Automatic Calibration of 1 and 2-D Look-up Tables using Recursive Least-squares Identification Techniques

Look-up tables are widely used in engine management strategies to characterize nonlinear relationships between inputs such as speed and load, and the desired output. However, the calibration of such tables can be time consuming, and is prone to errors due to fluctuating engine measurements, or to small mismatches between the actual test operating condition and the desired operating point in the lookup table grid. In this paper a recursive least-squares identification technique is used to automate the calibration of the table values as the engine is operated over the desired range. The memory and computational requirements of the technique have been optimized so that it can run in real time on a typical engine management system, and the same technique may be used to adapt the table during normal operation if a feedback value is available. The adaptation rate can be adjusted depending on the noise in the available signals. The technique has been applied to the calibration of the volumetric efficiency table commonly used in gasoline engine fueling strategies using time delayed feedback from a wide-range sensor in the exhaust manifold. The algorithm was implemented on a 2.0L I4 engine, and the results are presented.