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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.

Suspension design is influenced by many factors, especially by vehicle dynamics performance in ride, handling and durability. In the global automotive industry it is common to “customize” or tune suspension parameters so that a vehicle is more acceptable to a different customer base and in a different driving environment. This paper seeks to objectively quantify certain aspects of tuning via ride optimization, taking account of market differences in road surface spectral properties and loading conditions. A computationally efficient methodology for suspension optimization is developed using stochastic techniques. A small (B-class) vehicle is chosen for the study and the following main suspension parameters are selected for optimization - spring stiffness, damping rate and vertical tire stiffness. The road is characterized as a stationary random process, using scaling and shaping filters representative of comparable roads in India and the USA.

Structural stress methods are now widely used in fatigue life assessment of welded structures and structures with stress concentrations. The structural stress concept is based on the assumption of a global stress distribution at critical locations such as weld toes or weld throats, and there are several variants of structural stress approaches available. In this paper, the linear traction stress approach, a nodal force based structural stress approach, is reviewed first. The linear traction stress approach offers a robust procedure for extracting linear traction stress components by post-processing the finite element analysis results at any given hypothetical crack location of interest. Pertinent concepts such as mesh-insensitivity, master S-N curve, fatigue crack initiation and growth mechanisms are also discussed.

The global energy situation, the dependence of the transportation sector on fossil fuels, and a need for rapid response to the global warming challenge, provide a strong impetus for development of fuel efficient vehicle propulsion. The task is particularly challenging in the case of trucks due to severe weight/size constraints. Hybridization is the only approach offering significant breakthroughs in near and mid-term. In particular, the series configuration decouples the engine from the wheels and allows full flexibility in controlling the engine operation, while the hydraulic energy conversion and storage provides exceptional power density and efficiency. The challenge stems from a relatively low energy density of the hydraulic accumulator, and this provides part of the motivation for a simulation-based approach to development of the system power management. The vehicle is based on the HMMWV platform, a 4×4 off-road truck weighing 5112 kg.

The current test methods are insufficient to evaluate and ensure the safety and reliability of vehicle system for all possible dynamic situations including the worst cases such as rollover, spin-out and so on. Although the known NHTSA J-turn and Fish-hook steering maneuvers are applied for the vehicle performance assessment, they are not enough to predict other possible worst case scenarios. Therefore, it is crucial to search for the various worst cases including the existing severe steering maneuvers. This paper includes the procedure to search for other useful worst case based upon the existing worst case scenarios in terms of rollover and its application in simulation basis. The human steering angle is selected as a design variable and optimized to maximize the index function to be expressed in terms of vehicle roll angle. The obtained scenarios were enough to generate the worse cases than NHTSA ones.

This paper presents our efforts to formalize the knowledge domain of nondestructive quality control of automotive composite components with organic (resin) matrices and to develop a prototype knowledge-based system, called NICC for Nondestructive Inspection of Composite Components, to help in the quality assurance of individual components. Geometric and bonding characteristics of parts and assemblies are taken into account, as opposed to the better understood evaluation of test specimens. The reasoning process was divided in two stages: in the first stage all flaws that might be present in the given part are characterized; in the second stage appropriate nondestructive testing procedures are specified to detect each of the possible flaws. The use of nondestructive techniques in the inspection of composites is fairly recent and hence, the knowledge required to develop an expert system is still very scattered and not fully covered in the literature.

The hybrid FEA method combines the conventional FEA method with the energy FEA (EFEA) for computing the structural vibration in vehicle structures when the excitation is applied on the load bearing stiff structural members. Conventional FEA models are employed for modeling the behavior of the stiff members in the vehicle. In order to account for the effect of the flexible members in the FEA analysis, appropriate damping and spring/mass elements are introduced at the connections between stiff and flexible members. Computing properly the values of these damping and spring/mass elements is important for the overall accuracy of the computations. Utilizing in these computations the analytical solutions for the driving point impedance of infinite or semi-infinite members introduces significant approximations.

Improving the performance characteristics of a typical disc brake encompasses a number of design strategies as well as limitations imposed by cost objectives. Utilizing pad loading uniformity in a design is one strategy that offers an improvement in desired performance characteristics, including a reduction in tapered lining wear as well as a possible reduced propensity for noise generation. To approach this design strategy, a procedure has been developed to tailor the brake pad lining profile to maximize pad loading uniformity in a multibody dynamics model of a typical disc brake. In determining an optimal lining configuration, a suitable compromise for gaining beneficial performance improvements in a cost effective manner is reached. The implementation of this design strategy involves the parametric definition of the lining profile by introducing a series of variables that are linked to the profile markers.

In this paper, a simulation-based dynamic rollover evaluation procedure is described. This work is based on the worst-case methodology developed at the University of Michigan, and is the result of a collaborated research project between the University of Michigan and TRW Inc. The target vehicle studied in this paper is a large production volume SUV. This vehicle is equipped with a production-intent TRW Vehicle Stability Control (VSC) system. The main goals of this paper are to (i) study the rollover propensity of this SUV, as influenced by vehicle and environment parameters such as vehicle speed, road condition, etc.; and (ii) investigate whether, and by how much, does the VSC system influence the rollover propensity of this SUV. The modeling, evaluation procedure, and preliminary evaluation results are reported.

This paper proposes an approach for optimal design of multilevel systems under uncertainty. The approach utilizes the stochastic extension of the analytical target cascading formulation. The reliability of satisfying the probabilistic constraints is computed by means of the most probable point method using the hybrid mean value algorithm. A linearization technique is employed for estimating the propagation of uncertainties throughout the problem hierarchy. The proposed methodology is applied to a piston-ring/cylinder-liner engine subassembly design problem. Specifically, we assess the impact of variations in manufacturing-related properties such as surface roughness on engine attributes such as brake-specific fuel consumption. Results are compared to the ones obtained using Monte Carlo simulation.

We have developed new CAE tools in the concept design process based on First Order Analysis (FOA). Joints are often modeled by rotational spring elements. However, it is very difficult to obtain good accuracy. We think that one of the reasons is the influence of the nonlinear behavior due to local elastic buckling. Automotive body structures have the possibility of causing local buckling since they are constructed by thin walled cross sections. In this paper we focus on this behavior. First of all, we present the concept of joint analysis in FOA, using global-local analysis. After that, we research nonlinear behavior in order to construct an accurate joint reduced model. (1) The influence of local buckling is shown using uniform beams. (2) Stiffness decrease of joints due to a local buckling is shown. (3) The way of treating joint modeling considering nonlinear behavior is proposed.

A new method for crashworthiness optimization of vehicle structures is presented, where an early design exploration is done by the optimization of an equivalent mechanism approximating a vehicle structure. An equivalent mechanism (EM) is a network of rigid bodies connected by prismatic and revolute joints with special nonlinear springs. These springs are designed to mimic the force-displacement characteristics of thin-walled beams often found in the vehicle body structures. A computer software is implemented that allows the designer to quickly construct an equivalent mechanism model of a structure using a graphical user interface (GUI) to optimize the model for given objectives prior to final tuning using finite element (FE) models. A case study of a vehicle front substructure consisting of mid and lower rails is presented, which demonstrates that the new approach can obtain a better design with less computational resources than the direct optimization of a FE model.

The Moulton Hydragas suspension system improves small car ride quality by interconnecting the front and rear wheel on each side of the vehicle via a hydraulic fluid pipe between the front and rear dampers. A Hydragas system from a Rover Group MGF sports car was statically and dynamically tested to generate stiffness and damping coefficient matrices. The goal was to develop the simplest possible model of the system for use in ride quality studies. A linear model showed reasonable accuracy over restricted frequency ranges. A second model used bilinear spring and damping constants, and was more accurate for predicting force at both the front and rear units for frequencies from 1 to 8 Hz. The Hydragas system static stiffness parameters, when used in the model, caused peak force underprediction in the jounce direction. The bilinear model required increased jounce stiffness to account for hysteresis in the rubber elements of the system, and dynamic fluid flow phenomena.

Intermediate shaft assembly is used to connect steering gear to the steering wheel. The primary function of the intermediate shaft is to transfer torsional loads. There is a high probability of noise propagating through the Intermediate shaft to the driver. The current standard for measuring the noise is by performing vehicle level subjective evaluations. If improperly clamped at either of the yokes, a sudden change in the direction of the torsional load on the Intermediate shaft can generate a displeasing noise. Noise can also be generated from the constant velocity joint. Intermediate shaft noise can be measured using a microphone or can be correlated to acceleration values. The benefit of measuring the acceleration over sound pressure level is the reduction of complexity of the test environment and test set up. The nature of the noise in question requires the filtering of low frequency data. This paper presents a new test procedure that has been developed by General Motors.

The automotive industry has been witnessing a major shift towards downsized boosted direct injection engines due to diminishing petroleum reserves and increasingly stringent emission targets. Boosted engines operate at a high mean effective pressure (MEP), resulting in higher in-cylinder pressures and temperatures, effectively leading to increased possibility of abnormal combustion events like knock and pre-ignition. Therefore, the compression ratio and boost pressure in modern engines are restricted, which in-turn limits the engine efficiency and power. To mitigate conditions where the engine is prone to knocking, the engine control system uses spark retard and/or mixture enrichment, which decrease indicated work and increase specific fuel consumption. Several researchers have advocated water injection as an approach to replace or supplement existing knock mitigation techniques.

This paper proposes a method to make diagnostic/prognostic judgment about the health of a tire, in term of its wear, using existing on-board sensor signals. The approach focuses on using an estimate of the effective rolling radius (ERR) for individual tires as one of the main diagnostic/prognostic means and it determines if a tire has significant wear and how long it can be safely driven before tire rotation or tire replacement are required. The ERR is determined from the combination of wheel speed sensor (WSS), Global Positioning sensor (GPS), the other motion sensor signals, together with the radius kinematic model of a rolling tire. The ERR estimation fits the relevant signals to a linear model and utilizes the relationship revealed in the magic formula tire model. The ERR can then be related to multiple sources of uncertainties such as the tire inflation pressure, tire loading changes, and tire wear.

Existing methods for design optimization under uncertainty assume that a high level of information is available, typically in the form of data. In reality, however, insufficient data prevents correct inference of probability distributions, membership functions, or interval ranges. In this article we use an engine design example to show that optimal design decisions and reliability estimations depend strongly on uncertainty characterization. We contrast the reliability-based optimal designs to the ones obtained using worst-case optimization, and ask the question of how to obtain non-conservative designs with incomplete uncertainty information. We propose an answer to this question through the use of Bayesian statistics. We estimate the truck's engine reliability based only on available samples, and demonstrate that the accuracy of our estimates increases as more samples become available.

This study is to explore the application of electrorheology (ER) to the real-time control of damping forces that are transmitted through the nose landing gear for an F-106B aircraft. The main part of the landing gear is a strut that consists of a pneumatic spring and an ER controlled damper that is situated on the strut centerline and applies a force directly opposing the vertical displacement of the nose wheel. The damping element rotates in response to strut displacement, employing a co-axial arrangement of stator and rotor plates connected to the opposing electrodes in the control circuit. The vertical displacement is converted into rotation of the damper through a screw-nut mechanism. The ER fluid between the electrodes is thus engaged in shear along circumferential lines of action. This design results in a fast time response and a high ratio of strut forces achieved under ER- vs. zero-field control. Compact size and simplicity in fabrication are also attained.

Traditional reliability assessment methods based on physical testing can require prohibitively large sample sizes in many applications. This has led manufacturers to employ virtual testing using CAE models in place of physical testing. However, when the CAE models are not valid, the resulting reliability assessment may be unreliable. In this paper we develop theory and methodology in which traditional physical testing can be used in conjunction with CAE models to create a new type of accelerated testing that requires smaller sample sizes than traditional test plans while exhibiting robustness with respect to inaccuracies in the CAE models. These test plans are implemented by physically testing a biased sample of products and employing a variance reduction technique such as importance sampling. The CAE model is used as a prior belief for failure probability from which one can derive the sampling plan which minimizes the variance.

In this work, we discuss statistical energy methods for predicting mid-frequency vibration transmission between two spring-coupled substructures with parameter uncertainties. We adopt a parameter-based approach, which allows us to relax certain assumptions associated with a classical Statistical Energy Analysis (SEA) approximation. We consider both a numerical method and an analytical method. The latter is called a Parameter-based Statistical Energy Method (PSEM). An example of two elastic bars coupled by a single spring or multiple springs is examined. The power transmitted from the excited substructure to the other substructure is calculated and compared for the various methods.