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Case-based adaptation for automotive engine electronic control unit calibration

机译:基于案例的适应性用于汽车发动机电子控制单元校准

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摘要

The automotive engine performance is greatly affected by the calibration of its electronic control unit (ECU). The method for ECU calibration is traditionally done by trial-and-error. This traditional method consumes a large amount of time and money. To resolve this problem, case-based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA) (Craw, Jarmulak, & Rowe, 2001; Craw, Wiratunga, & Rowe, 2006; Leake, Kinley, & Wilson, 1996, 1997). CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.
机译:汽车发动机性能受其电子控制单元(ECU)的校准影响很大。 ECU校准的方法传统上是通过反复试验来完成的。这种传统方法消耗大量时间和金钱。为了解决此问题,采用了基于案例的推理(CBR),以便可以对现有的有效ECU设置进行调整以适合另一类相似的发动机。适应程序通过一个更复杂的步骤进行,即基于案例的适应(CBA)(Craw,Jarmulak,&Rowe,2001; Craw,Wiratunga,&Rowe,2006; Leake,Kinley,&Wilson,1996,1997)。 CBA是一种有效的知识管理工具,可以交互式地学习专家适应知识。本文简要回顾了CBR和CBA的方法。然后通过案例研究描述了ECU校准的应用。使用CBR和CBA,可以提高ECU的校准效率。还开发了原型系统来验证CBR在ECU校准中的有用性。

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