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The initial presence and dynamic formation of internal voids in human body models have been subjects of discussion within the human body modeling community. The relevant physics of the human body are described and the importance of capturing this physics for modeling of internal organ interactions is demonstrated. Basic modeling concepts are discussed along with a proposal of simulation setups designed to verify model behavior in terms of volume and pressure between internal organs.

Internal organ injuries of the chest are one of the leading causes of deaths in motor vehicle crashes. The issue of initial presence and dynamic formation of voids around the heart and aorta is addressed to improve kinematics, force interaction and injury risk assessment of these organs of the Global Human Body Model. Steps to fill the voids are presented.

Trivial Principal Component method (TPC) was developed recently to model a system based on measured data. It is a statistical method that utilizes Eigen-pairs of covariance matrix obtained from the measured data. It determines linear coefficients of a model by using the trivial eigenvector corresponding to the least eigenvalue. In general, linear modeling accuracy depends on the strength of nonlinearity and interaction terms as well as measurement error. In this paper, the TPC method is extended to analyze residual (error) vector to identify significant higher order and interaction terms that contribute to the modeling error. Subsequently, these additional terms are included for constructing a robust system model. Also, an iterative TPC analysis is proposed for the first time to correct the model gradually till the least eigenvalue becomes minimum.

Driver out-of-position (OOP) tests were developed to evaluate the risk of inflation induced injury when the occupant is close to the airbag module during deployment. The Hybrid III 5th percentile female Anthropomorphic Test Device (ATD) measures both sternum displacement and chest acceleration through a potentiometer and accelerometers, which can be used to calculate sternum compression rate. This paper documents a study evaluating the chest accelerometers to assess punch-out loading of the chest during this test configuration. The study included ATD mechanical loading and instrumentation review. Finite element analysis was conducted using a Hybrid III - 5th percentile female ATD correlated to testing. The correlated restraint model was utilized with a Hybrid III - 50th percentile male ATD. A 50th percentile male Global Human Body Model (HBM) was then applied for enhanced anatomical review.

Engine acoustics measured by microphones near the engine have been used in controlled laboratory settings for combustion feedback and even combustion phasing control, but the use of these techniques in a vehicle where many other noise sources exist is problematic. In this study, surface-mounted acoustic emissions sensors are embedded in the block of a 2.0L turbocharged GDI engine, and the signal is analyzed to identify useful feedback features. The use of acoustic emissions sensors, which have a very high frequency response and are commonly used for detecting material failures for health monitoring, including detecting gear pitting and ring scuffing on test stands, enables detection of acoustics both within the range of human hearing and in the ultrasonic spectrum. The high-speed acoustic time-domain data are synchronized with the crank-angle-domain combustion data to investigate the acoustic emissions response caused by various engine events.

A pilot-main injection strategy is investigated for a part-load operating point in a single cylinder optical Diesel engine. As the energizing dwell between the pilot and main injections decreases below 200 μs, combustion noise reaches a minimum and a reduction of 3 dB is possible. This decrease in combustion noise is achieved without increased pollutant emissions. Injection schedules employed in the engine are analyzed with an injection analyzer to provide injection rates for each dwell tested. Two distinct injection events are observed even at the shortest dwell tested; rate shaping of the main injection occurs as the dwell is adjusted. High-speed elastic scattering imaging of liquid fuel is performed in the engine to examine initial liquid penetration rates.

General Motors has developed an all-new Ecotec 1.5 L range extender engine for use in the 2016 next generation Voltec propulsion system. This engine is part of a new Ecotec family of small displacement gasoline engines introduced in the 2015 model year. Major enhancements over the range extender engine in the current generation Voltec propulsion system include the adoption of direct injection (DI), cooled external exhaust gas recirculation (EGR), and a high 12.5:1 geometric compression ratio (CR). Additional enhancements include the adoption of high-authority phasers on both the intake and exhaust camshafts, and an integrated exhaust manifold (IEM). The combination of DI with cooled EGR has enabled significant thermal efficiency gains over the 1.4 L range extender engine in the current generation Voltec propulsion system at high engine loads.

The introduction of new safety critical features using software-intensive systems presents a growing challenge to hazard analysis and requirements development. These systems are rich in feature content and can interact with other vehicle systems in complex ways, making the early development of proper requirements critical. Catching potential problems as early as possible is essential because the cost increases exponentially the longer problems remain undetected. However, in practice these problems are often subtle and can remain undetected until integration, testing, production, or even later, when the cost of fixing them is the highest. In this paper, a new technique is demonstrated to perform a hazard analysis in parallel with system and requirements development. The proposed model-based technique begins during early development when design uncertainty is highest and is refined iteratively as development progresses to drive the requirements and necessary design features.

This paper discusses observability of the vehicle states using different sensor configurations as well as fault-tolerant estimation of these states. The optimality of the sensor configurations is assessed through different observability measures and by using a 3-DOF linear vehicle model that incorporates yaw, roll and lateral motions of the vehicle. The most optimal sensor configuration is adopted and an observer is designed to estimate the states of the vehicle handling dynamics. Robustness of the observer against sensor failure is investigated. A fault-tolerant adaptive estimation algorithm is developed to mitigate any possible faults arising from the sensor failures. Effectiveness of the proposed fault-tolerant estimation scheme is demonstrated through numerical analysis and CarSim simulation.

This study concerns the generation of response surfaces for kinematics and injury prediction in pedestrian impact simulations using human body model. A 1000-case DOE (Design of Experiments) study with a Latin Hypercube sampling scheme is conducted using a finite element pedestrian human body model and a simplified parametric vehicle front-end model. The Kriging method is taken as the approach to construct global approximations to system behavior based on results calculated at various points in the design space. Using the response surface models, human lower limb kinematics and injuries, including impact posture, lateral bending angle, ligament elongation and bone fractures, can be quickly assessed when either the structural dimensions or the structural behavior of the vehicle front-end design change. This will aid in vehicle front-end design to enhance protection of pedestrian lower limbs.

Model-Based Development processes in the automotive industry typically use high-level modeling languages to build the reference models of embedded controllers. One can use formal verification tools to exhaustively verify these design models against their requirements, ensuring high quality models and a reduction in the cost and effort of functional testing. However, there is a gap, in terms of processes and tools, between the informal requirements and the formal specifications required by the verification tools. In this paper, we propose an approach that tries to bridge this gap by (i) identifying the verifiable requirements through a categorization process, (ii) providing a set of templates to easily express the verifiable requirements, and (iii) generating monitors that can be used as specifications in design verification tools. We demonstrate our approach using the Simulink Design Verifier tool for design verification of Simulink/Stateflow models.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

One of the major problems that the automotive industry faces is reducing friction to increase efficiency. Researchers have shown that 30% of the fuel energy was consumed to overcome the friction forces between the moving parts of any automobile, Holmberg et al. [1]. The interface of the piston pin and pin bore is one of the areas that generate high friction under severe working conditions of high temperature and lack of lubrication. In this research, experimental investigation and theoretical simulation have been carried out to analyze the motion of the floating pin against pin bore. In the experimental study, the focus was on analyzing the floating pin motion by using a bench test rig to simulate the floating pin motion in an internal combustion engine. A motion data acquisition system was developed to capture and record the pin motion. Thousands of images were recorded and later analyzed by a code written by MATLAB.

The light-medium load operating range (4-7 bar net IMEP) presents many challenges for advanced low temperature combustion strategies utilizing low cetane fuels (specifically, 87-octane gasoline) in light-duty, high-speed engines. The overly lean overall air-fuel ratio (Φ≺0.4) sometimes requires unrealistically high inlet temperatures and/or high inlet boost conditions to initiate autoignition at engine speeds in excess of 1500 RPM. The objective of this work is to identify and quantify the effects of variation in input parameters on overall engine operation. Input parameters including inlet temperature, inlet pressure, injection timing/duration, injection pressure, and engine speed were varied in a ~0.5L single-cylinder engine based on a production General Motors 1.9L 4-cylinder high-speed diesel engine.

In recent years, there has been a growing interest in driver visibility. This is, in part, due to increasing emphasis placed on design factors influencing visibility such as: aerodynamics, styling, structural stiffness and vehicle packaging. During the development process of a vehicle, it is important to be able to quantify all of these factors. Visibility, however, owing to its sensory nature, has been harder to quantify. As a result, General Motors (GM) has undertaken a study to gain deeper insight into customer perceptions surrounding visibility. Clinics were conducted to help determine the relative importance of different metrics. The paper also explores several new metrics that can help predict customer satisfaction based on vehicle configuration.

A numerical and corresponding experimental study was undertaken to identify the ability to accurately predict combustion performance using our 3-D numerical tools for a direct-injection homogeneous-charge engine. To achieve a significant range of combustion rates, the evaluation was conducted for the engine operating with and without enhanced charge motion. Five charge motion configurations were examined, each having different levels of swirl and tumble flow leading to different turbulence generation and decay characteristics. A detailed CFD analysis provides insight into the in-cylinder flow requirements as well as the accuracy of the submodels. The in-cylinder air-fuel distribution, the mass-averaged swirl and tumble levels along with mean flow and turbulent kinetic energies are calculated throughout the induction and compression processes.

Determining Li-ion battery life through life modeling is an excellent tool in determining and estimating end-of-life performance. Achieving End-of-Life (EOL) can be challenging since it is difficult to achieve both cycle and calendar life during the same test without years of testing. The plan to correlate testing with the model included three (3) distinct temperature ranges, beginning with the four-Season temperature profile, an aggressive profile with temperatures in the 50 to 55°C range, and using a mid-temperature range (40-45°C) as a final comparison test. A high duty-cycle drive profile was used to cycle all of the batteries as quickly as possible to reach the one potential definition of EOL; significant increases in resistance or capacity fade.

Developing a robust model that can simulate all real world conditions a vehicle can experience can be extremely difficult to predict. When working through the engineering process, Computer Aided Engineers (CAE) traditionally set modeling parameters and conditions to a nominal setting. This is done to simplify the models so that it avoided inputting too much tedious details into the system and wasting so much engineering time preparing the work. It was soon realized that this strategy did not capture all the possible conditions a hood on a vehicle could experience. There was a need to develop a formal approach and method to correlate an analysis model to real world conditions. The Design for Six Sigma (DFSS) process was utilized to develop robustness in the techniques used to accurately understand the vehicle environment. The DFSS process is normally used to design and develop robustness into physical parts.

Simscape is a physical modeling language developed by Mathworks Inc. The language uses equation statements instead of assignment statements to describe physical systems. The paper focuses on the Simscape language itself instead of using components in the Simscape libraries. The language will be introduced from a perspective different from the Mathworks' Physical Network point of view. Our perspective focuses on two types of variables at the connectors. In additional, internal variables are not separated into through and across variables. The alternative perspective is more general and easier to understand. The paper also illustrates how to develop components in a powertrain library following the proposed new perspective.

A Design for Six Sigma (DFSS) statistical approach is presented in this report to correlate a CFD cabin model with test results. The target is the volume-averaged hot-soak terminal temperature. The objective is to develop an effective correlation process for a simplified CFD cabin model so it can be used in practical design process. It is, however, not the objective in this report to develop the most accurate CFD cabin model that would be too expensive computationally at present to be used in routine design analysis. A 3-D CFD model of a vehicle cabin is the central part of the computer modeling in the development of automotive HVAC systems. Hot-soak terminal temperature is a thermal phenomenon in the cabin of a parked vehicle under the Sun when the overall heat transfer reaches equilibrium. It is often part of the simulation of HVAC system operation.