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This paper describes a new method to increase the efficiency of the battery charging process, η, which is defined as the ratio of the energy accumulated in the battery over the actual energy supplied to it. Through several simulation results, it has been found that such efficiency is a function of the current profile applied to the battery during the charging process; hence, plots describing the energy loss in the battery, time taken to achieve a desired level of charge, and power needed as a function of the charging current, are shown. In order to find the optimal charging current profile, the mathematical model of the energy loss in the battery is developed and the problem of finding the optimal current profile is formulated as an Optimal Control problem. A model based on a Lithium-Ion Battery commercially available for PHEV is used as the plant to be controlled.

The SISAME methodology is a system for extracting one-dimensional lumped parameter vehicle crash models from non-oblique crash test data, and for simulation of such models. Model extraction is based on constrained least squares optimization of an overdetermined system of target equations for the model parameters. The SISAME computer program performs extraction and simulation with a number of features that allow user control of the computations and outputs. Additional computer programs perform data assessment/correction and filtering. Experience has shown that the SISAME methodology can efficiently produce predictively useful models that accurately capture the motions of the actual crash event. The essential formulation of SISAME and some sample applications are presented in this paper.

Performance characteristics of passive, active, and broadband adaptive engine mounts are compared over a wide frequency range up to 250 Hz in the context of a quarter-vehicle heave model. The optimal damping coefficient of a rubber-metal mount is determined using random vibration theory. The small-scale active mount employs proportional-plus-integral control based on linear optimal control theory. The new adaptive hydraulic mount system implements an on-off damping control mode by using engine intake-manifold vacuum and a microprocessor-based solenoid valve controller. Through analytical methods, it is observed that this adaptive mount provides most desirable dynamic performance with regard to the engine-bounce control, shock absorption and vibration isolation performance requirements. Although technical prospects of the proposed adaptive system appear promising, in-situ performance needs to be evaluated.

The objective of this paper is to develop a self-tuning optimal control of an active suspension. An active suspension composed of an identifier and a controller is proposed in this paper. Although control strategies on active (or semi-active) suspensions have been investigated during the past few decades, some problems are not well understood yet. One of them arising from the ride control of an active suspension is that when the weight and the moments of inertia of the sprung mass are varied, the feedback gains of the controller should vary with the variation of parameters accordingly. Therefore, the identifier is proposed before the controller is designed. In the real situations, the parameter variation may occur when loadings on vehicles vary - either from passengers or payloads, especially, in the case of loading on a truck. An identification structure using parallel model reference adaptive system (MRAS) is proposed to identify the true parameters.

The main objective of this paper is to simulate the springback using combined kinematic/isotropic hardening model. Material parameters in the hardening model are identified by an inverse method. Three-point bending test is conducted on 6022-T4 aluminum sheet. Punch stroke, punch load, bending strain and bending angle are measured directly during the tests. Bending moments are then computed from these measured data. Bending moments are also calculated based on a constitutive model. Material parameters are identified by minimizing the normalized error between two bending moments. Micro genetic algorithm is used in the optimization procedure. Stress-strain curves is generated with the material parameters found in this way, which can be used with other plastic models. ABAQUS/Standard 5.8, which has the combined isotropic/kinematic hardening model, is used to simulate draw-bend of 6022-T4 series aluminum sheet. Absolute springback angles are predicted very accurately.

Weldability study has been performed on Polypropylene (PP) and PC/ABS samples to investigate how the paint layer along the weld joint affects the vibration weldability. The plastic used for this study were PP representing semicrystalline thermoplastics and PC/ABS representing amorphous thermoplastics. Both resins were molded to generate sample plaques for the study. Design of Experiment (DOE) studies were initially conducted with unpainted plaques and then repeated with the painted plaques for comparison. Optimal welding parameters were determined through DOE and the maximum weld strength under optimized welding conditions were determined and compared. Following each DOE, a regression analysis, using the weld strength as a response, was performed.