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Cast aluminum alloys are normally quenched after solution treatment or solidification process to improve aging responses. Rapid quenching can lead to high residual stress and severe distortion which significantly affects dimension stability, functionality and particularly performance of the product. To simulate residual stress and distortion induced during quenching, a finite element based approach was developed by coupling an iterative zone-based transient heat transfer algorithm with material thermo-viscoplastic constitutive model. With the integrated models, the numeric predictions of residual stresses and distortion in the quenched aluminum castings are in a good agreement with experimental measurements.

The need of weight reduction for fuel reduction and CO₂ regulations enforces the use of light-weight materials for structural parts also. The importance of reinforced composites will grow in this area. While the structural behavior and the simulation up to high strain-rate processes for those materials have been in the focus of investigation for many years, nowadays the simulation of high cycle fatigue behavior is getting important as well. Efficient fatigue analysis for metals was developed by understanding the microscopic behavior (crack nucleation and initiation) and bringing it to the macroscopic level by combining it with the matching test data (SN curves, etc.). Similar approaches can be applied to composite materials as well.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

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.

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 scientific fields where, for already more than 20 years, system identification plays a crucial role is this of structural dynamics and vibro-acoustic system optimization. The experimental approach is based on the “Modal Analysis” concept. The present paper reviews the test procedure and system identification principles of this approach. The main focus though is on the real problems with which engineers, performing modal analysis on complex structures on a daily basis, are currently confronted. The added value of several new testing approaches (laser methods, smart transducers…) and identification algorithms (spatial domain, subspace, maximum likelihood,..) for solving these problems is shown. The discussed elements are illustrated with a number of industrial case studies.

This paper examines Smart Electric Power Management as it pertains to when the vehicle charging system is active. Over the past decade there have been several factors at play which have stressed the demands placed upon the vehicle electrical power system. Many of these factors present challenges to electrical power that are at cross-purposes with one another. For example, demands of new and existing electrical loads, customer expectations about load performance and battery life, and the push by governments' world-wide for increased fuel economy (FE) and reduced CO2 emissions all have direct impact and can be directly impacted by decisions made in electric power design. As the electrification of the vehicle has progressed we now have much more specific vehicle state data available and the means to share this information among on-board computers through serial data link connectivity.

Remote vehicle start systems are commonly available as an aftermarket accessory, and more recently, as a factory installed vehicle feature. These systems and their associated algorithms enable a user of the vehicle to remotely start the engine and/or other vehicle systems with the end goal of preconditioning the cabin environment, for example, if the user wishes to have the vehicle's interior heated or cooled before the user enters the vehicle. However, if the engine is remotely started for an extended period of time, the increased use of fuel, energy, and/or other resources may be greater than optimal or desired. Through the use of available vehicle sensors and enhanced algorithms, a system can be implemented which allows the passenger cabin to be heated or cooled to within a range of moderate temperatures, while reducing the resources utilized by the vehicle.

Driving through intersections can be potentially dangerous because nearly 23 percent of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year [1]. The impact of traffic intersections on trip delays also leads to waste of human and natural resources. Our goal is to increase the safety and throughput of traffic intersections using co-operative driving. In earlier work [2], we have proposed a family of vehicular network protocols, which use Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environment (WAVE) technologies to manage a vehicle's movement at intersections Specifically, we have provided a collision detection algorithm at intersections (CDAI) to avoid potential crashes at or near intersections and improve safety. We have shown that vehicle-to-vehicle (V2V) communications can be used to significantly decrease the trip delays introduced by traffic lights and stop signs.

Due to the multitude of external design constraints, such as increasing fuel economy standards, and the increasing number of global vehicle programs, developers of automotive transmission controls have had to cope with increasing levels of system complexity while at the same time being forced by the marketplace to improve system quality, reduce development costs, and improve time to market. General Motors Powertrain (GMPT) chose to meet these challenges through General Motors Company's Road-to-Lab-to-Math (RLM) strategy, particularly the Math-based method of a virtual vehicle simulation environment called System Simulation. The use of System Simulation to develop transmission control algorithms has enabled GMPT to improve product quality and reduce development times and costs associated with the dependence on physical prototypes. Additionally, System Simulation has facilitated the reuse of GMPT controls development assets, improving overall controls development efficiency.

Active suspension systems aim at increasing safety by improving vehicle ride and handling performance while ensuring superior passenger comfort. Good control of this active system can only be achieved by providing the control algorithm with reliable and accurate signals for the required quantities. This paper presents the design and development of a state estimator that accurately provides the information required by a sky-hook controller, using a minimum of sensors. The vehicle inertial parameters are estimated by an algorithm based on Monte Carlo simulations and anthropometric data. All state updating is performed using Kalman filters. The resulting performance enhancement has been proven during test drives.

The investigation of critical noise sources on pass-by noise tests is demanding development of the current techniques in order to locate and quantify these sources. One recent approach is to use beamforming techniques to this purpose. The phased array information can be processed using several methods, for example, conventional delay-and-sum algorithms, deconvolution based algorithms, such as DAMAS, and more recently, the generalized inverse beamforming. This later method, presents the advantage of separating coherent sources with better dynamic range than conventional beamforming. Also, recent developments, such as Iteratively Re-Weigthing Least Squares, increases the localization accuracy allowing it to be used in a challenging problem as a fast moving source detection, a non-stationary condition. The work will raise the main advantages and disadvantages on this method using a practical case, a passenger vehicle pass-by test.

Automobile drivers/passengers perceive automatic transmission (AT) shift quality through the torque transferred by the transmission. Clearly, torque regulation is important for transmission control. Unfortunately, a physical torque sensor has been too costly for production applications. With no torque measurement for feedback, controls in AT is mainly implemented in an open-loop fashion. Therefore, complicated adaptation algorithms are necessary while undesired shifts may still occur. To further simplify the controls and enhance its consistency and robustness, a direct torque feedback has long been desired in transmission control synthesis and development. A “virtual” torque sensor (VTS) algorithm has recently been developed to show a good potential in estimating relative torque along transmission output shaft using transmission output speed sensor and wheel speed sensors.

This paper covers the application of hybrid vibro-acoustic simulation methods to shorten the design cycle of power-plant components. A comparison is made between Frequency Response Function based and Modal based algorithms for the generation of a predictive powerplant assembly model. The effectiveness of design modifications is evaluated by loading the original and modified predictive models with experimentally identified excitation forces. The procedure is validated by correlation with experimental data.

In a parallel hybrid electric vehicle, higher fuel economy gains are typically achieved if significant electric drive (or engine-off) operation is possible, shifting the engine operating schedule so that it only runs at medium to high load for best efficiency. To enable efficient engine-off driving, a typical configuration will have a disconnect clutch between the engine and the rest of the driveline. In some configurations, when engine-on operation is requested the disconnect clutch is applied in conjunction with the traction motor/generator to crank the engine (i.e., a flying engine start). In this paper we describe the development of a control system for a flying engine start using an engine disconnect clutch. The clutch is located between the engine and electric motor, which is connected to the input of a multispeed transmission. We first describe an initial control algorithm evaluation using a driveline model.