Vehicle active suspension system sensor reduction

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Tims, Heath Eric

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This paper describes the investigation and development of new approaches to reducing sensors used in active suspension control. This research utilized modeling, simulation, and mathematical tools to develop and investigate approaches to reducing the number of sensors. These approaches attempt to avoid changes in control techniques that have been developed and proven over time. Active suspension systems isolate vehicle sprung mass from terrain disturbances. These systems require vehicle mounted sensor information to control vehicle ride. Sensors add additional complexity and cost, and thus reduction in sensors is a potential approach to lowering cost and improving reliability of active suspension systems. Reduction also simplifies installation onto vehicle platforms by eliminating cabling and additional mounting of sensors. Each sensor is also a potential fault source and source of noise. This research addressed sensor suite reduction as one starting point for lowering cost, reducing computational load, aiding in installation, and lowering potential sources for failure. The basic strategy used to reduce sensors was first investigating equations of motion that govern dynamics of suspension systems. The next step involved developing a new analytical tool used to reduce sensors, which was called Delta-Based Estimation, utilizes a relative displacement sensor already available in typical active suspension sensor suites to estimate vehicle corner sprung mass velocity. Finally, this study made use of a test vehicle (equipped with an active suspension system) for experimental validation of numerical simulations.