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Switched inertance hydraulic systems (SIHS) use inductive, capacitive, and switching elements to boost or "buck" (reduce) a pressure from a source to a load in an ideally lossless manner. Real SIHS circuits suffer a variety of energy losses, with throttling of flow during transitions of the high-speed valve resulting in as much as 44% of overall losses. These throttling energy losses can be mitigated by applying the analog of zero-voltage-switching, a soft switching strategy, adopted from power electronics. In the soft switching circuit, the flow that would otherwise be throttled across the transitioning valve is stored in a capacitive element and bypassed through check valves in parallel with the switching valves. To evaluate the effectiveness of soft switching in a boost converter SIHS, a lumped parameter model was constructed. Simulation demonstrates that soft switching improves the efficiency of the modeled circuit by 42% at peak load power and extends the power delivery capabilities by 77%. [ABSTRACT FROM AUTHOR]

In this paper, general strategies are presented by which a multi-domain, multi-objective, mechanism-based optimization problem may be efficiently formulated and solved by means of a genetic algorithm. These strategies include integration of traditional precision position techniques with genetic optimization, efficient selection of design variables and search bounds, and a nested optimization structure. A case study illustrating these methods is presented in which a hydraulic rescue spreader is simultaneously optimized for four objectives relating to structural efficiency and kinematic behavior. The solution obtained is shown to be equal or superior to a comparable commercially available device with respect to all four objectives. [ABSTRACT FROM AUTHOR]