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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.

A new method is demonstrated for rating the “severity” of a hypoid gear set duty cycle (revolutions at torque) using the intercept of T-N curve to support gearset selection and sizing decision across vehicle programs. Historically, it has been customary to compute a cumulative damage (using Miner's Rule) for a rotating component duty cycle given a T-N curve slope and intercept for the component and failure mode of interest. The slope and intercept of a T-N curve is often proprietary to the axle manufacturer and are not published. Therefore, for upfront sizing and selection purposes representative T-N properties are used to assess relative component duty cycle severity via cumulative damage (non-dimensional quantity). A similar duty cycle severity rating can also be achieved by computing the intercept of the T-N curve instead of cumulative damage, which is the focus of this study.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.

In recent years, there is increasing demand for every CAE engineer on their confidence level of the virtual simulation results due to the upfront robust design requirement during early stage of an automotive product development. Apart from vehicle feel factor NVH characteristics, there are certain vibration target requirements at system or component level which need to be addressed during design stage itself in order to achieve the desired functioning during vehicle operating conditions. Vehicle passive safety system is one which primarily consists of acceleration sensors, control module and air-bag deployment system. Control module’s decision is based on accelerometer sensor signals so that its mounting locations should meet the sufficient inertance or dynamic stiffness performance in order to avoid distortion in signals due to its structural resonances.

The development of complex engineering systems often encounters various challenges in terms of meeting New Product Development (NPD) assigned budget, launch time, and system performance goals. Most of the NPD processes have been experiencing challenges to meet these goals within an increasingly competitive global market environment. These challenges become more complicated to manage when the development process is long with different sources of uncertainty. Despite decades of industrial experience and academic research efforts in managing NPD processes, it is observed that designing and developing increasingly complex systems, e.g., automotive, is still subjected to significant cost overrun, schedule delays, and functional issues during early design stages. To provide a Reliability Growth Planning (RGP) model, several inputs are required, e.g., the initial reliability estimation, the reliability goal, test recourses, and the duration of the design or test period.

Simplified vehicle dynamics models used to study the driveline durability are typically limited to the longitudinal dynamics and do not account for vertical and pitch dynamics. The influence of suspension on the vehicle ride and handling characteristics is studied extensively in the literature but its impact on the driveline torques is often not considered. In this paper, an effort is made to investigate the influence of suspension compliance on the driveline torque using a planar (longitudinal, pitch and vertical) vehicle dynamics model. An AWD vehicle is studied to understand its impact on the torque levels of both axles (primary and secondary). Subsequently the planar dynamics is explored in the context of anti-squat/anti-dive suspension. The primary focus of the paper is to predict the driveline torque.

The noise radiated from the snorkel of an air induction system (AIS) can be a major noise source to the vehicle interior noise. This noise source is typically quantified as the snorkel volume velocity which is directly related to vehicle interior noise through the vehicle noise transfer function. It is important to predict the snorkel volume velocity robustly at the early design stage for the AIS development. Design For Six Sigma (DFSS) is an engineering approach that supports the new product development process. The IDDOV (Identify-Define-Develop-Optimize-Verify) method is a DFSS approach which can be used for creating innovative, low cost and trouble free products on significant short schedules. In this paper, an IDD project which is one type of DFSS project using IDDOV method is presented on developing a robust simulation process to predict the AIS snorkel volume velocity. First, the IDDOV method is overviewed and the innovative tools in each phase of IDDOV are introduced.

Increase in the atmospheric temperature across the globe during summer, increases the heat load in the vehicle cabin, creating a huge thermal discomfort for the passengers. There are two scenarios where these adverse conditions can be a problem during the summer. Firstly, while driving the vehicle in traffic conditions and secondly, when the vehicle is parked under the sun. When the vehicle is exposed to the radiation from the sun for a period, the cabin temperature can reach alarming levels, which may have serious discomfort and health effects on the people entering the vehicle. Although there are options of remote switching on of air conditioners, they are restricted to vehicles having an automatic transmission and availability of the mobile network. So, it is important to explore the possible options which can be used for restricting the external heat load to the cabin.

There have been multiple studies on the effect of vehicle impact pulses on occupant responses, and studies on the previous and current US NCAP (New Car Assessment Program) vehicle pulses. This paper analyzes 35 mph (56.3 kph) front impact vehicle pulses and occupant responses in US NCAP tests conducted by the NHTSA from 2011 to 2019. Based on the occupant response analysis, a simple generic occupant restraint force-relative displacement model has been created. This generic model captures the fundamental restraint characteristics of the vehicles in the recent years, and together with the vehicle pulse, they provide several occupant response predictors. Furthermore, this paper proposes a new pulse severity metric PSD (Pulse Severity by Displacement) based on the vehicle impact data statistics, and uses the pulse severity to compare with other pulse severity definitions.

This paper delves into the investigation of flatness-based active damping control for hybrid vehicle transmissions. The main objective is to improve the current in-production controller performances without the need for additional sensors or observers. The primary goals include improving torque setpoint tracking, enhancing robustness margins, and ensuring zero steady-state torque correction. The investigation proceeds in several steps: Initially, both the general differential flatness property and the identification of flat outputs in linear dynamical systems are revisited. Subsequently, the bond graph formalism is employed to deduce straightforwardly the dynamical equations of the system. Next, a new flat output of the vehicle transmission is identified and utilized to formulate the trajectory tracking controller to align with the required control objectives and to fulfill the system constraints.

This paper proposes a method to evaluate the sensitivity of the perceived quality of a panel interface design to variation in the measurements of fit and finish. The novelty of this approach is in the application of the concept of utility to fit and finish. The significance is in the ability to evaluate alternative designs with regard to perceived quality long before time and money are spent on their realization. In the automotive industry “fit and finish” is the term applied to the precision of the alignment of one part to another. Fit and finish gives the buyer a sense of the overall quality of the vehicle purely from an aesthetic perspective. Fit and finish is usually evaluated by the manufacturer through dimensional measurements of the gap and flushness conditions between panels.

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.

Computational cost plays a major role in the performance of scientific and engineering simulation. This in turn makes the virtual validation process complex and time consuming. In the simulation process, achievement of appropriate level of accurate models as close as physical testing is the root for increase in the computational cost. During preliminary phase of product development, it is difficult to identify the appropriate size, shape and other parameters of the component and they will undergo several modifications in concept and other stages. An approximation model called metamodel or surrogate model has developed for reducing these effects and minimizing the computational cost. Metamodel can be used in the place of actual simulation models. Metamodel can be an algorithm or a mathematical relation representing the relations between input and output parameters.

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.

Thermal development of automotive applications is a lot more complex than it used to be in the past. Specifically, for Plug-in Hybrid Electric Vehicles (PHEVs), all the sub-systems are so intertwined that it’s hard to analyze them as sub-systems only. A system level solution is needed for proper sizing of components. For early thermal development, a co-simulation method can ensure that we take into account the inter-dependency of all the thermal features in the car. As for example, a large PHEV battery may need to be passively cooled by refrigerant, which is also associated with the interior Heating, Ventilation, and Air Conditioning (HVAC) cooling system. For proper sizing of the condenser, chiller etc., one has to account for the battery cooling and cabin cooling as one system. There are also many thermal actuators on a PHEV, e.g. control valves, pulse-width-module (PWM) pumps, electric compressor, electric coolant heaters etc.

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.

Automobiles have a high degree of mechanical and electrical complexity. However, product complexity has the accompanying effect of requiring high levels of design and process oversight. The net result is a product creation process which is prone to creating failures. These failures typically have their origin in an overall lack of complete understanding of the system in terms of materials, geometries and energy flows. Despite all of the engineering intentions, failures are inevitable, common, and must be dealt with accordingly. In the worst case, if a failure manifests itself into an observable failure the customer may have a negative experience. Therefore, it is imperative that design engineers, suppliers along with reliability professionals be able to assess the design risk. One approach to assess risk is the use of degradation analysis. Degradation analysis often provides more information than failure time data for assessing reliability and predicting the remnant life of a system.

As CAFE requirements increase, automotive OEMs are pursuing innovative methods to lightweight their Body In Whites (BIWs). Within FCA US, this lightweighting research and development activity often occurs through Decoupled Innovation projects. A Decoupled Innovation team comprised of engineers from the BIW Structures Group, in collaboration with Tier 1 supplier Magna Exteriors, sought to re-design a loadbearing component on the BIW that would offer significant weight savings when the current steel component was replaced with a carbon fiber composite. This paper describes the design, development, physical validation and partnership that resulted in a composite Rear Package Shelf Assembly solution for a high-volume production vehicle. As the CAFE requirements loom closer and closer, these innovation-driven engineering activities are imperative to the successful lightweighting of FCA US vehicles.