Search Results

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.

Welding is one of the most convenient and extensively used manufacturing process across every industry and is recognized as a cost effective joining technique. The root cause of most of the fabricated structural failures lies in the uncertainties associated with the welding process. It is prone to generate high residual stresses due to non-volumetric changes during heating and cooling cycle. These residual stresses have a significant impact on fatigue life of component leading to poor quality joints. To alleviate these effects, designers and process engineers rely upon their experience and thumb rules but has its own limitations. This approach often leads to conservative designs and pre-mature failures. Recent advances in computational simulation techniques provide us opportunity to explore the complex phenomenon and generate deep insights. The paper demonstrates the methodology to evaluate the residual stresses due to welding in virtual environment.

This paper highlights the transition of multi-axis suspension test rig from fixed reacted type to semi-inertial type and the benefits derived thereof in simulation accuracies. The critical influence of ‘Mx’ and ‘Mz’ controls on simulation accuracies has been highlighted. The vital role of ‘Mz’ control in the resonance of wheel pan along ‘Z’ axis and thereof arresting unwanted failures modes in spindle has been duly emphasized. Finally, the role of constraints and boundary conditions on simulation accuracies has been demonstrated by replacing the reaction frame with vehicle body.

Automotive OEMs are launching multiple products with ever reducing development time, balancing costs, quality and time to market, with clear focus on performance and weight. Platform architecture concepts, modular designs for differentiation etc. are strategies adopted by automotive OEMs towards shorter development cycles. Thus, concept generation phase of the digital product development process is expected to enable generation and evaluation of multiple concept architectures, carry out performance studies and largely focus on optimization, upfront. This Front loading of engineering and call for simultaneous engineering requires support in terms of quick and good CAD modeling with maturity. This paper proposes a process that focuses on generation and evaluation of multiple concepts, besides enabling optimization of concept before the detailed design phase kicks in.

Passive safety regulations specify minimum safety performance requirements of vehicle in terms of protecting its occupants and other road users in accident scenarios. Currently for majority cases, the compliance of vehicle design to passive safety regulations is assessed through physical testing. With increased number of products and more comprehensive passive safety requirements, the complexity of certification is getting challenged due to high cost involved in prototype parts and the market pressures for early product introduction through reduced product development timelines. One of the ways for addressing this challenge is to promote CAE based certification of vehicle designs for regulatory compliance. Since accuracy of CAE predictions have improved over a period of time, such an approach is accepted for few regulations like ECE-R 66/01, AIS069 etc which involves only loadings of the structures.

Reduction of NOx (Oxides of Nitrogen) and particulates from engine exhaust is one of the prime considerations in current research and development in automotive industry. The present paper describes the combustion optimization done on a four cylinder, 4 liter DI diesel engine to meet stringent Euro-III emission norms. The engine FIE (Fuel Injection Equipment) and injector geometry was optimized for performance and emission. Smoke measurements were considered as indicative of soot, to predict particulate emissions. This was done to simplify the overall process and save development time. It was concluded that by combining the flexibility of electronically controlled fuel injection begin, with improved nozzle technologies, with higher spray velocities and spray penetration, a considerable reduction in NOx and particulate emissions can be achieved. This can serve as a low cost solution, without any exhaust after-treatment systems.

The use of Wheel Force Transducers (WFTs) to acquire data for laboratory simulation is becoming standard industry practice. However, in test rigs where we have only the suspension module and not the complete vehicle, does the reproduction of the orthogonal forces and moments at the wheel centre guarantee an accurate replication of the fatigue damage in the suspension components? The objective of this paper is to review the simulation methodology for a highly non-linear suspension in a 3 DOF (degree-of-freedom) suspension test rig in which the simulation was carried out using only the three orthogonal loads and vertical displacement. The damage at critical locations in the suspension is compared with that on the road and an assessment of the simulation using the WFT is made based on a comparison of the damage on the road vs. the rig.

Design of a Cabin Tilting System of heavy trucks, a multi degree of freedom mechanism, is a challenge. Factors like adequate tilting angle, cabin styling, packaging, non interference of tilting system with ride comfort, forces in the system, specifications of the hydraulic system, are all very important for designing the system. Numerous considerations make the design process highly iterative hence longer design time. This paper primarily focuses on Kinematics and Dynamic analysis of the system in ADAMS and validation of system with real time testing results. Intention of this work is to make a parametric ADAMS model and link it to a Knowledge Based Engineering application to facilitate designer to quickly carry out design iterations for reducing development time. The Knowledge Based Engineering software is made using object oriented language called ‘Object Definition Language’ which has been developed using C and C++ software languages.

EU directive 2005/64/EC on type approval of motor vehicles with respect to their Reusability, Recyclability and Recoverability ( RRR ) requires vehicle manufacturers to put in place the necessary arrangements and procedures for Parts, Materials and Weight (PMW ) data collection from full chain of supply. This is required to perform the calculations of recyclability rate and recoverability rate in line with ISO 22628. Commonly practiced data collection methodologies included spreadsheet and use of internationally available IT support system for collection of material data. Data complexity and prohibitive cost for using Internationally available IT Support systems like IMDS (International Material Data System) has led to the in-house development of IT enabled Solution customizing Siemens PLM software product (Team centre Enterprise) and SAP (SRM suite).

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.

New noise regulations, with reduced noise limits, have been proposed by UN-ECE. A new method which aims at representing urban driving of the vehicles more closely on roads is proposed and is considerably different from the existing one (IS 3028:1998). It is more complex; we also found that some of the low powered vehicles can not be tested as per this method. The paper proposes ways of improvement in the test method. The new noise reduction policy options will have a considerable impact on compliance of many categories of vehicles. Technological challenges, before the manufacturers, to meet all performance needs of the vehicle along with the cost of development will be critical to meet the new noise limits in the proposed time frame.

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.

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.

During every clutch engagement energy is dissipated in clutch assembly because of relative slippage of clutch disc w.r.t. flywheel and pressure plate. Energy dissipated in clutch is governed by many design parameters like driveline configuration of the vehicle vis-a-vis vehicle mass, and operational parameters like road conditions, traffic conditions. Clutch burning failure, which is the major failure mode of clutch assembly, is governed by energy dissipation phenomenon during clutch engagement. Clutch undergoes different duty cycles during usage in city traffic, highways or hilly regions during its lifetime. A test schedule was derived using energy dissipated during every clutch engagement event as a base and using road load data collected on the vehicle. Road load data was collected in different road mix conditions comprised of city traffic, highway, hilly region, rough road for few hundred kilometers.

Spot welding is the primary joining method used in automobiles. Spot-weld plays a major role to maintain vehicle structural integrity during impact tests. Robust spot weld failure definitions is critical for accurate predictions of structural performance in safety simulations. Spot welds have a complex metallurgical structure, mainly consisting of fusion and heat affected zones. For accurate material property definitions in simulation models, huge number of inputs from test data is required. Multiple tests, using different spot weld joinery configurations, have to be conducted. In order to accurately represent the spot-weld behavior in CAE, detailed modeling is required using fine mesh. The current challenge in spot-weld failure assessment is developing a methodology having a better trade-off between prediction accuracy, testing efforts and computation time. In view of the above, cohesive zone models have been found to be very effective and accurate.

The automotive industry is heading in the direction of signing off the exhaust system durability based on computer simulation rather than rig simulation and physical vehicle testing. This is due to the cost, time and availability of prototype vehicles and test track. Use of Finite Element Method (FEM) enables to assure the structural integrity of the exhaust system and also contribute to better understanding of the system behavior in the various operating conditions and evaluation of structural strength. This paper deals with dynamic analysis of a modular automotive exhaust system where it is directly mounted on power train pack. Selection of dynamic loads, processing of the test data, and effect of assembly loads along with material property variation due to temperature are explained. It also includes validation of the CAE model, prediction of probable failure locations and improving the design based on analysis outcome.

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.

Steering pull during high speed braking of heavy commercial vehicles possesses a potential danger to the occupants. Even with negligible wheel-to-wheel brake torque variation, steering pull during the high speed braking has been observed. If the steering pull (i.e. steering rotation) is forcibly held at zero degree during high speed braking, the phenomena called axle twist, wheel turn and shock absorber deflection arise. In this work the data have been collected on the mentioned measures with an intention to develop a mathematical model which uses real time data, coming from feedback mechanism to predict the values of the measures in coming moments in order to aid steering system to ‘auto-correct’. Driven by the intention, ‘Time Series Analysis’, a well-known statistical methodology, has been explored to see how suitable it is in building the kind of model.

Shock tube is used to simulate blast loading conditions on materials for studying the failure behavior of different materials under blast pressures on smaller scale. This paper describes CAE method developed for simulating shock tube experiment in LS-DYNA3D environment. The objective of shock tube simulation is to characterize material failure parameters so as to predict risk of material failure in full vehicle blast simulations while developing vehicle for blast protection applications. The paper describes modeling of shock wave and its interaction with test specimen in shock tube environment. Arbitrary Lagrangian-Eulerian (ALE) techniques are applied to simulate shock tube experiment in LS-DYNA3D and simulation predictions are compared with experimental test data. CAE correlation studies were carried out with respect to incident and reflected pressures in shock tube, deformation and plastic strains on test specimen, shock wave velocity etc.

Tire inflation pressure has a significant impact over vehicle driving dynamics, fuel consumption as well as tire life. Therefore, continuous monitoring of tire pressure becomes imperative for ride comfort, safety and optimum vehicle handling performance. Two types of tire pressure monitoring systems (TPMS) used by vehicles are - direct and indirect TPMS. Direct systems deploy pressure sensors at each wheel and directly send pressure value to the vehicle Controller Area Network (CAN). Indirect sensors on the other hand use the information from already existing sensors and some physics-based equations to predict the value of tire pressure. Direct TPMS tend to be more accurate but have higher cost of installation while indirect TPMS comes with a minimum cost but compromised accuracy. A digital proof-of-concept study for indirect TPMS development of a non-ESP vehicle based on machine learning (ML) technique is elaborated in this paper.