November 8, 2005
Purdue method shows promise for improving auto suspensions
WEST LAFAYETTE, Ind. Mechanical engineers at Purdue University have demonstrated a new method for analyzing the components of automotive suspension systems in work aimed at improving the performance, reducing the weight and increasing the durability of suspensions.
The researchers have demonstrated that their method can be used to show precisely how a part's performance is changed by damage and also how its changing performance affects other parts in the suspension.
Findings are detailed in a paper being presented Wednesday (Nov. 9) during the International Mechanical Engineering Congress and Exposition in Orlando, Fla. The conference is sponsored by the American Society of Mechanical Engineers.
The approach represents a potential change in how automotive suspension systems will be designed in the future, said Douglas E. Adams, an associate professor of mechanical engineering who is leading the research.
"The way it's done now is that each of the parts making up the suspension are manufactured to be as rugged as possible," Adams said. "Usually, different suppliers provide the different components, and what they do as good suppliers is optimize the strength and durability of their component.
"The problem with this approach is that some of the parts are over-engineered and heavier than they need to be because they are designed to withstand greater forces than they will encounter once they are integrated into the system. This results in a heavy suspension system that doesn't handle very well, and higher fuel and steel consumption than you would like.
"A better, more integrated approach that automakers are now pursuing is to test the entire suspension by analyzing parts, not as isolated units but as interconnected components. That way, we will learn more precisely how individual parts interact with each other, and we will be able to design parts that are just as light and rugged as they need to be but not too heavy or rugged."
The integrated approach is particularly important for the design of suspension systems because one damaged part can cause heavier strain on surrounding parts. If engineers know which parts are most prone to damage, those parts can be built heavier and other parts can be made lighter, reducing the overall weight and improving the performance of the suspension.
A suspension system consists of parts such as bolts, rubber bushings, coil springs, steering mechanisms and tie rods. The method developed at Purdue senses naturally occurring vibration patterns to detect damage to components. Sensors called "tri-axial accelerometers" are attached to suspension components and are used to collect data as vibration passes through the components. The data are fed to a computer, where complex software programs interpret the information to analyze each part's performance.
Such "fault-identification" methods may not only provide information for designing better suspensions but also might be used for future "structural health monitoring" systems in cars that automatically detect damaged parts and estimate how long they will last.
When perfected, such a "systems approach" could provide a competitive edge to companies that make suspension parts. The work is funded by ArvinMeritor Inc., which makes suspension components at its plant in Columbus, Ind. The research also is supported by the Center for Advanced Manufacturing, located in Purdue's Discovery Park, the university's hub for interdisciplinary research.
"We want to develop instrumentation, sensing methods and technologies and also ways to process data that industry can use to conduct durability tests on so-called integrated suspensions," Adams said. "The company that designs an integrated suspension system that is lighter and lasts longer than the component-wise suspension will have a competitive advantage over other companies."
The research paper being presented this week, written by mechanical engineering doctoral student Muhammad Haroon and Adams, focuses on bolts connecting the various components in the suspension system of a luxury sedan. In research conducted at the university's Ray W. Herrick Laboratories, the engineers showed that their system was able to detect damaged bolts, precisely determine how a bolt's performance was affected by the damage and how its changing performance affected other parts in the suspension system.
"What we've shown in this particular paper is that we can detect very small changes in a part's performance when it is damaged, and we've also been able to quantify the changes, which is really significant," Adams said. "We quantify the changes by turning data into information using a software algorithm that utilizes an embedded sensitivity model, which we developed.
"The reason it's important to quantify the change is that, if we know one part is experiencing a failure mechanism of a certain type and another component is experiencing increasing strain as a result of the damaged part, we can figure out which parts need to be heaviest and which can be lighter."
The researchers hope to complete work to develop the method in less than two years, at which time it could be ready for commercial use.
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Active and Event-Driven Passive Mechanical Fault Identification in Ground Vehicle Suspension Systems
School of Mechanical Engineering, Purdue University
Data interrogation methodologies are needed for identifying loads and faults in suspensions, tires, and other vehicle components to help design more durable systems and reduce the total cost of ownership. The application of passive and active data interrogation methodologies to passenger vehicle suspension systems is discussed here. For passive diagnostics, operating acceleration response data in conjunction with fundamental mechanics models are utilized. Mechanical faults in suspension components, e.g. degradation to shock, are identified using force state maps and transmissibility functions. First, it is shown that damage causes changes in the frequency characteristics of restoring forces, provided by the force state maps, which help to detect damage. Second, autoregressive nonlinear transmissibility models are used to locate faults and also characterize the degree to which faults alter nonlinear correlations in the response data. Force state maps are suited to narrow band inputs (e.g., sinusoidal) and transmissibility models are suited to broad-band inputs (e.g., random). This difference in preferential bandwidth for the two different data analysis methods motivates the selection of the diagnostic algorithm in an event-driven manner. For active diagnostics, experimental sensitivity functions, which are algebraic combinations of measured frequency response data, estimate the change in the forced response of the system with perturbation in stiffness or damping. By comparing the sensitivity functions to finite difference functions, faults can be detected, located, and quantified. The passive and active techniques are applied to experimental vehicle data and various issues (e.g., quantifying faults) are discussed.
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