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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.

Important vehicle performance parameters such as, fuel economy and high speed stability are directly influenced by its aerodynamic drag and lift. Wind tunnel testing to asses these parameters requires heavy investment especially when test wind tunnel is not available in the country where vehicle development center is present. Hence to save cost and to compress development time, it is essential to asses and optimize parameters of a vehicle in very early stages of development. Using numerical flow simulations optimization runs can be carried out digitally. Industry demands prediction of aerodynamic drag and lift coefficients (CD,CL) within an accuracy of a few counts, consuming minimal HPC resources and in a short turnaround time. Different OEMs deploy different testing methods and different softwares for numerical simulations.

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.

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.

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.

The traditional method of collecting the Road Torque Data of a vehicle is by instrumenting and running the vehicle on different road terrains. Every time, physical testing becomes tedious & most challenging task due to unavailability of unit under tests, kind of resource required and so on. However, in view of response to the fast emerging technology & limit less competition, it has become mandatory to develop & launch products in market within no time. In recent times, there is increased demand for physical road torque data measurements for a vehicle program based on its application and different powertrain configurations, which clearly shows that unless we front load the data to design it is practically impossible to meet the deadlines. Each of these measurements cost and consumes valuable resources of the company in collecting and analyzing the data.

One of the very first customer touchpoint in a vehicle is quality of gear shifting. Gearshift quality is perceived as a symbol of refinement of a vehicle. Globally, lot of efforts are taken to refine the gearshift quality. Design improvements in internal components of transmission, cable and shifter assembly, knob design iterations are carried out to arrive at optimum gearshift quality at the vehicle level. Current practice for this activity includes processes such as design modification, manufacturing of proto components, assembly of components and fitment in the vehicle. This vehicle is then instrumented with sensors and data acquisition units to capture the parameters which determine the gearshift quality. This is an iterative process which goes on until necessary refinement/improvement is achieved. This process requires investment of lot of time, efforts and the budget. This paper describes a virtual approach to arrive at optimum design of components.

Climate change due to global warming calls for more fuel-efficient technologies. Parallel Full hybrids are one of the promising technologies to curb the climate change by reducing CO2 emissions significantly. Different parallel hybrid electric vehicle (HEV) architectures such as P0, P1, P2, P3 and P4 are adopted based on different parameters like fuel economy, drivability, performance, packaging, comfort and total cost of ownership of the vehicle. It is a great challenge to select right hybrid architecture for different vehicle segments. This paper compares P2 and P3 HEV with AMT transmission to evaluate most optimized architecture based on vehicle segment. Vehicles selected for study are from popular vehicle segments in India with AMT transmission i.e. Entry segment hatch and Compact SUV. HEV P2 and P3 architectures are simulated and studied with different vehicle segments for fuel economy, performance, drivability and TCO.