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Cast austenitic stainless steels, such as 1.4837Nb, are widely used for turbo housing and exhaust manifolds which are subjected to elevated temperatures. Due to assembly constraints, geometry limitation, and particularly high temperatures, thermomechanical fatigue (TMF) issue is commonly seen in the service of those components. Therefore, it is critical to understand the TMF behavior of the cast steels. In the present study, a series of fatigue tests including isothermal low cycle fatigue tests at elevated temperatures up to 1100°C, in-phase and out-of-phase TMF tests in the temperature ranges 100-800°C and 100-1000°C have been conducted. Both creep and oxidation are active in these conditions, and their contributions to the damage of the steel are discussed.

Complex chassis systems operate in various environments such as low-mu surfaces and highly dynamic maneuvers. The existing metrics for lateral motion hazard by Neukum [13] and Amberkar [17] have been developed and correlated to driver behavior against disturbances on straight line driving on a dry surface, but do not cover low-mu surfaces and dynamic driving scenarios which include both linear and nonlinear region of vehicle operation. As a result, an improved methodology for evaluating vehicle yaw dynamics is needed for safety analysis. Vehicle yaw dynamics safety analysis is a methodical evaluation of the overall vehicle controllability with respect to its yaw motion and change of handling characteristic.

General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants.

Accelerating product development cycles and incentives to reduce costs in product development are strong motivators to move to virtual development and validation processes. Challenges to moving to a virtual paradigm include a wealth of historical data and context for hardware tests, uncertainty over dependencies, and a lack of a clear path of transition to virtual methods. In this paper we will discuss approaches to understanding the value created by hardware tests and aligning that value to virtual processes. We will also discuss the need for a virtual context to be added to SAE J1739 [1] (DFMEA detection criteria), and how to create paths to maximize the value of virtual assessments. Finally, we will also discuss the cultural and organizational changes required to support.

As passenger vehicle design evolves and accelerates, the use of multi-body dynamics solvers has proven to be invaluable in the engineering workflow. MBD solvers allow engineers to build virtual vehicle models that can accurately simulate vehicle responses and calculate internal forces, which previously could only be assessed using physical prototype builds with hundreds of measurement transducers. Evaluation and selection of solvers within an engineering environment is inherently a multi-dimensional activity that can include ease of use, retention of previously developed expertise, accuracy, speed, and integration with existing analysis processes. We discuss here some of the challenges present in developing capability and accumulating data to support each of these criteria. Developing a pilot model that is capable of being applied to a comprehensive set of use cases, and then verifying those use cases, required significant project management activity.

The world is moving towards E-mobility solutions and Battery Electric Vehicles (BEVs) are the main enabler towards it. Li-ion cells are the fundamental building block of any BEVs. There are three common types of Li-ion cell design i.e., cylindrical cells, Prismatic Cells and Pouch cells. Ensuring safety of BEVs are critical to gain customer trust and acceptance over Internal Combustion Engine (ICE) vehicles. EV fire is found to be one of the major concerns related to using higher energy batteries. During a crash event, Post-Crash Electrical Integrity of the BEV is to be ensured and hence primary focus is on mitigation of Li-ion cell internal short circuit. It has been seen in prior published articles that cell internal short circuit can be triggered by physical intrusion of cell. This paper primarily focusses on simulating the mechanical behavior of cylindrical cell under various crush conditions.

Torque ripple from electric motor can excite a system resonance perceived as vibration at the vehicle seat track. The CAE simulation procedure was applied to analyze the seat track acceleration excited by electric motor torque ripple. In this study, the transfer function between the electric motor torque and vehicle level seat track acceleration was developed, and it incorporates the control capability and vehicle sensitivity subfunctions. The motor level torque ripple requirement was developed, which can support motor design in early vehicle development stage based on vehicle level criteria. The analysis results obtained for motor level torque ripple requirement shows good agreement with the experimental validation using vehicle test data. The variation study on control capability and vehicle sensitivity was investigated, and the results can help to identify the solution to improve vehicle torque ripple response.

Stamped components play an important role in supporting various sub-systems within a typical engine and transmission assembly. In some cases, the stamped components will not initially meet the design criteria, and material may need to be added to strengthen it. However, in other cases the component may be overdesigned, and there will be opportunities to reduce mass while still meeting all design criteria. In this latter case, multiple CAE simulations are often performed to enhance the component design by varying design parameters such as thickness, bend radius, material, etc., The conventional process will assess changes in one parameter at a time, while holding other parameters constant. Though this helps in meeting the design criteria, it is often very difficult to produce the best optimized design within the limited time span with this approach. With the aid of Altair-HyperMorph techniques, multiple design parameters can be varied simultaneously.

Vehicle manufacturers conduct tests to develop crash sensing system calibrations. Ditch fall-over is one of a suite of laboratory tests used to develop rollover sensing calibrations that can trigger deployment of safety devices like roof rail airbags and seat belt pretensioners. The ditch fall-over test simulates a flat road followed by a ditch on one side of the road. The vehicle heads into the ditch and the driver applies swift steer input once the ditch slope is sensed. Typically, the steer input is applied when the two down-slope wheels on the ditch side enter the ditch. Multi-Body Dynamics (MBD) software can be used for virtual simulation of these test events. Conventionally in simulations, the vehicle-model is run without steer input and the marking line crossing time is observed/manually recorded from observation of simulation video. This recorded time is used to apply the steer input and the full event is then re-simulated.

The main objective of crash sensing is to predict a vehicle collision early in the event and command vehicle’s occupant protection systems to take appropriate actions to reduce the severity of crash injury. Currently Computer Aided Engineering (CAE) models are being used to predict the sensing signals with sensors placed at front end structure of the vehicle. The front-end structure as well as other critical components packaged in the front end play important role in absorbing energy and provide sensing signals during impact, headlamp being one such critical components. The headlamp with its lens being the exterior surface, experience large magnitude of loads from barrier during full frontal, angled and offset impact. The impact with barrier usually results in scattered damage to the headlamp and its lens. In this paper, CAE model of headlamp has been improved to reflect similar deformation pattern as observed in physical tests.

Remote Function Actuator (RFA) systems are widely used as the standard solution for conveniently accessing vehicles by remote control. To accelerate product development cycles and reduce engineering costs of physical test, a computer aided engineering (CAE) method has been developed to predict transmission range of the RFA system. Firstly, the detailed computational electromagnetic (CEM) models of the transmitting and receiving antennas were developed. Secondly, the articulated human model and the full vehicle meshed model were introduced to the CEM models to reflect the physical test environment. Lastly, the RFA system range model was built by including both the key fob held by an articulated human body and RFA module installed in the fully meshed vehicle. The transmission range could be extracted when the simulated received power reached the receiving sensitivity of the RFA module.

Turbochargers are widely employed in internal combustion engines, in both, diesel and gasoline vehicle, to boost the power without any extra fuel usage. Turbocharger comes in different sizes based upon the boost pressure to increase. Capacity of turbocharger are available in great range in the market which are designed to match the requirement. From structural point of view, key component of an automotive turbocharger is rotor. This rotor consists of compressor wheel, turbine wheel, shaft and bearing (journal/ball) mainly. In industries, design & development of turbocharger rotor for its dynamic characteristics is done using virtual engineering technique (Computer Aided Engineering). Multibody dynamic (MBD) analysis simulation is one of the best approaches which is used to study the rotor in great details. In this current MBD procedure fluid-structure interaction problem is solved by modelling oil film in the journal bearing and solving it using “Reynolds equation”.

A computational study based on unsteady Reynolds-Averaged-Navier-Stokes that resolves the gas-liquid interface was performed to examine the unsteady multiphase flow in a 4 cylinder Inline (i-4) engine. In this study, the rotating motion of the crankshaft and reciprocating motion of the pistons were accounted for to accurately predict the oil distribution in various parts of the engine. Three rotational speeds of the crankshaft have been examined: 1000, 2800, and 4000 rpm. Of particular interest is to examine the mechanisms governing the process of oil drawdown from the engine head into the case. The oil distributions in other parts of the engine have also been investigated to understand the overall crankcase breathing process. Results obtained show the drawdown of oil from the head into the case to be strongly dependent on the venting strategy for the foul air going out of the engine through the PCV system.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

Most of the applications of magnesium in lightweighting commercial cars and trucks are die castings rather than sheet metal, and automotive applications of magnesium sheet have typically been experimental or low-volume serial production. The overarching objective of this collaborative research project organized by the United States Automotive Materials Partnership (USAMP) was to develop new low-cost magnesium alloys, and demonstrate warm-stamping of magnesium sheet inner and outer door panels for a 2013 MY Ford Fusion at a fully accounted integrated component cost increase over conventional steel stamped components of no more than $2.50/lb. saved ($5.50/kg saved). The project demonstrated the computational design of new magnesium (Mg) alloys from atomistic levels, cast new experimental alloy ingots and explored thermomechanical rolling processes to produce thin Mg sheet of desired textures.

The automotive industry is continuously striving to reduce vehicle mass by reducing the mass of components including wheel bearings. A typical wheel bearing assembly is mostly steel, including both the wheel and knuckle mounting flanges. Mass optimization of the wheel hub has traditionally been accomplished by reducing the cross-sectional thickness of these components. Recently bearing suppliers have also investigated the use of alternative materials. While bearing component performance is verified through analysis and testing by the supplier, additional effects from system integration and performance over time also need to be comprehended. In a recent new vehicle architecture, the wheel bearing hub flange was reduced to optimize it for low mass. In addition, holes were added for further mass reduction. The design met all the supplier and OEM component level specifications.

Fatigue failure is one of the major failure modes for internal combustion engines, especially with reduction in engine size and increase in combustion pressure and operating temperature. Dynamometer tests are devised to ensure engine durability for high and low cycle fatigue. With the advent of CAE technology, the dynamometer test behavior can be simulated using CAE analysis and engine durability can be assessed. The data generated in CAE analyses can be used to predict failure of the engines or future engine design modifications. The present paper has two parts - first is running finite element analysis (FEA) to get stress, strain data and running high cycle fatigue analysis to get safety factors and second is creating a predictive tool to assess failures using data from the first part as inputs. Using advancements in the field of machine learning, the paper presents use of support vector machine (SVM) algorithm to predict failure of the engine based on inputs.

Casting is the ability to let users transfer their favorite videos, music, movies, etc. from their phone to a chosen display. This functionality has become very popular these days, and to the user, it is as simple as clicking a button. This “simple” task is a complex system that requires various independent sources to communicate efficiently and effectively to produce a robust and reliable output. The sending and receiving devices are required to be on the same network - which involves reliable and secure connection. This allows the sending of the URL of the chosen feature to the server provider, which will then connect to the receiver embedded electronics where the authentication process that protects Digital Rights Management (DRM) is established. In the era of developing autonomous and luxury vehicles, this technology has the potential to add a new dimension of in-vehicle entertainment that could come very close to the home experience.

Automated driving systems (ADS) are one of the key modern technologies that are changing the way we perceive mobility and transportation. In addition to providing significant access to mobility, they can also be useful in decreasing the number of road accidents. For these benefits to be realized, candidate ADS need to be proven as safe, robust, and reliable; both by design and in the performance of navigating their operational design domain (ODD). This paper proposes a multi-pronged approach to evaluate the safety performance of a hypothetical candidate system. Safety performance is assessed through using a set of test cases/scenarios that provide substantial coverage of those potentially encountered in an ODD. This systematic process is used to create a library of scenarios, specific to a defined domain. Beginning with a system-specific ODD definition, a set of core competencies are identified.

Cast Al-Si alloys are widely used in automotive industry to produce structural components, such as engine block and cylinder head, because of the increasing demands in reducing mass for improved fuel efficiency. The fatigue performance of the castings is critical in their application. Porosity is highly detrimental to the fatigue behavior of cast Al-Si alloys. Therefore, accurate measurement of pore sizes is important in order to develop the correlations between porosity and fatigue strength. However, quantification of porosity is challenging and shows large variation depending on the measurement methods, particularly for micro-shrinkage porosity due to the torturous and complex morphology. The conventional metallographic image analysis method in the 2D polished surface often underestimates the actual pore size particularly when the porosity morphology is complex.