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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.

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.

A cargo box is a key structure in a pickup truck which is used to hold various items. Therefore, a cargo box must be durable and robust under different ballast conditions when subjected to road load inputs. This paper discusses a Design for Six Sigma (DFSS) approach to improve the durability of cargo box panel in its early development phase. Traditional methods and best practices resulted in multiple iterations without an obvious solution. Hence, DFSS tools were proposed to find a robust and optimum solution. Key control factors/design parameters were identified, and L18 Orthogonal Array was chosen to optimize design using CAE tools. The optimum design selected was the one with the minimum stress level and the least stress variation. This design was confirmed to have significant improvement and robustness compared to the initial design. DFSS identified load paths which helped teams finally come up with integrated shear plate to resolve the durability concern.

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.

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.

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.

Many chassis and powertrain components in the transportation and automotive industry experience multi-axial cyclic service loading. A thorough load-history leading to durability damage should be considered in the early vehicle production steps. The key feature of rubber fatigue analysis discussed in this study is how to define local critical location strain time history based on nominal and complex load time histories. Material coupon characterization used here is the crack growth approach, based on fracture mechanics parameters. This methodology was utilized and presented for a truck engine mount. Temperature effects are not considered since proving ground (PG) loads are generated under isothermal high temperature and low frequency conditions without high amounts of self-heating.

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.

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.

Upper frame deflection of automobile doors is a key design attribute that influences structural integrity and door seal performance as related to NVH. This is a critical customer quality perception attribute and is a key enabler to ensure wind noise performance is acceptable. This paper provides an overview of two simulation methodologies to predict door upper frame deflection. A simplified simulation approach using point loads is presented along with its limitations and is compared to a new method that uses CFD tools to estimate aerodynamic loads on body panels at various vehicle speeds and wind directions. The approach consisted of performing external aerodynamic CFD simulation and using the aerodynamic loads as inputs to a CAE simulation. The details of the methodology are presented along with results and correlation to experimental data from the wind tunnel.

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.

ISO/SAE 21434 [1] Final International Standard was released September 2021 to great fanfare and is the most prominent standard in Automotive Cybersecurity. As members of the Joint Working Group (JWG) the authors spent 5 years developing the 84 pages of precise wording acceptable to hundreds of contributors. At the same time the auto industry had been undergoing a metamorphosis probably unmatched in its hundred-year history. A centerpiece of the metamorphosis is the adoption of the Agile development method to meet market demands for time-to-market and flexibility of design. Unfortunately, a strategic decision was made by the JWG to focus ISO/SAE 21434 on the V-Model method. Agile does not break ISO/SAE 21434. Agile is a framework that can be adapted to suit any process. In the end the goals are the same regardless of development method; security by design must be achieved.

Cargo box is one of the indispensable structures of a pickup truck which makes it capable of transporting heavy cargo weights. This heavy cargo weight plays an important role in durability performance of the box structure when subjected to road load inputs. Finite element representation for huge cargo weight is always challenging, especially in a linear model under dynamic proving ground road load durability analysis using a superposition approach. Any gap in virtual modeling technique can lead to absurd cargo box modes and hence durability results. With the existing computer aided engineering (CAE) approach, durability results could not correlate much with physical testing results. It was crucial to have the right and robust CAE modeling technique to represent the heavy cargo weight to provide the right torsional and cargo modes of the box structure and in turn good durability results.

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.

Through real-time online optimization, the full potential of the performance and energy efficiency of multi-gear, multi-mode, series–parallel hybrid powertrains can be realized. The framework allows for the powertrain to be in its most efficient configuration amidst the constantly changing hardware constraints and performance objectives. Typically, the different gears and hybrid/electric modes are defined as discrete states, and for a given vehicle speed and driver power demand, a formulation of optimization costs, usually in terms of power, are assigned to each discrete states and the state which has the lowest cost is naturally selected as the desired of optimum state. However, the optimization results would be sensitive to numerical exactitude and would typically lead to a very noisy raw optimum state. The generic approach to stabilization includes adding hysteresis costs to state-transitions and time-debouncing.