Automotive Science and Engineering
Volume:5 Issue: 4, Autumn 2015

Due to the increasing development in various branches of the automotive industry, the need for a comfort climate in the cabin is more sensible. However, to achieve climate comfort, HVAC system consumes a considerable amount of engine power. Hence, improving HVAC system performance leads to more energy saving of the vehicle which is a critical factor for nowadays automotive. Besides, one crucial task of HVAC system is defrosting/defogging of windshield which is considered as a mandatory requirement in most countries. In the current study, the defrosting/defogging performance of HVAC system in the main product of national vehicle platform is numerically evaluated based on the ECE-78-715 legal requirement. For this purpose, after validation and mesh independency study, the transient air flow in three-dimensional cabin geometry is simulated by SSTk-ω turbulence model via ANSYS Fluent software and the windshield thermal condition is reported during defrosting/defogging. Besides, two national HVAC standards of AERC-10-01 and AERC-10-02 are also checked. The results demonstrate that HVAC system of the main product of the national vehicle platform can satisfactorily fulfill ECE-78-715, AERC-10-01 and AERC-10-02.

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method consists of three steps, firstly the six different base wavelets are considered. Out of these six wavelets, the base wavelet is selected based on wavelet selection criterion to extract statistical features from wavelet coefficients of raw vibration signals. Based on wavelet selection criterion, Daubechies wavelet and Meyer are selected as the best base wavelet among the other wavelets considered from the Maximum Relative Energy and Maximum Energy to Shannon Entropy criteria respectively. Finally, the gearbox faults are classified using these statistical features as input to LSSVM technique. The optimal decomposition level of wavelet is selected based on the Maximum Energy to Shannon Entropy ratio criteria. In addition to this, Energy and Shannon Entropy of the wavelet coefficients are used as two new features along with other statistical parameters as input of the classifier. Some kernel functions and multi kernel function as a new method are used with three strategies for multi classification of gearboxes. The results of fault classification demonstrate that the LSSVM identified the fault categories of gearbox more accurately with multi kernel and OAOT strategy.

In the present paper, the modal analysis on a full finite element model of an off-road vehicle. This vehicle was modeled in the CATIA software and then meshed in the HYPERMESH software. The free vibration analysis was conducted by the ABAQUS software. By applying an external displacement, the forced vibration analysis was also performed. As a result, natural frequencies and shape modes were extracted to detect critical regions. Then, some improvements were suggested to have better vibration behavior of the vehicle.

Electric vehicles (EVs) have gained the attention of many authorities, automakers and researchers due to their considerable energy saving and emission reduction. One of the main issues that must be considered in design of a road vehicle is the calculation of aerodynamic forces. This issue also must be scrutinized in the design of EVs. Installation of rear spoiler is one of the solutions proposed for reduction of aerodynamic drag in racing cars and consequently increasing their maximum speed. This study focuses on the effects of installing a rear spoiler on an EV. The vehicle's drag and lift coefficients are determined by solving a 3D steady-state incompressible solution of Navier-Stokes equations with computational fluid dynamic (CFD) analysis in ANSYS FLUENT. In order to verify the effects of installing a rear spoiler on an EV, all the components were modelled in MATLAB /SIMULINK also, practical tests were performed to confirm and verify the simulation results. The results show that installing a rear spoiler on an EV, not only improves the aerodynamic characteristics of vehicle but also improves operating efficiency of electric motor and some operational aspects of batteries. In addition, it is shown that an EV with a rear spoiler is able to travel more in comparison with an EV without rear spoiler.

Loading conditions and complex geometry have led the cylinder heads to become the most challenging parts of diesel engines. One of the most important durability problems in diesel engines is due to the cracks valves bridge area. The purpose of this study is a thermo-mechanical analysis of cylinder heads of diesel engines using a two-layer viscoplasticity model. In this article, mechanical properties of A356.0 alloy, obtained by tensile tests at 25 and 200°C. The results of the thermo-mechanical analysis indicated that the maximum temperature and stress occurred in the valves bridge. The results of the finite element analysis of cylinder heads correspond with the simulation results, carried out by researchers.