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As technology gets upgraded every day, automotive manufacturers are paying more attention towards delivering a highly reliable product which performs its intended function throughout its useful life (without any failure). To develop a reliable product, accelerated combined stress testing should be conducted in addition to the conventional design validation protocol for the product. It brings out most of the potential failure modes of the product, so that necessary actions can be taken for the reliability improvement. This paper discusses about the field failure simulation and reliability estimation of automotive headlamp relays using accelerated combined stress testing. To analyze various field failure modes, performance and tear down analysis were carried out on the field failure samples. Field data (i.e. electrical, thermal and vibration signals) were acquired to evaluate normal use conditions.

All automotive components, systems and vehicles undergo stringent validation protocol standards. Nevertheless, there are certain factors which cannot be captured during validation phase and result in field failures. With multiple players prying for market share in the automotive industry, timely resolution of field failures can go a long way in retaining customer base. In such a scenario, when customer’s tolerance on field failures is very limited, failures need severe attention and must be captured as early as possible to cut down warranty expenses. This project aims at creating a methodology to simulate field failures and validate improved design. The reliability parameters such as β (Shape Factor), η (Scale factor), Reliability and life are estimated and the values are compared between field and lab conditions. Life estimated in field conditions (Failure data base) and lab are correlated using Reliability techniques and target is established for validating improved sample.

Driver safety is one of the key considerations in truck design and development. Virtual simulation offers opportunities to reduce development time and the number of physical prototypes consumed for design verification and validation for safety parameters. Thus, the application of virtual simulations of crash has become an integral part of the vehicle development process. The continuously emerging scenarios involving challenging test requirements can only be tested by means of virtual simulation techniques. This paper presents simulations that are performed to verify various safety aspects to ensure crashworthiness of the truck cabin. The cabin structure was evaluated for various national/international safety regulations. The FE model and simulation methodology was validated through physical testing and correlated for frontal impact test and roof strength test as per AIS 029/ECE R29. Analysis performed to ensure compliance to upcoming regulation ECE R29 Revision 03 is also discussed.

A case study was conducted on the design, optimization and material replacement for an automobile suspension link. The link is part of a four bar mechanism. The mechanism was developed in Adams/Car® and multibody simulation was carried out on it. The joint forces arrived from the simulation were exported for finite element analysis of the components in OptiStruct®. Finally, topology and shape optimization was conducted to reduce the weight of the original component. A feasibility study was also carried out to replace the fabricated steel link with a heat treated cast iron link. Heat treated cast iron being lighter than steel, ensures reduction in weight without compromising on strength. The experiment resulted in a feasible optimized shape which was 32% lighter than the current shape of the link being used in the vehicle, while keeping the stresses and displacements within limits.

Evaluation of vehicle structural durability is one of the key requirements in design and development of today's automobiles. Computer simulations are used to estimate vehicle durability to save the cost and time required for building and testing the prototype vehicles. The objective of this work was to find the service life of automotive structures like passenger commercial vehicle (bus) and truck's cabin by calculating cumulative fatigue life for operation under actual road conditions. Stresses in the bus and cabin are derived by means of performing finite element analysis using inertia relief method. Multi body dynamics simulation software ADAMS was used to obtain the load history at the bus and cabin mount locations - using measured load data as input. Strain based fatigue life analysis was carried out in MSC-Fatigue using static stresses from Nastran and extracted force histories from ADAMS. The estimated fatigue life was compared with the physical test results.

Every class of commercial vehicle has an entirely different usage pattern based on customer application and needs. To perform accurate durability testing, these prototypes should run on real customer usage locations and loading conditions for the target life. However, this is time consuming and not practical, hence resulting in Proving Ground (PG) testing. It is also known that a standard PG durability cycle cannot be valid for every class of vehicle and every application. So a statistical approach was followed to develop an accelerated durability test cycle based on in-house PG test surfaces in order to match the real customer usage to the durability target life. This paper summarizes the methodology to develop Durability Validation test cycles for commercial vehicle based on the work carried out on a heavy duty tipper and an intermediate commercial vehicle.

In recent years NVH has gained a lot of importance in the commercial vehicle industry as it contributes significantly towards user comfort and also towards the quality perception associated with a vehicle. The in-cabin noise of vehicles is critical towards the comfort and usability for the end user and the sound package installed on the vehicle plays a vital role in determining the levels associated with this attribute, especially the high frequency content. The paper discusses a methodology for optimizing the sound package for performance, cost and mass, for a truck. The approach uses a Statistical Energy Analysis (SEA) based optimization. A virtual SEA model is developed, which is correlated with actual test data. After establishing the correlation, an optimization study is carried out to identify the effectiveness of different materials and material combinations towards in-cabin noise.

Driver's ride comfort is an important characteristic in heavy commercial vehicle cab design. Optimizing the ride behavior for different cab variants and vehicle applications is a challenge for cab design and development engineers. Suspension parameter tuning with physical test is time consuming and costly. Therefore, a lumped parameter quarter car model of suspended cab is developed in MATLAB® tool SimScape which includes cab mass, springs and dampers for predicting ride behavior as per ISO 2631. The study is done for a 25 t rigid truck. The input to the system is displacement at axles and the output is acceleration measured at cab and chassis level. This output is correlated with test data obtained from physical measurements using Power Spectral Density (PSD) curves, bode plots and level cross count. This proved that simple lumped parameter models which use very few input parameters can be effectively employed in analysis of cab ride in initial design phases.

Spring seat plays major role in bogie suspension; which is guiding and controlling the leaf spring for better suspension and also to withstand the compressive load from leafs. Currently used spring seats are failing frequently in medium and heavy duty vehicles, which lead to customer concerns by higher idle time and part replacement cost. Thickness of the spring seat can't be increased by large extent due to packaging constraints in the vehicle. Stress levels identified by FEA method are found higher than the current material capacity. With these constraints, the spring seat has been re-designed with improved strength and ductility of material by modern technology - Austempered Ductile Iron (ADI). The parts have been developed and assembled in various tipper applications and performance was studied. The developed spring seat shows five times superior durability compare to existing design.

Due to the emerging technologies and globalization, expectations of the customers on commercial vehicles are getting increased over the period. It is an important duty of an OEM to deliver a perfectly configured product to suit the customer requirements. When it comes to configuration of a vehicle, engine power is one of the key factors which indicate the performance of that vehicle. There is a tough competition between every OEM to increase the engine power for enhancing the overall operational performance. One method to increase power is to improve its volumetric efficiency. This is achieved with help of turbocharger and Charge Air Cooler (CAC). CAC improves volumetric efficiency by increasing intake air-charge density. Any failure on CAC leads to lower the volumetric efficiency and increase in turbocharger loading. This paper deals with the validation of CAC assembly using different test conditions by analyzing potential failure modes against the field issues.

Automotive business is more focused towards delivering a highly durable and reliable product at an optimum cost. Anything falls short of customer expectation will ruin the manufacturer’s reputation. To exterminate this, all automotive components shall undergo stringent testing protocol during the design validation process. Nevertheless, there are certain factors in the field which cannot be captured during design validation. This paper aims at developing a validation methodology for engine oil sump by simulating field failure. In few of our vehicles, field failure was observed in engine oil sump near the drain plug location. Preliminary analysis was carried out to find the potential causes for failure. Based on the engine test bed results, multi frequency swept sine testing was carried out in laboratory. Field failure was simulated in the lab test and the root causes for failure were found out.

Diesel Exhaust Fluid (DEF) concentration monitoring is done to detect the concentration at which the emission thresholds are exceeded in BSVI engines [1]. This paper introduces a novel method to model the fault monitoring system with enable conditions designed to detect deterioration in DEF concentration, while reducing misdetection. This eliminates the need for dedicated sensor, reduces complexity, cost, and potential sensor-related failure modes. Traditionally, Diesel Exhaust Fluid quality sensors have been employed to measure the absolute concentration of Diesel Exhaust Fluid in the aqueous solution of urea [2]. This information is used to detect usage of poor quality DEF which results in increase in NOx emission beyond legal limits.

In the commercial vehicle business, vehicle availability is a pivotal factor for the profitability of the customer. Nonetheless, the intricate nature of the technologies embedded in modern day engines and exhaust after-treatment systems coupled with the variability of the duty cycles of end applications of the vehicles imposes added challenges on the vehicle's sustained performance and reliability. In this context, the ability to predict potential failures through tools like telematics and real-time data analytics presents a significant opportunity for original equipment manufacturers (OEMs) to deliver distinctive value to their customers.

The gearbox is a crucial aggregate in a diesel truck. Gearboxes must work efficiently to get the job done properly and lubrication is vital to this efficiency. Lubricating oil is like the circulation system of a gearbox. If the oil levels fall too low, the gearbox will likely fail. Gearbox failure can lead to expensive repairs that could be prevented. Besides added costs due to replacement or repair, costs associated with a loss of production could be significant. These issues are why; it is important to understand the consequences of having low lubricant levels. Similarly, higher oil level creates higher churning losses, heating of the Gear oil and oxidation, reduction in efficiency and increased oil leaks. Understanding the functions of gearbox lubricating oil can help you choose the right quantity of prevent gearbox failures.