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In an engine system, the piston pin is subjected to high loading and severe lubrication conditions, and pin seizures still occur during new engine development. A better understanding of the lubricating oil behavior and the dynamics of the piston pin could lead to cost- effective solutions to mitigate these problems. However, research in this area is still limited due to the complexity of the lubrication and the pin dynamics. In this work, a numerical model that considers structure deformation and oil cavitation was developed to investigate the lubrication and dynamics of the piston pin. The model combines multi-body dynamics and elasto-hydrodynamic lubrication. A routine was established for generating and processing compliance matrices and further optimized to reduce computation time and improve the convergence of the equations. A simple built-in wear model was used to modify the pin bore and small end profiles based on the asperity contact pressures.

Three-piece oil control rings (TPOCR) are widely used in the majority of modern gasoline engines and they are critical for lubricant regulation and friction reduction. Despite their omnipresence, the TPOCRs’ motion and sealing mechanisms are not well studied. With stricter emission standards, gasoline engines are required to maintain lower oil consumption limits, since particulate emissions are strongly correlated with lubricant oil emissions. This piqued our interest in building a numerical model coupling TPOCR dynamics and oil transport to explain the physical mechanisms. In this work, a 2D dynamics model of all three pieces of the ring is built as the main frame. Oil transport in different zones are coupled into the dynamics model. Specifically, two mass-conserved fluid sub-models predict the oil movement between rail liner interface and rail groove clearance to capture the potential oil leakage through TPOCR. The model is applied on a 2D laser induced fluorescence (2D-LIF) engine.

As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

Topology of liner finish is critical to the performance of internal combustion engines. Proper liner finish simulation processes lead to efficient engine design and research. Fourier methods have been well studied to numerically generate liner topology. However, three major issues wait to be addressed to make the generation processes feasible and reliable. First, in order to simulate real plateau honed liners, approaches should be developed to calculate accurate liner geometric parameters. These parameters are served as the input of the generation algorithm. Material ratio curve, the common geometry calculation method, should be modified so that accurate root mean square of plateau height distribution could be obtained. Second, the set of geometric parameters used in generating liner finish (ISO 13565-2) is different from the set of parameters used in manufacturing industry (ISO 13565-3). Quantitative relations between these two sets should be studied.

In the development of fuel tank systems, it is important to maintain fuel system integrity even if a car accident occurs. When a fuel tank undergoes a sudden change in velocity, the fuel starts to move and deforms the tank walls and baffle plates, and then the deformation changes the flow pattern of fuel. Because interaction of fuel with tank components is the main cause of fuel spillage upon crash, it is important to predict complex fluid-structure interaction responses at an early stage of crash safety development with a multiphysics simulation. Development of the multiphysics simulation technique was conducted stepwise by examining “fluid motion” and “tank deformation.” First, a sled test of a rigid-wall tank with observation window was conducted to evaluate the fluid motion inside the tank. A numerical model was developed based on an ALE (Arbitrary Lagrangian Eulerian) algorithm for the fluid and a Lagrangian algorithm for the structure.

Improving turbocharger performance to increase engine efficiency has the potential to help meet current and upcoming exhaust legislation. One limiting factor is compressor surge, an air flow instability phenomenon capable of causing severe vibration and noise. To avoid surge, the turbocharger is operated with a safety margin (surge margin) which, as well as avoiding surge in steady state operation, unfortunately also lowers engine performance. This paper investigates the possibility of detecting compressor surge with a conventional engine knock sensor. It further recommends a surge detection algorithm based on their signals during transient engine operation. Three knock sensors were mounted on the turbocharger and placed along the axes of three dimensions of movement. The engine was operated in load steps starting from steady state. The steady state points of operation covered the vital parts of the engine speed and load range.

The compressor surge line of automotive turbochargers can limit the low-end torque of an engine. In order to determine how close the compressor operates to its surge limit, the Hurst exponent of the pressure signal has recently been proposed as a criterion. The Hurst exponent quantifies the fractal properties of a time series and its long-term memory. This paper evaluates the outcome of applying Hurst exponent based criterion on time-resolved pressure signals, measured simultaneously at different locations in the compression system. Experiments were performed using a truck-sized turbocharger on a cold gas stand at the University of Cincinnati. The pressure sensors were flush-mounted at different circumferential positions at the inlet of the compressor, in the diffuser and volute, as well as downstream of the compressor.

To improve fuel efficiency and facilitate handling of the vehicle in a dense city environment, it should be as small as possible given its intended application. This downsizing trend impacts the size of the engine bay, where the air filter box has to be packed in a reduced space, still without increased pressure drop, reduced load capacity nor lower filtering efficiency. Due to its flexibility and reduced cost, CFD simulations play an important role in the optimization process of the filter design. Even though the air-flow through the filter box changes as the dust load increases, the current modeling framework seldom account for such time dependence. Volvo Car Corporation presents an industrial affordable model to solve the time-dependent dust load on filter elements and calculate the corresponding flow behavior over the life time of the air filter box.

A Multi-Objective Optimization (MOO) problem concerning the thermal control problem of Multifunctional Structures (MFSs) is here addressed. In particular the use of Multi-Objective algorithms from an optimization tool and Self-Organizing Maps (SOM) is proposed for the identification of the optimal topological distribution of the heating components for a multifunctional test panel, the Advanced Bread Board (ABB). MFSs are components that conduct many functions within a single piece of hardware, shading the clearly defined boundaries that identify traditional subsystems. Generally speaking, MFSs have already proved to be a disrupting technology, especially in aeronautics and space application fields. The case study exploited in this paper refers to a demonstrator breadboard called ABB. ABB belongs to a particular subset of an extensive family of MFS, that is, of thermo-structural panels with distributed electronics and a health monitoring network.

An extravehicular activity (EVA) path-planning and navigation tool, called the Mission Planner, has been developed to assist with pre-mission planning, scenario simulation, real-time navigation, and contingency replanning during astronaut EVAs, The Mission Planner calculates the most efficient path between user-specified waypoints. Efficiency is based on an exploration cost algorithm, which is a function of the estimated astronaut metabolic rate. Selection of waypoints and visualization of the generated path are realized within a 3D mapping interface through terrain elevation models. The Mission Planner is also capable of computing the most efficient path back home from any point along the path.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

A unified approach to collision warning due to in-lane and neighboring traffic is presented. It is based on the concept of velocity obstacles, and is designed to alert the driver of a potential front collision and against attempting a dangerous lane change maneuver. The velocity obstacle represents the set of the host velocities that would result in collision with the respective static or moving vehicle. Potential collisions are simply determined when the velocity vector of the host vehicle penetrates the velocity obstacle of a neighboring vehicle. The generality of the velocity obstacle and its simplicity make it an attractive alternative to competing warning algorithms, and a powerful tool for generating collision avoidance maneuvers. The velocity obstacle-based warning algorithm was successfully tested in simulations using real sensor data collected during the Automotive Collision Avoidance System Field Operational Test (ACAS FOT) [10].

The present study had two aims: (1) to develop a model which reproduced the dummy lower leg kinematics observed in a high-speed test, and (2) to develop a methodology to assess various theoretical design parameters of a heel foam pad to reduce the risk of the lower extremity injuries. To address the first aim, a MADYMO sled simulation model was developed. The interior parts were represented mainly with finite element (FE) models, with intent to capture deformations and the reaction force directions. Moreover, the occupant responses were estimated from the refined version of the dummy model (i.e., the Hybrid III model; Q dummy model). The model was acceptably correlated to experiments. To address the second aim, the model was simplified for subsequent optimization of the heel foam pad.

Continuous improvement of side airbag safety performance is an important step because it is associated with many public domain tests and regulations. Thus, occupant restraint with a side airbag is critical and it is necessary to develop tools that can be utilized to help in design of side airbags. Though many papers on side impact safety have been published, only a few papers are related to MADYMO simulations of side airbags. This paper describes an improved injury prediction and optimization approach using a MADYMO model for side impact. This model consists of 3 parts: dummy, trim and airbag in FEM. In this study, a side impact with a ES-2, EuroSID-2, was simulated in MADYMO as follows: First, component tests were conducted for trim and airbag respectively to establish correlation. Second, these component models were then integrated into a MADYMO model, which has high correlation with a crash simulator that is capable of replicating physical vehicle tests.

This paper presents a comprehensive Matlab/Simulink-based framework that affords a rapid, systematic, and efficient engine control system development process including automated code generation. The proposed framework hinges on three essential pillars: 1 ) an accurate model for the target engine, 2) a toolset for systematic control design, and 3) a modular system architecture that enhances feature reusability and rapid algorithm deployment. The proposed framework promotes systematic model-based algorithm development and validation in virtual reality. Within this context, the framework affords integration and evaluation of the entire control system at an early development stage, seamless transitions across inherently incompatible product development stages, and rapid code generation for production target hardware.

The fierce competition and shifting consumer demands require automotive companies to be more efficient in all aspects of vehicle development and specifically in the area of embedded engine control system development. In order to reduce development cost, shorten time-to-market, and meet more stringent emission regulations without sacrificing quality, the increasingly complex control algorithms must be transportable and reusable. Within an efficient development process it is necessary that the algorithms can be seamlessly moved throughout different development stages and that they can be easily reused for different applications. In this paper, we propose a flexible engine control architecture that greatly boosts development efficiency.

The value of model-based design has been attempted to be communicated for more than a decade. As methods and tools have appeared and disappeared from a series of different vendors it has become apparent that no single vendor has a solution that meets all users’ needs. Recently standards (UML, MDA, MOF, EMF, etc.) have become a dominant force and an alternative to vendor-specific languages and processes. Where these standards have succeeded and vendors have failed is in the realization that they do not provide the answer, but instead provide the foundation to develop the answer. It is in the utilization of these standards and their capability to be customized that companies have achieved success. Customization has occurred to fit organizations, processes, and architectures that leverage the value of model-driven design.

In GM R&D Powertrain/Engine Control Group, rapid prototyping controller (RPC) systems with Matlab/Simulink are used extensively to design, simulate and implement advanced engine control algorithms and models. However, those RPC systems use powerful microprocessors with large amounts of RAM contrary to engine control modules (ECM) in production vehicles. Therefore, a thorough analysis on the comparatively much more complicated algorithms and models cannot be performed during the research stage, since there are not enough tools to enable the smooth transition from Matlab/Simulink to the production type processor. The Real-Time Interface (RTI) Blockset for a production like microprocessor would close the transition gap between rapid prototyping controller systems and production type microprocessors by leveraging the power and popularity of Matlab/Simulink in control engineering world and automatic code generation tools.

This paper presents a pioneer work and first time application of Multi Objective Robust Optimization to analytically improve Idle Shake Performance. The method is developed to obtain a robust design with multiple objectives under consideration along with managing material property variation. It was a Robust Optimization on top of Multi Objective Genetic Algorithm, Robu-MOGA. The design variables in the study included the nominal values and tolerances of Sound Transmission Loss property, and interior material Absorption property. The analytical objective was not only to minimize the peak airborne noise at each specified frequency, but also to reduce the total cost and the total mass of the materials. In the study, AutoSEA (statistical energy analysis) from ESI Software, Inc. was used as the solver. AutoSEA was integrated with iSIGHT from Engineous Software, Inc.