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The main function of mobile air conditioning system in a vehicle is to provide the thermal comfort to the occupants sitting inside the vehicle at all environmental conditions. The function of ducts is to get the sufficient airflow from the HVAC system and distribute the airflow evenly throughout the cabin. In this paper, the focus is to optimize the rear passenger floor duct system to meet the target requirements through design for six sigma (DFSS) methodology. Computational fluid dynamics analysis (CFD) has been used extensively to optimize system performance and shorten the product development time. In this methodology, a parametric modeling of floor duct design using the factors such as crossectional area, duct length, insulation type, insulation thickness and thickness of duct were created using CATIA. L12 orthogonal design array matrix has been created and the 3D CFD analysis has been carried out individually to check the velocity and temperature.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

Dimensional Engineering concentrates effort in the early design phases to meet the dimensional build objectives in automotive production. Design optimization tools include tolerance stack up, datum optimization, datum coordination, dimensional control plans, and measurement plans. These tools are typically based on the assumption that parts are rigid and tooling dimensions are perfect. These assumptions are not necessarily true in automotive assemblies of compliant sheet metal parts on high volume assembly lines. To address this issue, Finite Element Analysis (FEA) has been increasingly used to predict the behavior of imperfect and deformable parts in non-nominal tooling. This paper demonstrates an application of this approach. The complete analysis is divided into three phases. The first phase is a nominal design gravity analysis to validate the nominal design and tooling.

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements.

An automobile door is one vital commodity which has its role in vehicle’s function, strength, safety, dynamics and aesthetic parameters. The door system comprises of individual components and sub-assemblies such as door upper, bolster, armrest, door main panel, map-pocket, handle, speaker and tweeter grille. Among them, armrest is an integral part which provides function and also takes care of some safety parameter for the customers. The basic function of an armrest is to provide ergonomic relief to occupant for resting his hand. Along with this, it also facilitates occupant safety during a side impact collision by absorbing the energy and not imparting the reactive force on occupant. Thus an armrest has evolved as a feature of passive safety. The armrest design should be stiff enough to withstand required elbow load condition with-in the acceptable deflection criteria. On the other hand, armrest has to absorb the dynamic force by deflecting proportionally to the side impact load.

This paper focuses on an inherent problems of active damping control prevalent in contemporary hybrid torque controls. Oftentimes, a supervisory torque controller utilizes simplified system models with minimal system states representation within the optimization problem, often not accounting for nonlinearities and stiffness. This is motivated by enabling the generation of the optimum torque commands with minimum computational burden. When inherent lash and stiffness of the driveline are not considered, the resulting command can lead to vibrations and oscillations in the powertrain, reducing performance and comfort. The paper proposes a Linear Quadratic Integral (LQI)-based compensator to be integrated downstream the torque supervisory algorithm, which role is to shape transient electric machine torques, compensating for the stiffness and backlash present in the vehicle while delivering the driver-requested wheel torque.

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the inlet air compression process, the air is heated to temperatures that can result in pre-ignition resulting and reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat created during the compression process. The present research describes the physics and develops the optimized simulation method that defines the process and gives insight into the development of CACs.

Current generation passenger vehicles are built with several electronic sensors and modules which are required for the functioning of passive safety systems. These sensors and modules are mounted on the vehicle body at locations chosen to meet safety functionality requirements. They are mounted on pillars or even directly on panels based on specific packaging requirements. The body panel or pillar poses local structural resonances and its dynamic behavior can directly affect the functioning of these sensors and modules. Hence a specific inertance performance level at the mounting locations is required for the proper functioning of those sensors and modules. Drive point modal frequency response function (FRF) analysis, at full vehicle model for the frequency range up to 1000 Hz, is performed using finite element method (FEM) and verified against the target level along with test correlation.

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

Design for Six Sigma (DFSS) is an essential tool and methodology for innovation projects to improve the product design/process and performance. This paper aims to present an application of the DFSS Taguchi Method for an automotive/vehicle component. High-Pressure Vacuum Assist Die Casting (HPVADC) technology is used to make Cast Aluminum Front Shock Tower. During the vehicle life, Shock Tower transfers the road high impact loads from the shock absorber to the body structure. Proving Ground (PG) and washout loads are often used to assess part strength, durability life and robustness. The initial design was not meeting the strength requirement for abusive washout loads. The project identified eight parameters (control factors) to study and to optimize the initial design. Simulation results confirmed that all eight selected control factors affect the part design and could be used to improve the Shock Tower's strength and performance.

Two methods of assessing the similarity of a set of impact test signals have been proposed and used in the literature, which are cumulative variance-based and cross correlation-based. In this study, a normalized formulation unites these two approaches by establishing a relationship between the normalized cumulative variance metric (v), an overall similarity metric, and the normalized magnitude similarity metric (m) and shape similarity metric (s): v=1 − m · s. Each of these ranges between 0 and 1 (for the practical case of signals acquired with the same polarity), and they are independent of the physical unit of measurement. Under generally satisfied conditions, the magnitude similarity m is independent of the relative time shifts among the signals in the set; while the shape similarity s is a function of these.

Automotive companies are studying to add extra value in their vehicles by enhancing powertrain sound quality. The objective is to create a brand sound that is unique and preferred by their customers since quietness is not always the most desired characteristic, especially for high-performance products. This paper describes the process of developing a brand powertrain sound for a high-performance vehicle using the DFSS methodology. Initially the customer's preferred sound was identified and analyzed. This was achieved by subjective evaluations through voice-of-customer clinics using vehicles of similar specifications. Objective data were acquired during several driving conditions. In order for the design process to be effective, it is very important to understand the relationship between subjective results and physical quantities of sound. Several sound quality metrics were calculated during the data analysis process.

Automotive AC systems are typically either single unit or dual unit systems, while the dual unit systems have an additional rear evaporator. The refrigerant evaporates inside these heat exchangers by taking heat and condensing the moisture from the recirculated or fresh air that is being pushed into the car cabin by air blowers. This incoming cold air in turn brings the cabin temperature and humidity to a level that is comfortable for the passengers. These HVAC units have their own thermal expansion valve to set the refrigerant flow, but both are connected to the main AC refrigerant loop. The airflows, however, are controlled independently for front and rear unit that can affect the temperature and amount of air coming into the cabin from each location and consequently the overall cabin cool-down performance.

An automotive powertrain system consists of several interactive and linked nonlinear systems. This research focuses on the coordination of Gasoline Direct Injection (GDI) engine, transmission and emission aftertreatment systems. The goal is to design an optimal control strategy for driving performance, emissions (HC, CO, NOX), fuel economy and smoothness when switching engine mode and when shifting gears, under both discrete and continuous limitations. A multivariable control strategy is used to compromise among all powertrain subsystems to achieve optimal overall performance. A nonlinear discrete dynamic programming approach is proposed for hybrid system optimization. The complex multivariable automotive control problem is then simplified into an optimization problem. The feasibility of automotive hybrid control via the discrete dynamic programming approach is demonstrated by results from many numerical simulations under different operating conditions.

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.

This paper focuses on the conjugate heat transfer analysis of an I4 engine, and discusses optimization of the coolant passages in engine coolant jackets. Direct Optimization approach integrates an optimizer with the numerical solver. This method of optimization is compared with a metamodel-based optimization in which a metamodel is generated to aid in finding an optimal design. The direct optimization and metamodel approaches are compared in terms of their accuracy, and execution time.

As electrification of powertrains is progressing, diversification of hybrid powertrains increases. This generally imposes the challenge for a supervisory controller of how to optimally control the torque of the electric machine(s). Architectures, which have at least one belt driven electric machine, are an essential part of the portfolio. This paper describes a strategy on how to include the losses of the belt device in the determination of optimal electric machine torque command. It first depicts a physics-based method for controlling optimal electric machine torque command for systems without a belt connected electric machine. This method considers the constraints of the electric machine(s) as well as the power limitations from the electric devices, which supply power to the motors.

The present work is concerned with the objective of developing a process for practical multi-disciplinary design optimization (MDO). The main goal adopted here is to minimize the weight of a vehicle body structure meeting NVH (Noise, Vibration and Harshness), durability, and crash safety targets. Initially, for simplicity a square tube is taken for the study. The design variables considered in the study are width, thickness and yield strength of the tube. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value. The optimum solution is then obtained by using traditional gradient-based search algorithm functionality “fmincon” in commercial Matlab package.

The automotive Air Induction System (AIS) is an important part of the engine systems which delivers the air to the engine. A well-designed AIS should have low flow restriction and radiates a good quality sound at the snorkel. The GT-Power simulation tool has been widely utilized to evaluate the snorkel noise in industry. In Fiat Chrysler Automobiles, the simulation method enhanced with Design For Six Sigma (DFSS) approach has been developed and implemented in AIS development to meet the functional requirements. The development work included different types of DFSS projects such as identifying new concept, robust optimization and robust assessment etc. In this paper, the work of a robust optimization project is presented on developing an AIS parametric model to achieve optimized snorkel noise performance for a V8 engine. First, the theory of AIS acoustic modeling using GT-power and DFSS robust optimization using Taguchi’s parameter design method are described.