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Error in suspension asymmetry or tire parameters may lead to vehicle drifting laterally from its intended straight-line path, which is called vehicle pull. Driver then needs to apply constant steering correction to maintain the vehicle in straight line which will lead to high driver fatigue and deteriorate driving experience. Manufacturing a perfectly symmetric suspension system is impractical, however an insight into the manufacturing tolerances of suspension system at the early design stage can be extremely useful. Also tire force and moment parameters at straight line operation and its maximum allowable variations will help in defining the tire parameter specifications and tolerances. The objective of this study was to develop a 1D model of suspension and tire system which can predict the torque experienced in steering and drift of the vehicle from straight line due to the tire force and moment and asymmetric suspension geometry.

Authors were challenged with a task of developing a full vehicle simulation model, with a target to simulate the electrical system performance and perform digital tests like Battery Charge Balance, in addition to the fuel efficiency estimation. A vehicle is a complicated problem or domain to model, due to the complexities of subsystems. Even more difficult task is to have a control algorithm which controls the vehicle model with the required control signals to follow the test specification. Particularly, simulating the control of a vehicle with a manual transmission is complicated due to many associated control signals (Throttle, Brake and Clutch) and interruptions like gear changes. In this paper, the development of a full vehicle model aimed at the assessment of electrical system performance of the vehicle is discussed in brief.

Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS). IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities.

Computer Aided Engineering (CAE) plays an important role in the product development. Now a days major decisions like concept selection and design sign off are taken based on CAE. All the Original Equipment Manufacturers (OEMs) are putting consistent efforts to improve accuracy of the CAE results. In recent years confidence on CAE prediction has been increased mainly because of good correlation of CAE predictions with the test results. Defining proper correlation criteria and using a systematic approach helps significantly in building the overall confidence level for predictions given by CAE simulations. Representation of manufacturing effects on material properties and material failure in the simulation is still a big challenge for achieving a good CAE correlation. This paper describes side impact test vs CAE correlation. The important parameters affecting the CAE correlation were discussed.

Structural adhesive is a good alternative to provide required strength at joinery of similar and dissimilar materials. Adhesive joinery plays a critical role to maintain structural integrity during vehicle crash scenario. Robust adhesive failure definitions are critical for accurate predictions of structural performance in crash Computer Aided Engineering (CAE) simulations. In this paper, structural adhesive material characterization challenges like comprehensive In-house testing and CAE correlation aspects are discussed. Considering the crash loading complexity, test plan is devised for identification of strength and failure characteristics at 0°, 45°, 75°, 90°, and Peel loading conditions. Coupon level test samples were prepared with high temperature curing of structural adhesive along with metal panels. Test fixtures were prepared to carryout testing using Instron VHS machine under quasi-static and dynamic loading.

Battery Thermal management is a major challenge for occupant safety in an electric vehicle. Predicting the battery electrical losses and thermal behaviour is another challenge for the battery management system. Different virtual models are developed for cell level and pack level thermal evaluation. All these models have a varying degree of accuracy and limitation. The latest developed model is more accurate and can predict the battery cell & pack level temperatures. The battery can be modeled in different ways, ECM (Electrochemical model), EIS (Electrochemical Impedance Spectroscopy) [1]. Newman model is a well-known electrochemical model. [2]. EIS uses a combination of DC and small AC signal [3,4]. ECM model also used for estimating SOC and in BMS [5]. The cell temperature in the battery pack not only depends upon the cell inside physics but also depends upon cell outside cooling physics. Cell outside physics is simulated by 3D CFD software during the design process [6].

Automotive window buffeting is a source of vehicle occupant’s discomfort and annoyance. Original equipment manufacturers (OEM) are using both experimental and numerical methods to address this issue. With major advances in computational power and numerical modelling, it is now possible to model complex aero acoustic problems using numerical tools like CFD. Although the direct turbulence model LES is preferred to simulate aero-acoustic problems, it is computationally expensive for many industrial applications. Hybrid turbulence models can be used to model aero acoustic problems for industrial applications. In this paper, the numerical modelling of side window buffeting in a generic passenger car is presented. The numerical modelling is performed with the hybrid turbulence model Scale Adaptive Simulation (SAS) using a commercial CFD code.

Engine Stop/Start System (ESS) promises to reduce greenhouse emissions and improve fuel economy of vehicles. Previous work of the Authors was concentrated on bridging the gap of improvement in fuel economy promised by ESS under standard laboratory conditions and actual driving conditions. Findings from the practical studies lead to a conclusion that ESS is not so popular among the customers, due to the complexities of the system operation and poor integration of the system design with the driver behavior. In addition, due to various functional safety requirements, and traffic conditions, actual benefits of ESS are reduced. A modified control algorithm was proposed and proven for the local driving conditions in India. The ways in which a given driver behaves on the controls of the vehicles like Clutch and Brake Pedals, Gear Shift Lever were not uniform across the demography of study and varied significantly.

With the current state of ever rising fuel prices and unavailability of affordable alternate technologies, significant research and development efforts have been invested in recent times towards improving fuel efficiency of vehicles powered with conventional internal combustion engines. To achieve this, a varied approach has been adopted by researchers to cover the entire energy chain including fuel quality, combustion quality, power generation efficiency, down-sizing, power consumption efficiency, etc. Apart from energy generation, distribution and consumption, another domain that has been subjected to significant scrutiny is energy recuperation or recovery. A moving vehicle and a running engine provide a number of opportunities for useful back-recovery and storage of energy. The most significant sources for recuperation are the kinetic energy of the moving vehicle or running engine and to a lesser extent the thermal energy from medium such as exhaust gas.

Structural optimization has evolved vastly based on the development of computational based analysis – CAE. Structural optimization is usually a linear static response optimization because nonlinear response structural optimization is very expensive to perform. But in the real world, most of the automobile load cases are non-linear in nature. Equivalent static load structural optimization is a structural optimization method where Equivalent Static Loads (ESLs) are utilized as external loads for linear static response optimization. ESL is defined as the static load that generates the similar displacement by an analysis which is not linear static. This paper explains the development of a weight optimized BIW structure from an already existing model satisfying the NVH and Crash requirements. Basic structural crash loads are converted into ESLs with appropriate constraints.

The performance of door assembly is very significant for the vehicle design and door sag/set is one of the important attribute for design of door assembly. This paper provides an overview of conventional approach for door sag/set study based on door-hinge-BIW assembly (system level approach) and its limitation over new approach based on subassembly (subsystem level approach). The door sag/set simulation at system level is the most common approach adopted across auto industry. This approach evaluates only structural adequacy of door assembly system for sag load. To find key contributor for door sagging is always been time consuming task with conventional approach thus there is a delay in providing design enablers to meet the design target. New approach of door sag/set at “subsystem level” evaluates the structural stiffness contribution of individual subsystem. It support for setting up the target at subsystem level, which integrate and regulate the system level performance.

This paper describes the Common Automobile Program (CAP) that can be implemented to improve mass transportation. CAP is the use of automated electric vehicles using smart navigation and control technologies to improve mass transportation. In CAP, common vehicles are used by different passengers, thus, reducing the on-road traffic and also the parking space required. Various low-cost stations are to be built along specified paths and the vehicle can be used at the convenience of the commuter. Currently, buses and trains require the passengers to wait at the station and a significant amount of time is spent at intermediate stops. The vehicle in CAP runs directly from origin to destination and also eliminates the waiting time at stations. Passengers do not wait for vehicles; instead vehicles wait for the passengers. The journey starts as the passenger enters the station and selects the destination.

Conventionally, the automotive outer panels, giving vehicle its shape, have been manufactured from steel sheets. The outer panels are subjected to loads due to wind loading, palm-prints, person leaning on the vehicle, cart hits, and hail stones for example. Consumer awareness about these two panel characteristics: Oilcanning and Dent resistance is increased, which has been observed in recent marketing studies. Apart from perceptive quality, another factor depending on the dent performance is insurance and respective cost implications. Dents can occur due to several reasons such as object hits, parking misjudgement, hail stones etc. Phenomenon can be divided into two types, static and dynamic denting. Static dent case covers scenario wherein interaction with outer panel is mostly quasi-static. Hail stones present dynamic case where object hits a panel with certain kinetic energy. Automotive companies usually perform static dent assessment to cover all the cases.

Automakers are being subjected to increasingly strict fuel economy requirements which led OEMs to focus more on Light weighting and Energy efficiency areas. Considering the aforesaid challenges, efforts have been taken in Light weighting of mounting bracket for Engine application. This paper deals with conversion of Engine accessory bracket from Aluminum material to Metal Matrix composite (MMC). In Design phase, existing bracket has been studied for its structural requirements and further Bracket is designed to meet MMC process requirement and CAE carried out for topology optimization and Structural integrity. Finally observations and results were compared for Existing design and Proposed design and further optimization proposed.

In the past few decades CNG (Compressed Natural Gas) fuel growing as an alternate fuel due to its more economically as compared to Gasoline & Diesel fuels by vehicle running cost in both passenger as well as commercial vehicles, additionally it is more environment friendly & safer fuel with respect to gasoline & diesel. At standard temperature & pressure fuel density of Natural Gas (0.7-0.9 kg/m3) is lower than Gasoline (715-780 kg/m3), Diesel (849~959 kg/m3), therefore CNG fuel require higher storage space as compared to Gasoline & Diesel & also it stores at very high pressure (200-250 bar) to further increase the fuel density 180 kg/m3 (at 200 bar) and for 215 kg/m3 (at 250 bar) in CNG cylinders so that max fuel contains in the cylinders and increase the vehicle running range per fuel filling & reduces its fuel filling frequency at filling stations.

Engine cooling systems for vehicles are used for cooling the engine fluids. The cooling system normally consists of following components: radiator, expansion tank, cooling fan, fan drive and shroud. The mounting structure for this system must be designed to withstand the loads that will be imposed by the vehicle operation which consists of stresses such as those caused by linear static and dynamic loading. Automotive industries perform various tests on vehicles in the end-user environment to reduce failures; these investigations are carried out on the design using finite element method (FEM). Finite element methods are being used routinely to analyze for structural behavior. Modeling is done with CATIA software, meshing is carried out with HYPERMESH software and solution is acquired using NASTRAN solver.

Increasing demands on engine power to meet increased load carrying capacity and adherence to emission norms have necessitated the need to improve thermal management system of the vehicle. The efficiency of the vehicle cooling system strongly depends on the fan and fan-shroud design and, designing an optimum fan and fan-shroud has been a challenge for the designer. Computational Fluid Dynamics (CFD) techniques are being increasingly used to perform virtual tests to predict and optimize the performance of fan and fan-shroud assembly. However, these CFD based optimization are mostly based on a single performance parameter. In addition, the sequential choice of input parameters in such optimization exercise leads to a large number of CFD simulations that are required to optimize the performance over the complete range of design and operating envelope. As a result, the optimization is carried out over a limited range of design and operating envelope only.

The modern trend of engine downsizing for CO₂ reduction coupled with stringent emission norms compel the engine air inlet system to outperform the conventional designs. Modern turbo diesel engine air inlet system handles higher & higher air flow, boost pressure and temperature. Air inlet system ducting designs have become complex due to oil particles (received through PCV system), engine movement and isolation for NVH. Air inlet ducting failures; like oil mist leakage through joints and seepage through hose wall cause high engine oil consumption and most predominantly environment damage. Also to some extent boost leakage in certain operating conditions. These failures reduce the reliability and performance of engine in certain conditions. This paper discusses design and development of cost-effective non-permeable and leak-proof hose-piping system for turbocharged diesel engine where PCV system was connected to air inlet system.

For an automotive exhaust system, noise level and back pressure are the most important parameters for passenger comfort and engine performance respectively. The sound quality perception of the existing silencer design was unacceptable, although the back pressure measured was below the target limit. To improve the existing design, few concepts were prepared by changing the internal elements of silencer only. The design constraints were the silencer shell dimensions, volume of silencer, inlet pipe and outlet tailpipe positions, which had to be kept same as that of the existing base design. The sound quality signal replaying and synthesizing was performed to define the desired sound quality. The numerical simulation involves 3D computational fluid dynamics (CFD) with appropriate boundary condition having less numerical diffusions to predict the back pressure. The various silencer concepts developed with this preliminary analysis, was then experimentally verified with the numerical data.

The purpose of Federal Motor Vehicle Safety Standard 216 is to reduce fatalities and serious injuries when vehicle roof crushes into occupant compartment during rollover crash. Upgraded roof crush resistance standard (571.216a Standard No. 216a) requires vehicle to achieve maximum applied force of 3.0 times unloaded vehicle weight (UVW) on both driver and passenger sides of the roof. (For vehicles with gross vehicle weight rating ≤ 6,000 lb.) This paper provides an overview of current approach for dual side roof strength Finite Element Analysis (FEA) and its limitations. It also proposes a new approach based on powerful features available in virtual tools. In the current approach, passenger side loading follows driver side loading and requires two separate analyses before arriving at final assessment. In the proposed approach only one analysis suffices as driver and passenger side loadings are combined in a single analysis.