it utilized the chain derivative rule and the gradient descent mechanism to formulate adaptation rules based on integral sliding surfaces. In the next step, the control parameters were regulated by employing a fuzzy system comprising the product inference engine, singleton fuzzifier, and center average defuzzifier. Eventually, the optimum gains of the proposed controller were determined by running a multi-objective material generation algorithm (MOMGA). Simulation results implied the superiority of the proposed controller over other controllers in handling road irregularities.

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Conventional suspension systems exhibit performance limitations when encountering road irregularities and specific surface profiles, often failing to attenuate road-induced disturbances effectively. This functional deficiency reduces ride comfort and compromises vehicle dynamic stability under various driving conditions. In contrast, active suspension systems, utilizing hydraulic or pneumatic actuators in combination with feedback control strategies, have demonstrated a significant potential for disturbance suppression and considerable improvement in ride comfort and vehicle stability. Previous studies have identified that vertical (bounce) and rotational (roll) motions are among the primary factors influencing passenger comfort and vehicle stability in dynamic scenarios. Therefore, controlling these motions is essential to enhance ride quality and handling performance. In this study, a half-car dynamic model equipped with an active suspension system is developed, focusing on controlling bounce and roll motions. All modeling and simulation tasks are conducted within the MATLAB environment, where two control strategies fuzzy control and optimal control are designed and implemented for the active suspension system. Finally, the dynamic performance of these two approaches is compared and analyzed. The simulation results indicate that the optimal control strategy outperforms the fuzzy control method regarding disturbance rejection and overall ride comfort and vehicle stability improvement.