Search Results

This paper proposes a methodology for collision prevention in car following scenarios. For this purpose, Emotional Learning Fuzzy Inference System (ELFIS) approach is used to simulate and predict the behavior of a driver-vehicle-unit in a short time horizon ahead in the future. Velocity of the follower vehicle and relative distance between the follower and the lead vehicles are predicted in a parallel structure. Performance of the proposed algorithm is assessed using real traffic data and superior accuracy of this method is demonstrated through comparisons with another available technique (ANFIS). The predicted future driving states are then used to judge about safety of the current driving pattern. The algorithm is used to generate a warning message while a safe-distance keeping measure is violated in order to prevent a collision. Satisfactory performance of the proposed method is demonstrated through simulations using real traffic data.

The main purpose of this research is to tune the stiffness of engine mounts of a passenger car in order to reduce the transmitted vibration to driver with regard to the permissible values of natural frequencies of engine using DOE method. Based on the previous experiments, prevalent criteria are introduced by automakers which would lead the designer to optimum values of mountings' stiffness. In this paper we benefit the usage of experimental frequency bands introduced by the NVH authoritative references. To achieve this, we use a mixed Finite element and multi body dynamic modeling. The FEM model of the body front end and engine subframe is developed using Hypermesh. The engine block is modeled as a rigid body attached to the neighbor parts with rubber mounts. The modal natural file of the whole system is created by the aim of MSC/Nastran and exported to the ADAMS/View for further analysis.

Ride quality is one of the most fundamental properties of a vehicle, therefore this subject is always noticed by automotive engineers. A lot of researches have been done for improving vehicle ride performance but most of them centered on development of control systems such as active and semi active suspension systems. In this research, modification of suspension system parameters has been used for optimization of vehicle ride quality. For this reason, Virtual model of an off road car in ADAMS/Car has been developed. Several different experimental test results have confirmed the validity of the model. To reduce the number of input parameters of optimization, a sensitivity analysis has been performed based on design of experiments (DOE) method. Two level fractional factorial designs have been selected for this purpose. The sensitivity analysis indicated that five parameters from fifteen selected parameters play major roles.

Currently, the interest in using alternative clean types of fuels has been extensively increased all over the world because of the global approach in reducing engine emissions and creating new sources of fuel for internal combustion engines. The hydrogen-methane blend is one of the alternative fuels which includes the benefits of both of the fuels compared to the traditional petrol/gasoline fuel. This paper addresses a two-zone quasi-dimensional model to investigate the performance of an SI engine which uses a mixture of methane and hydrogen. In this model, gases inside the cylinder are divided into two regions: burned and the unburned. The chemical reactions are supposed to be in equilibrium in each zone, but the extended Zedlovich mechanism is utilized to determine the amount of the NOx available in the exhaust gas. Also, CO concentration is determined by two steps kinematic reactions. The flame front is assumed to be a surface with no thickness in adiabatic flame temperature.