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Automotive manufacturers are being challenged to come up with radical solutions to achieve substantial (30-35%) vehicle weight reductions without compromising Safety, Durability, Handling, Aero-thermal or Noise, Vibration and Harshness (NVH) performance. Developing light weight vehicle enablers have assumed foremost priority amongst vehicle engineering teams in order to address the stringent Fuel Economy Performance (FEP) targets while facilitating lower CO2 emissions, downsizing of engines, lower battery capacities etc. Body sheet metal panels have become prime targets for weight reductions via gage reduction, high strength steel replacement, lighter material applications, lightening holes etc. Many of these panel weight reduction solutions are in sharp conflict with NVH performance requirements.

Damages (fracture) in metals are caused by material degradation due to crack initiation and growth due to fatigue or dynamic loadings. The accurate and realistic modeling of an inelastic behavior of metals is essential for the solution of various problems occurring in engineering fields. Currently, various theories and failure models are available to predict the damage initiation and the growth in metals. In this paper, the failure of aluminum alloy is studied using progressive damage and failure material model using Abaqus explicit solver. This material model has the capability to predict the damage initiation due to the ductile and shear failure. After damage initiation, the material stiffness is degraded progressively according to the specified damage evolution response. The progressive damage models allow a smooth degradation of the material stiffness, in both quasi-static and dynamic situations.

In recent years clearing the mist on side windows is one of the main criterions for all OEMs for providing comfort level to the person while driving. Visibility through the side windows will be poor when the mist is not cleared to the desired level. “Windows fog up excessively/don't clear quickly” is one of the JD Power question to assess the customer satisfaction related to HVAC performance. In a Mobile Air Conditioning System, HVAC demister duct and outlet plays an important role for removing the mist formation on vehicle side window. Normally demister duct and outlet design is evaluated by the target airflow and velocity achieved at driver and passenger side window. The methodology for optimizing the demister outlet located at side door trim has been discussed. Detailed studies are carried out for creating a parametric modeling and optimization of demister outlet design for meeting the target velocity.

Springback prediction for stamped components is a challenging task for Automotive Industry. Automotive Manufacturers are working to reduce the springback effect of sheet metal stampings caused due to elastic behavior of materials with the help of changes to manufacturing process and part geometry. Recent development in Finite Element Analysis (FEA) studies made it possible for the industry to rely on stamping simulation. There is always a gap between the springback predicted from stamping simulation and the actual stamped part. Currently FEA techniques are trying to close this gap. The objective of this study is to minimize this gap using DFSS method for predicting the springback and optimizing the simulation parameters with the help of LS-Dyna FEM tool. The behavior of material with different simulation parameters has been studied in this paper and the ones that best correlate with actual data are identified.

NHTSA issued the FMVSS 226 ruling in 2011. It established test procedures to evaluate countermeasures that can minimize the likelihood of a complete or partial ejection of vehicle occupants through the side windows during rollover or side impact events. One of the countermeasures that may be used for compliance of this safety ruling is the Side Airbag Inflatable Curtain (SABIC). This paper discusses how three key phases of the optimization strategy in the Design for Six Sigma (DFSS), namely, Identify; Optimize and Verify (I_OV), were implemented in CAE to develop an optimized concept SABIC with respect to the FMVSS 226 test requirements. The simulated SABIC is intended for a generic SUV and potentially also for a generic Truck type vehicle. The improved performance included: minimization of the test results variability and the optimization of the ejection mitigation performance of the SABIC.

During the service life, the impacts of vehicle against potholes result in damage for the wheel and suspension components. Knowing the internal forces generated in the suspension components during this event would helpful to design the critical components. Measurement of these loads in physical test is more costly and not feasible for new designs. There are several virtual tools and methods available to predict the loads during this event. Using the ABAQUS FE solver, the non-linear dynamic behavior could be captured accurately during the impact. The tire model plays an important role during this event by absorbing energy during the impact. The CAE tire model is validated with some physical tests results and it is used in the vehicle pothole impact simulation. In vehicle pothole physical test, the force and acceleration measurement are taken and compared with the CAE results. The effect of the tire pressure variations and the vehicle speed at pothole impact is also studied.

The Charge Air Cooler (CAC) is designed to cool the charge air after being boosted by the Turbocharger. In order to maintain the optimum temperature and to further improve the charge air density entering to the engine the CAC is used. This makes the combustion more efficient and better engine performance and fuel economy. The performance of the CAC is highly affected by the plumbing lines which transport the compressed charge air from turbocharger to the intake manifold of the Engine. It consists of tube, hose, duct and resonator. Designing the optimum CAC plumbing lines with lesser pressure drop is the major requirement of the CAC system considering the complex packaging. In such scenarios, one-dimensional (1D) simulation is a good way to compute the pressure drop for faster and economical solution.

In this paper a design methodology for automotive heat exchangers has been applied which brings robustness into the design process and helps to optimize the design goals: as to maintain an optimal coolant temperature and to limit the vehicle underhood air temperature within a tolerable limit. The most influential design factors for the heat exchangers which affect the goals have been identified with that process. The paper summarizes the optimization steps necessary to meet the optimal functional goals for the vehicle as mentioned above. Taguchi's [1] Design for Six Sigma (DFSS) methods have been employed to conduct this analysis in a robust way.

In this paper, thermal models are developed based on experimental test data, and the physics of thermal systems. If experimental data is available, the data can be fitted to mathematical models that represent the system response to changes in its input parameters. Therefore, empirical models which are based on test data are developed. The concept of time constant is presented and applied to development of transient models. Mathematical models for component temperature changes during transient vehicle driving conditions are also presented. Mathematical models for climate control system warm up and cool-down are also discussed. The results show the significance of adopting this concept in analysis of vehicle test data, and in development of analytical models. The developed models can be applied to simulate the system or component response to variety of changes in input parameters. As a result, significant testing and simulation time can be saved during the vehicle development process.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

A snap-fit is a form-fitting joint, which is used to assemble plastic parts together. Snap-fits are available in different forms like a projecting clip, thicker section or legs in one part, and it is assembled to another part through holes, undercuts or recesses. The main function of the snap-fit is to hold the mating components, and it should withstand the vibration and durability loads. Snap-fits are easy to assemble, and should not fail during the assembling process. Based on the design, these joints may be separable or non-separable. The non- separable joints will withstand the loads till failure, while separable joints will withstand only for the design load. The insertion and the retention force calculation for the snaps are very essential for snap-fit design. The finite element analysis plays a very important role in finding the insertion and the retention force values, and also to predict the failure of the snaps and the mating components during this process.

Accurate numerical prediction of an engine thermal map at a wide range of engine operating conditions can help tune engine performance parameters at an early development stage. This study documents the correlation of an engine thermal simulation using the conjugate heat transfer (CHT) methodology with thermocouple data from an engine operating in a dynamometer and a vehicle drive cell. Three different operating conditions are matched with the simulation data. Temperatures predicted by simulation at specific sections, both at the intake and the exhaust sides of the engine are compared with the measured temperatures in the same location on the operating engine.

Advanced high strength steels (AHSS) offer a good balance of strength, durability, crash energy absorption and formability. Applications of AHSS for lightweight designs of automotive structures are accelerating in recent years to meet the tough new CAFE standard for vehicle fuel economy by 2025. At the same time, the new generation pickup cargo box is to be designed for a dramatic increase in payload. Upgrading the box material from conventional mild steels to AHSS is necessary to meet the conflicting requirements of vehicle light weighting and higher payload. In this paper, typical AHSS grades such as DP590 and DP780 were applied to selected components of the pickup cargo box for weight reduction while meeting the design targets for fatigue, strength and local stiffness.

In recent trend, there is a huge demand for lightweight chassis frame, which improves fuel efficiency and reduces cost of the vehicle. Stiffness based optimization process is simple and straightforward while durability (life) based optimizations are relatively complex, time consuming due to a two-step (Stress then life) virtual engineering process and complicated loading history. However, durability performances are critical in chassis design, so a process of optimization with simplified approach has been developed. This study talks about the process of chassis frame weight optimization without affecting current durability performance where complex durability load cases are converted to equivalent static loadcases and life targets are cascaded down to simple stress target. Sheet metal gauges and lightening holes are the parameters for optimization studies. The optimization design space is constrained to chassis unique parts.

Interference assessments of a stepped-radius power-train component moving within a deformed stepped bore often arise during engine and transmission development activities. For example, when loads are applied to an engine block, the block distorts. This distortion may cause a cam or crankshaft to bind or wear prematurely in its journals as the part rotates within them. Within an automatic transmission valve body, care must be taken to ensure valve body distortion under oil pressure, assembly, and thermal load does not cause spool valves to stick as they translate within the valve body. In both examples, the mechanical scenario to be assessed involves a uniform or stepped radius cylindrical part maintaining a designated clearance through a correspondingly shaped but distorted bore. These distortions can occur in cross-sections (“out-of-round”) or along the bore (in an “s” or “banana” shaped distortions).

Exposure in ISO 26262 is defined as the state of being in an operational situation that can be hazardous if coincident with the failure mode under analysis. An operational situation is defined as a scenario that can occur during a vehicle's life with examples given such as driving, parking, or maintenance. Accurately predicting exposure is one of the more difficult tasks in the ASIL determination. ISO 26262 Part 3 attempts to provide guidance in Annex B through tables of potential operational situations and associated exposure levels. However, the contents of these tables may not allow for an accurate prediction of exposure and may lead to an exposure value that is too high or too low. In this paper, we describe a potential method for determining exposure that considers a potential mishap scenario as a composition of multiple coincident operational situations rather than considering a single operational situation as indicated in the tables in Annex B of Part 3.

An automotive cockpit module is a complex assembly, which consists of components and sub-systems. The critical systems in the cockpit module are the instrument panel (IP), the floor console, and door trim assemblies, which consist of many plastic trims. Stiffness is one of the most important parameters for the plastic trims' design, and it should be optimum to meet all the three functional requirements of safety, vibration and durability. This paper presents how the CAE application and various other techniques are used efficiently to predict the stiffness, and the strength of automotive cockpit systems, which will reduce the product development cycle time and cost. The implicit solver is used for the most of the stiffness analysis, and the explicit techniques are used in highly non-linear situations. This paper also shows the correlations of the CAE results and the physical test results, which will give more confidence in product design and reduce the cost of prototype testing.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

This paper highlights a simplified CAE model technique, which can simulate and predict door crush strength performance quickly. Such quick models can be used for DFSS and Design change studies. The proposed method suggests an equivalent sub model technique using only the door beam with tuned stiffness end springs to predict FMVSS214S full vehicle crush performance. Such models can be solved in minutes and hence very useful for DFSS studies during product design. The proposed method can be used to finalize door beam design for identical size of vehicle doors to meet required FMVSS214S crush performance. The paper highlights the door beam end springs tuning for identical size of cars and SUVs. Four vehicles were considered for the study. A single spring F-D (force -displacement) is tuned which correlated well for frond door of all the four vehicles. A separate unique spring F-D was needed which correlated well for rear door of all the 4 vehicles.

In an Automotive air conditioning system, the air flow distribution in the cabin from the HVAC (Heating, ventilation and air conditioning), ducts and outlets is evaluated by the velocity achieved at driver and passenger mannequin aim points. Multiple simulation iterations are being carried out before finalizing the design of HVAC panel duct and outlets until the target velocity is achieved. In this paper, a parametric modeling of the HVAC outlet is done which includes primary and secondary vane creation using CATIA. Java macro files are created for simulation runs in STAR CCM+. ISIGHT is used as an interface tool between CATIA and STARCCM+. The vane limits of outlet and the target velocity to be achieved at mannequin aim points are defined as the boundary conditions for the analysis. Based on the optimization technique and the number of iterations defined in ISIGHT, the vane angle model gets updated automatically in CATIA followed by the simulation runs in STARCCM+.