Showing 5 results for Fuzzy Controller
Gh.h Payeganeh, M. Esfahanian, S. Pakdel Bonab,
Volume 4, Issue 2 (6-2014)
Abstract
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.
Mohsen Esfahanian, Mohammad Saadat, Parisa Karami,
Volume 8, Issue 3 (9-2018)
Abstract
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.
Abbas Harifi, Farzan Rashidi, Fardad Vakilipoor Takaloo ,
Volume 10, Issue 1 (3-2020)
Abstract
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.
Mr Mohamadreza Satvati, Dr Abdolah Amirkhani, Dr Masoud Masih-Tehrani, Mr Vahid Nourbakhsh,
Volume 11, Issue 4 (12-2021)
Abstract
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.
Mr. Hosein Hamidi Rad, Prof. Mohsen Esfahanian, Prof. Saeed Behbahani,
Volume 13, Issue 3 (9-2023)
Abstract
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.
