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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.

An actual trend in the automotive industry is to have global products in order to have economy of scale. This paper presents how a Belt Drive Rack EPS developed for the North American market had to be modified in order to be assembled in a Vehicle sold all around the world. Main technical challenges for achieving that goal were generated from different Architectures, whether electrical or mechanical, used in each vehicle, Packaging issues and Regional Requirements. Main features affected are Database Configuration, Electromagnetic Compatibility, Smooth Road Shake mitigation and Pull Compensation.

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.

The die wear up to 80,800 hits on a prog-die setup for bare DP1180 steel was investigated in real production condition. In total, 31 die inserts with the combination of 11 die materials and 9 coatings were evaluated. The analytical results of die service life for each insert were provided by examining the evolution of surface wear on inserts and formed parts. The moments of appearance of die defects, propagation of die defects, and catastrophic failure were determined. Moreover, the surface roughness of the formed parts for each die insert was characterized using Wyko NT110 machine. The objectives of the current study are to evaluate the die durability of various tooling materials and coatings for flange operations on bare DP 1180 steel and update OEM tooling standards based on the experimental results. The current study provides the guidance for the die material and coating selections in large volume production for next generation AHSSs.

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.

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.

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.

With deflected-disc dampers, digressive force-velocity shapes are achieved via the combined effects of disc stack stiffness and hub-offset. The degree of digressiveness can be adjusted to alter vehicle performance by changing the proportion of these parameters. Optimizing this relationship can yield substantial vehicle performance improvements, but the time consuming iterative process of developing a new disc stack for each hub-offset discourages experimentation. To enable more efficient digressiveness comparisons, a regression-based computational method has been developed which converts disc stack stiffness from one hub-offset to other offsets directly, without iteration. Once an initial disc stack for one offset has been tuned by traditional methods, stacks for other offsets can be calculated that maintain overall damper control.

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].

Numerical results are presented for simulating buoyancy driven flow in a simplified full-scale underhood with open enclosure in automobile. The flow condition is set up in such a way that it mimics the underhood soak condition, when the vehicle is parked in a windbreak with power shut-down after enduring high thermal loads due to performing a sequence of operating conditions, such as highway driving and trailer-grade loads in a hot ambient environment. The experimental underhood geometry, although simplified, consists of the essential components in a typical automobile underhood undergoing the buoyancy-driven flow condition. It includes an open enclosure which has openings to the surrounding environment from the ground and through the top hood gap, an engine block and two exhaust cylinders mounted along the sides of the engine block. The calculated temperature and velocity were compared with the measured data at different locations near and away from the hot exhaust plumes.

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 effects of using blended renewable diesel fuel (30% vol.), obtained from Rapeseed Methyl Ester (RME) and Hydrotreated Vegetable Oil (HVO), in a Euro 5 small displacement passenger car diesel engine have been evaluated in this paper. The hydraulic behavior of the common rail injection system was verified in terms of injected volume and injection rate with both RME and HVO blends fuelling in comparison with commercial diesel. Further, the spray obtained with RME B30 was analyzed and compared with diesel in terms of global shape and penetration, to investigate the potential differences in the air-fuel mixing process. Then, the impact of a biofuel blend usage on engine performance at full load was first analyzed, adopting the same reference calibration for all the tested fuels.

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.

The U.S. Renewable Fuel Standard 2 (RFS2) mandates the use of advanced renewable fuels such as cellulosic ethanol to be blended into gasoline in the near future. As such, determining the impact of these new fuel blends on vehicle performance is important. Therefore, General Motors conducted engine dynamometer evaluations on the impact of cellulosic ethanol blends on port fuel injected (PFI) intake valve deposits and gasoline direct injected (GDI) fuel injector plugging. Chemical analysis of the test fuels was also conducted and presented to support the interpretation of the engine results. The chemical analyses included an evaluation of the specified fuel parameters listed in ASTM International's D4806 denatured fuel ethanol specification as well as GC/MS hydrocarbon speciations to help identify any trace level contaminant species from the new ethanol production processes.

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.

Generally linear finite element analysis (FEA) is used to predict fatigue life of spot welded joints in a vehicle body structure. Therefore, the effect of plastic deformation at the vicinity of the spot welded joints is not included on fatigue prediction. This study introduces a simple technique to include the plastic deformation effect without performing elastic-plastic finite element analysis. The S-N curve obtained from fatigue test results is modified to consider this effect. Tensile strength test results of spot welded joint specimens were utilized to find the load range for FEA equivalent to the applied load range for fatigue tests. To demonstrate the proposed approach, fatigue test results of advanced high strength steels (AHSS) for lap-shear and coach peel specimens were used. Both the specimen types were tested at various constant amplitudes with the load ratios of R=0.1 and 0.3.

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.