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Combatting the modification of automotive control systems is a current and future challenge for OEMs and suppliers. ‘Chip-tuning’ is a manifestation of manipulation of a vehicle's original setup and calibration. With the increase in automotive functions implemented in software and corresponding business models, chip tuning will become a major concern. Recognizing and reporting of tuned control units in a vehicle is required for technical as well as legal reasons. This work approaches the problem by capturing the behavior of relevant control units within a machine learning system called a recognition module. The recognition module continuously monitors vehicle's sensor data. It comprises a set of classifiers that have been trained on the intended behavior of a control unit before the vehicle is delivered. When the vehicle is on the road, the recognition module uses the classifier together with current data to ascertain that the behavior of the vehicle is as intended.

A method has been developed for calculating the internal temperature distribution in an aircraft tire while free rolling under load. The method uses an approximate stress analysis of each point in the tire as it rolls through the contact patch, and from this stress change the mechanical work done on each volume element may be obtained and converted into a heat release rate through a knowledge of material characteristics. The tire cross-section is then considered as a body with internal heat generation, and the diffusion equation is solved numerically with appropriate boundary conditions at the wheel and runway surface. Comparisons with buried thermocouples in actual aircraft tires shows good agreement.

Simulations conducted on-board in a vehicle control module can offer valuable information to control strategies. Continued improvements to on-board computing hardware make online simulations of complex dynamic systems such as drivetrains within reach. This capability enables predictions of the system response to various control actions and disturbances. Implementation of online simulations requires model initialization that is consistent with the physical drivetrain state. However, sensor signals and estimated variables are susceptible to errors, compromising the accuracy of the initialization and any future state predictions as the simulation proceeds through the numerical integration process. This paper describes a drivetrain modeling and analysis method that accounts for initialization errors, thereby enabling accurate simulations of system behaviors.

This paper presents the development of surrogate models (metamodels) for evaluating the bearing performance in an internal combustion engine. The metamodels are employed for performing probabilistic analyses for the engine bearings. The metamodels are developed based on results from a simulation solver computed at a limited number of sample points, which sample the design space. An integrated system-level engine simulation model, consisting of a flexible crankshaft dynamics model and a flexible engine block model connected by a detailed hydrodynamic lubrication model, is employed in this paper for generating information necessary to construct the metamodels. An optimal symmetric latin hypercube algorithm is utilized for identifying the sampling points based on the number and the range of the variables that are considered to vary in the design space.

This paper presents the development of surrogate models (metamodels) for evaluating the bearing performance in an internal combustion engine without performing time consuming analyses. The metamodels are developed based on results from actual simulation solvers computed at a limited number of sample points, which sample the design space. A finite difference bearing solver is employed in this paper for generating information necessary to construct the metamodels. An optimal symmetric Latin hypercube algorithm is utilized for identifying the sampling points based on the number and the range of the variables that are considered to vary in the design space. The development of the metamodels is validated by comparing results from the metamodels with results from the actual bearing performance solver over a large number of evaluation points. Once the metamodels are established they are employed for performing probabilistic analyses.

The preliminary design of a single engine business jet is presented. The airplane is intended to fill a market niche surrounded by several types of airplanes: single engine (piston and turboprop) and entry-level twin engine airplanes (turboprop and turbofan). The Williams-Rolls FJ44 turbofan engine, with a takeoff thrust rating of 1900 pounds, is chosen as the powerplant because of its low acquisition and maintenance costs. The airplane is designed to carry four persons and baggage 1500 n.m. with VFR reserves, and is intended to meet FAR 23 standards — including the 61 knot single engine stall speed requirement. A parametric analysis of wing aspect ratio, thickness, and taper is performed to determine the best planform from the standpoint of weight, cruise speed, and cost. Maximum cruise speed is estimated to be 371 knots and the airplane purchase price is estimated to be 1.98 million. These results indicate the airplane will satisfy intended market niche.

In this study, a new actuation system concept is developed for automotive transmission shift control. A piezoelectric-hydraulic pump (in short, PHP) based actuation system is one of the potential alternatives that can replace the current electro-hydraulic actuation system in automotive transmissions. Their feasibility has been successfully demonstrated in a lab environment. This study extends the application of the PHP actuator into an AT (Automatic Transmission) test-bed to validate the effectiveness of the new power-by-wire actuation concept. To demonstrate the potentials of the PHP actuator, a nonlinear sliding mode control for force tracking and hardware-in-the-loop simulation (in short, HILS) are performed.

Automated clutches for vehicle startup is being increasingly deployed in commercial trucks for benefits, which include driver comfort, gradient performance, improved clutch life, emissions and driveline vibration reduction potential. The process of designing the controller is divided into 2 parts. Firstly, the parameter estimation of previously developed driveline models is carried out. The procedure involves an off-line minimization technique based on measured and estimated speeds. Secondly, the nominal plant model is used to develop LQR based optimal control strategy, which takes into account the slip time, dissipated power and slip acceleration. Mathematical expression of the performance index is clearly developed. A variety of clutch lock up profiles can be incorporated by changing a single tuning parameter, thus providing the driver the ability to select a launch profile based on specific driving objectives.

A novel application in the field of Life Cycle Assessment is presented that investigates optimal vehicle retirement timing and design life. This study integrates Life Cycle Energy Analysis (LCEA) with Dynamic Replacement Modeling and quantifies the energy tradeoffs between operating an older vehicle versus replacing it with a new more energy efficient model. The decision to keep or replace a vehicle to minimizes life cycle energy consumption is influenced by several factors including vehicle production energy, current vehicle's fuel economy and its deterioration with age, the improvement in fuel economy technology of new model vehicles and annual vehicle miles traveled (VMT). Model simulations explore vehicle replacement under incremental improvements in vehicle technology and leapfrog technology improvements such as with the PNGV (Partnership for a New Generation of Vehicles).

This study investigates a novel approach towards boosted HCCI operation, which makes use of all engine system components in order to maximize overall efficiency. Four-cylinder boosted HCCI engines have been modeled employing valve strategies and turbomachines that enable high load operation with significant efficiency benefits. A commercially available engine simulation software, coupled to the University of Michigan HCCI combustion and heat transfer correlations, was used to model the HCCI engines with three different boosting configurations: turbocharging, variable geometry turbocharging and combined supercharging with turbocharging. The valve strategy features switching from low-lift Negative Valve Overlap (NVO) to high-lift Positive Valve Overlap (PVO) at medium loads. The new operating approach indicates that heating of the charge from external compression is more efficient than heating by residual gas retention strategies.

A fast and accurate journal bearing elastohydrodynamic analysis is presented based on a finite difference formulation. The governing equations for the oil film pressure, stiffness and damping are solved using a finite difference approach. The oil film domain is discretized using a rectangular two-dimensional finite difference mesh. In this new formulation, it is not necessary to generate a global fluidity matrix similar to a finite element based solution. The finite difference equations are solved using a successive over relaxation (SOR) algorithm. The concept of “Influence Zone,” for computing the dynamic characteristics is introduced. The SOR algorithm and the “Influence Zone” concept significantly improve the computational efficiency without loss of accuracy. The new algorithms are validated with numerical results from the literature and their numerical efficiency is demonstrated.

In this research, off-road vehicle simulation is performed with tire-soil interaction model. The predictive semi-analytical model, which is originally developed for tire-snow interaction model by Lee [4], is applied as a tire-soil interaction model and is implemented to MSC/ADAMS, commercial multi-body dynamic software. It is applied to simulate the handling maneuver of military vehicle HMMWV. Two cases are simulated with Michigan sandy loam soil property. Each case has two maneuvers, straight-line brake and step steer (J-turn). First, tire-soil interaction model and conventional on-road tire model are simulated on the flat road of the same frictional coefficient. The proposed tire-soil interaction model provided larger force under the same slip. Second, the same maneuvers are performed with real off-road frictional coefficient. The proposed tire-soil model can be validated and the behavior of the off-road vehicle can be identified through two simulation cases.

The cooling system of Series Hybrid Electric Vehicles (SHEVs) is more complicated than that of conventional vehicles due to additional components and various cooling requirements of different components. In this study, a numerical model of the cooling system for a SHEV is developed to investigate the thermal responses and power consumptions of the cooling system. The model is created for a virtual heavy duty tracked SHEV. The powertrain system of the vehicle is also modeled with Vehicle-Engine SIMulation (VESIM) previously developed by the Automotive Research Center at the University of Michigan. VESIM is used for the simulation of powertrain system behaviors under three severe driving conditions and during a realistic driving cycle. The output data from VESIM are fed into the cooling system simulation to provide the operating conditions of powertrain components.

This paper assesses the technical potential, costs and benefits of improving the fuel economy of light-duty trucks over the next five to ten years in the United States using conventional technologies. We offer an in-depth analysis of several technology packages based on a detailed vehicle system modeling approach. Results are provided for fuel economy, cost, oil savings and reductions in greenhouse gas emissions. We examine a range of refinements to body, powertrain and electrical systems, reflecting current best practice and emerging technologies such as lightweight materials, high-efficiency IC engines, integrated starter-generator, 42 volt electrical system and advanced transmission. In this paper, multiple technological pathways are identified to significantly improve fleet average light-duty-truck fuel economy to 27.0 MPG or higher with net savings to consumers.

Electric power assisted steering (EPAS) systems are widely adopted in modern vehicles to reduce the steering effort of drivers. In rack EPAS, assist torque is applied by a motor and transmitted through two key mechanical components: ball bearing and ball nut assembly (BNA) to turn the front wheels. Large combined load and manufacturing errors not only make it hard to accurately calculate the load distribution in the ball bearing and BNA for the purpose of sizing, but also make the friction behavior of EPAS gear complicated. Rack EPAS gear is well known to suffer from “stick-slip” (i.e., sticky feel sensed by the driver), which affects the user experience. “Stick-slip” is an extreme case of friction variation mainly coming from ball bearing and BNA. Finite Element Analysis (FEA) in commercial software like ANSYS is usually conducted to study the load distribution and friction of ball bearing and BNA.

Some body parts, such as the head and the hand, change their orientation during motion. Orientation can be conveniently and elegantly represented using quaternions. The method has several advantages over Euler angles in that the problem of gimbal lock is avoided and that the orientation is represented by a single mathematical object rather than a collection of angles that can be redefined in various arbitrary ways. The use of quaternions has been popular in animation applications for some time, especially for interpolating motions. We will introduce some new applications involving statistical methods for quaternions that will allow us to present meaningful averages of repeated motions involving orientations and make regression predictions of orientation. For example, we can model how the glancing behavior of the head changes according to the target of the reach and other factors.

Adjusting the Residual Gas Fraction (RGF) by means of Variable Valve Actuation (VVA) is a strong candidate for controlling the ignition timing in Homogeneous Charge Compression Ignition (HCCI) engines. However, at high levels of residual gas fraction, insufficient mixing can lead to the presence of considerable temperature and composition variations. This paper extends previous modeling efforts to include the effect of RGF distribution on the onset of ignition and the rate of combustion using a multi-dimensional fluid mechanics code (KIVA-3V) sequentially with a multi-zone code with detailed chemical kinetics. KIVA-3V is used to simulate the gas exchange processes, while the multi-zone code computes the combustion event. It is shown that under certain conditions the effect of composition stratification is significant and cannot be captured by a single-zone model or a multi-zone model using only temperature zones.

High-fidelity overall vehicle simulations require efficient computational routines for the various vehicle subsystems. Typically, these simulations blend theoretical dynamic system models with empirical results to produce computer models which execute efficiently. Provided that the internal combustion engine is a dominant source of vehicle vibration, knowledge of its dynamic characteristics throughout its operating envelope is essential to effectively predict vehicle response. The present experimental study was undertaken to determine the rigid body modal content of engine block vibration of a modern, heavy-duty Diesel engine. Experiments were conducted on an in-line six-cylinder Diesel engine (nominally rated at 470 BHP) which is used in both commercial Class-VIII trucks, and on/off-road military applications. The engine was mounted on multi-axis force transducers in a dynamometer test cell in the standard three-point configuration.

The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance.

This paper presents the utilization of alternative correlation functions in the Kriging method for generating surrogate models (metamodels) for the performance of the bearings in an internal combustion engine. Originally, in the Kriging method an anisotropic exponential covariance function is developed by selecting optimal correlation parameters through optimization. In this paper an alternative nonparametric isotropic covariance approach is employed instead for generating the correlation functions. In this manner the covariance for spatial data is evaluated in a more straightforward manner. The metamodels are developed based on results from a simulation solver computed at a limited number of sample points, which sample the design space.