Search Results

This paper summarizes results from the author's work on friction in dry sliding contacts in the presence of vibration. A number of idealized models of smooth and rough contacts are examined. It is shown that vibration can cause up to a 10% reduction in average friction even with continuous contact. A larger reduction in friction occurs when there is intermittent contact loss. This is found to be true for both elastic and plastic contacts, and for adhesive and plowing mechanisms of friction. The results of this work are compared and validated with measurements from experiments. The results presented are fundamental, but applicable to machine components with contacts including brake systems.

The RFID on Parts Project Team has recently completed and approved Spec 2000 Chapter 9, “RFID on Parts”. Once approved by the ATA e-Business Steering Group, this standard will allow for archiving and sharing part history information directly on RFID tags using the User Memory Bank. Using a structure similar to a File Storage System, this standard organizes tag data in a structured and indexed system so that information can be shared among all members of the supply chain. Now that high memory, passive tags are becoming available, when used in conjunction with the “RFID on Parts” standard, they make it possible to tag parts not just with an identification number, but with birth records, a full history of maintenance activities and user archives. Since end users and maintenance organizations will no longer need to rely solely on information retrieved from a centralized database, new processes and efficiencies can be realized.

Complexity and nonlinearity of engines makes precise first principle engine models often difficult to obtain, as for instance for emissions. System identification is a well known possible alternative, successfully used in several automotive applications. In most cases system identification is concerned with the estimation of the unknown parameters of a known set of equations. Unfortunately, for many engine subsystems, there is no sufficiently precise or real time suitable model. This paper presents a sequential algorithm which allows to derive real time suitable models on line by a combination of model structure hypothesis of increasing complexity and an associated optimal input design and selection process. This paper introduces the method and shows its use both for a rather simple and a very difficult engine identification task, a dynamical model of the airpath of a Diesel engine and a dynamical model of nitrogen oxides and particulate matter.

A method for identification of object impact location and bumper stiffness curve is presented in this paper. The method calculates an offset distance of object impact based on intrusions obtained from three accelerometers mounted in the bumper fascia. The method also evaluates a center strength based on an absolute sum of acceleration. A characteristic line has been introduced in a two-dimensional domain consisting of intrusion-based offset and center strength. When test data are projected onto the characteristic line, an improved object impact location can be achieved. An intrusion curve over offset distance is obtained for impact tests striking at different locations with the same object and same speed. Then, a bumper stiffness curve can be identified by taking a reciprocal of the intrusion curve. This study shows a bumper stiffness curve can be used for an impact object classification for the pedestrian protection system.

The advancements made in modeling and parameter identification of nonlinear isolation components in the underlying investigation confirm the importance of accurate Multibody Dynamics modeling of these components for reducing vibration and/or improving ride comfort. Considering dynamic stiffness and loss angle characteristics, the proposed nonlinear isolation component uses the Bouc/Wen hysteresis model for excitation amplitude dependency and a transfer function for excitation frequency dependency. Various combinations of Bouc/Wen hysteresis parameters result in different shapes for hysteresis loops and allows for modeling a wide range of soft and stiff isolator characteristics. The effect of the proposed isolation component on ride studies is illustrated by simulating a maneuver on a road profile using the OpenCRG road description with SimXpert Motion Workspace and Adams/Car. Tire belt dynamics are captured by adding a rigid ring part to the PAC2002 tire model [ 1 ].

The contributions of vibration sources in a gasoline direct-injection (GDI) engine are identified by simulating a two input-one output model. A partial coherence function between two inputs and one output was calculated to identify the contributions of the two inputs to the output. In order to evaluate the proposed method, a principle test was performed using a laboratory test rig. The results show that the model can be used to identify the contribution of each input to the output. Finally, this model is applied to the identification of the vibration source in a GDI engine.

A flag is a global boolean variable used to achieve synchronization between various tasks of an embedded system. An application implementing flags performs actions or events based on the value of the flags. If flag variables are not implemented properly, certain synchronization related issues can arise which can lead to unexpected behavior or failure of the underlying system. In this paper, we present an automated verification technique to identify and verify flag usage patterns at an early stage of code development. We propose a two-step approach which consists of: a. identification of all potential flag variables and b. verification of flag usage patterns against predefined set of rules. The results of our experiment demonstrate that the proposed approach reduces the cost and complexity of the flag review process by almost 70%.

This paper focuses on the numerical simulations of flow around a realistic generic car model called the DrivAer body. This new open-source model is based on the geometries of two medium sized cars, the Audi A4 and the BMW 3 series, and possesses more representative car features as the well-known generic Ahmed body. In this paper, only the fastback geometry is investigated. The flow solver used is ISIS-CFD developed by CNRS and Ecole Centrale de Nantes. This solver is based on a finite-volume method, and two turbulence modelizations are used: the Explicit Algebraic Reynolds Stress Model (EARSM) and a Detached Eddy Simulation (DES). Two meshes are used. For one, the walls are described with a wall function and the mesh contains 19 million cells. This mesh is called “Mesh 1”. For the second mesh, a low-Reynolds number turbulence model for the walls is used. In this case, the mesh contains 39 million cells, and is called “Mesh 2”.

For high torque permanent magnet wheel motor, this paper describes an experimental research method to optimize and identify the motor parameters based on the results of offline calculation. In order to improve the accuracy of motor parameters identification, the motor model considering the affect of iron loss was established, and the motor parameters were identified using genetic algorithm (GA). Based on this, parameters validation experiment was performed. The results show that: parameters obtained by this method can be used to describe the steady-state and transient-state response of permanent magnet synchronous motors accurately.

Car components are exposed to the random/harmonic/impact excitation which can result in component failure due to vibration fatigue. The stress and strain loads do depend on local stress concentration effects and also on the global structural dynamics properties. Standardized fatigue testing is long-lasting, while the dynamic fatigue testing can be much faster; however, the dynamical changes due to fatigue are usually not taken into account and therefore the identified fatigue and structural parameters can be biased. In detail: damage accumulation results in structural changes (stiffness, damping) which are hard to measure in real time; further, structural changes change the dynamics of the loaded system and without taking this changes into account the fatigue load in the stress concentration zone can change significantly (even if the excitation remains the same). This research presents a new approach for accelerated vibration testing of real structures.

Cost and performance requirements are driving military and commercial systems to highly integrated, optimized systems which require more sophisticated, highly complex controls. To realize benefits and make confident decisions, the validation of both plant and control models becomes critical. To quickly develop controls for these systems, it is beneficial to develop models and determine the uncertainty of those models so as to predict performance and stability. A process of model validation for a boost circuit based on acceptance sampling is presented here. The validation process described in this paper includes the steps of defining requirements, performing a screening and exploration of the system, completing a system and parameter identification, and finally executing a validation test. To minimize the cost of experimentation and simulation, design of experiments is used extensively to limit the amount of data taken without losing information.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

A tire may be one of the most critical and complex components in vehicle dynamics and road loads analyses because it serves as the only interface between the road surface and the vehicle. Extensive research and development activities about vehicle dynamics and tire models have been published in the past decades, but it is still not clear about the applications and parameter identification associated with all of these tire models. In this literature review study, various published tire models used for vehicle dynamics and road loads analyses are compared in terms of their modeling approaches, applications and parameters identification process and methodologies. It is hoped that the summary of this literature review work can help clarify and guide the future research and development direction about tire modeling.

For more than a decade, investigations of the surface topography and chemical behavior of the boundary layer have been performed. This is of great importance for the understanding of friction, as it provides valuable insights into the dynamic processes that influence the brake pad's performance. The adaption of the boundary layer to a new load condition is of particular interest because it allows for the identification and description of mechanisms that influence macroscopically-observable effects, and quantities such as the coefficient of friction. It is possible to determine time constants that describe this process of adaption. The investigations discussed in this paper combine tribometer tests and optical investigations at the same time. Therefore, the measured coefficient of friction can be related to the observed surface topography of the brake pad.

The purpose of this work is to evaluate the efficiency of several calibration methods applied to a six-axis industrial (serial) robot. Specifically, the absolute position accuracy of a Fanuc LR Mate 200 iC industrial robot is improved using two calibration models. The first model is purely kinematic, and takes into account all geometric parameters. The second model considers, in addition, five compliance parameters related to the stiffness in joints 2, 3, 4, 5, and 6. For both models, the so-called calibration (or identification) robot configurations are selected based on an observability analysis. For each model, the efficiency of five different observability indices are compared. The parameter identification is based on the forward kinematic approach, where only the residual of the calibration positions is minimized.

Career paths are not something that one can predict. They are as much about being in the right spot at the right time with the desired skill set as they are about having a detailed, calculated plan. How does one go from being a young Original Equipment Manufacturer (OEM) test engineer to being an airline Senior Vice President of Safety, Security and Compliance and the joint industry/FAA co-chair of the Commercial Aviation Safety Team? It is a bit unusual that a non-pilot ends up on an airline Operations Specification listed as the Federal Aviation Regulations (FAR) Part 119 Director of Safety for one of the largest airlines in the world. Engineering background and experience were key stepping stones on that journey along with a healthy dose of skepticism. An initial assignment to make an airline's safety program robust, credible and data driven, much like the very successful aircraft reliability programs, set the direction and path forward.

The 9-meter wind tunnel of the National Research Council (NRC) of Canada is equipped with a boundary layer suction system, center belt and wheel rollers to simulate ground motion relative to test articles. Although these systems were originally commissioned for testing of full-scale automotive models, they are appropriately sized for ground simulation with half-scale tractor-trailer combinations. The size of the tunnel presents an opportunity to test half-scale commercial vehicles at full-scale Reynolds numbers with a model that occupies 3% of the test section cross-sectional area. This study looks at the effects of ground simulation on the force and pressure data of a half-scale model with rotating tractor wheels. A series of model changes, typical of a drag reduction program, were undertaken and each configuration was tested with both a fixed floor and with full-ground simulation to evaluate the effects of this technology on the total and incremental drag coefficients.

The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

Response Surface Models are often used as a surrogate for expensive black-box functions during optimization to reduce computational cost. Often, the CAE analysis models are highly nonlinear and multi-modal. A response surface approximation of such analysis as a result is highly multi-modal; i.e. it contains multiple local optima. A gradient-based optimizer working with such a response surface will often converge to the nearest local optimum. There does not exist any method to guarantee a global optima for non-convex multi-modal functions. For such problems, we propose an efficient algorithm to find as many distinct local optima as possible. The proposed method is specifically designed to work in large dimensions (about 100 ∼ 1000 design variables and similar number of constraints) and can identify most of the locally optimal solutions in a reasonable amount of time.