Development of Automated Mapping and Calibration Technique for Complex Engine Control Systems, 03-9323Printer Friendly Version
Inclusive Dates: 07/01/02 - Current
Background - In the pursuit to simultaneously meet the often conflicting emission regulations and consumer demands, modern engines must incorporate a number of new subsystems, for example, advanced fuel systems, after-treatment devices, camless valve-trains, and so on. However, with the increasing number of subsystems, it is difficult to make a simple one-to-one association between actuators and performance indices. From the point of view of the control system designer, it is important that cross coupling between the actuators and the performance measures be characterized (mapped). While such characterization is important in itself, it is only a step toward the final goal of determining settings for the various actuators to achieve overall performance that is optimal in some sense.
Traditionally the full-factorial tabulation method has been used to characterize an engine. In such a method, one systematically steps through the valid range of actuator settings and measures various performance indices. The optimization (calibration) step follows this exhaustive data collection. For a modern engine, with many actuators, such an approach is clearly impractical from the time and cost points of view. Simple estimates suggest that the traditional methods may require years to calibrate a modern engine.
Approach - For a control system designer, the main goal is to optimize actuator settings. Recognize that the exhaustive data mentioned above are necessary to identify globally best collection of actuator settings. From a practical standpoint, however, it suffices to have a satisfactory collection of settings, provided that they can be arrived at with significantly less cost and time. While this program will start with the full-factorial approach to calibration, the main thrust will be on designing an efficient and scalable procedure. In particular, the test team will use model-based and adaptive approaches to design experiments for selection of test points in the operating domain of the engine. For each test point, the team will use intelligent on-line search methods for actuator optimization. Embedded in the procedure will be a scheme to automatically enlarge the experimental set based on an index of goodness of the collected data.
Accomplishments - Because this work is still in the initial phases, no accomplishments can be reported.