Automotive Science and Engineering

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Nowadays, due to increasing the complexity of IC engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. Accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. In this paper four network based modeling methods are used and compared to model the behavior of an IC engine: neural networks model (NN), group method of data handling model (GMDH), a hybrid NN and GMDH model (NN-GMDH), and a GMDH model whose structure is determined by genetic algorithm (Genetic-GMDH). The inputs are engine speed, throttle angle, and intake valve opening and closing timing, and the output is the engine brake torque. Results show that NN has the best prediction capability and Genetic-GMDH model has the most flexible and simplest structure and relatively good prediction ability.

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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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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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To reduce the harmful effects of fuel based engines new technologies in automotive industries have introduced. Combination of novel ball continuously variable transmission and hybrid technologies with the advantages of optimum controlling of power sources in the vehicle are the main topic of this paper by preparing a model of transmission using GT-Suite software. In order to determine the operation and responses of the proposed transmission, different operational modes, along with different inputs in term of speed, torque and ratio are presented. This research successfully demonstrates a new type of transmission which is developed to enjoy the benefits of combining technologies in vehicle drivetrain that features high torque capacity and desirable drivability. Main achievement of this paper is to show the operational modes of this system as well as ability to mode alteration during vehicle operation. Various steady and transient modes are studied in this paper using multi body modeling and it shows HBCVT can eliminate most limitation of parallel hybrid systems.

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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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