Engine manufacturers worldwide are under pressure to provide engines that meet tougher government-mandated emissions regulations as well as increased customer expectations for durability, noise and performance, and low fuel consumption. Engines are becoming more complex—using variable valve timing, EGR (internal or external), multiple injections, and turbocharger controls (variable geometry or wastegate) as well as advanced control strategies and sophisticated exhaust after-treatment systems—to meet these demands.
When engines had only a few controlled parameters, the skilled calibrator could determine near-optimal settings using a variety of manual methods and general-purpose software. Plots of the effects and the cross-effects of parameters could be generated in Microsoft® Excel® or other mainstream analysis or plotting tools. From these plots and with the experience of the calibrators, good calibrations could be generated and refined.
Now that engines have many more controlled parameters, efficiently generating tests and analyzing the results to produce an optimal calibration is becoming increasingly difficult. Whereas using traditional full factorial mapping, three variations of three parameters with potential interactions at 11 speed/load conditions would take 297 (33*11 = 297) experiments, five variations of five variables at 11 conditions takes more than 30,000 (55*11 = 34,375) experiments. Engineers now have at least this number of variables to deal with. Going beyond three-dimensional space (more than three variables) usually requires analytical tools. Clearly, new engine and engine controls design requires new methods of mapping, optimization, and calibration.
To help engineers with these ever-increasing problems, A&D has developed ORION, a supervisory test cell control system for automating the characterization and calibration of engines.
ORION allows great flexibility in the process by taking its inputs in open, simple formats (.csv for DoE, ASAP2 for parameters). Outputs are also produced in simple, open format (.csv for data). This approach enables users to use the tools in the other parts of the process that best fit the needs of their specific application.
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